The present application incorporates by reference the following U.S. patent application Ser. No. 16/144,992, filed Sep. 27, 2018, U.S. patent application Ser. No. 16/146,533, filed Sep. 28, 2018, now U.S. Pat. No. 11,178,259, U.S. patent application Ser. No. 16/146,324, filed Sep. 28, 2018, now U.S. Pat. No. 10,798,224, U.S. patent application Ser. No. 16/146,916, filed Sep. 28, 2018, now U.S. Pat. No. 10,819,831, U.S. patent application Ser. No. 16/236,032, filed Dec. 28, 2018, now U.S. Pat. No. 11,212,373, U.S. patent application Ser. No. 16/363,495, filed Mar. 25, 2019, now U.S. Pat. No. 11,178,260, U.S. patent application Ser. No. 16/368,396, filed on Mar. 26, 2019, U.S. patent application Ser. No. 16/368,338, filed on Mar. 28, 2019, now U.S. Pat. No. 11,159,651, U.S. patent application Ser. No. 16/365,484, filed on Mar. 26, 2019, now U.S. Pat. No. 11,095,758, U.S. patent application Ser. No. 16/368,368, filed on Mar. 28, 2019, U.S. patent application Ser. No. 16/368,214, filed on Mar. 28, 2019, now U.S. Pat. No. 11,368,560, U.S. patent application Ser. No. 16/936,228, filed Jul. 22, 2020, now U.S. Pat. No. 11,477,123, U.S. patent application Ser. No. 16/935,982, filed Jul. 22, 2020, now U.S. Pat. No. 11,558,348, and U.S. patent application Ser. No. 16/936,143, filed Jul. 22, 2020, all in their entirety.
The disclosure relates generally to the field of electronic devices, as well as networks thereof and including computerized networking stack infrastructures.
The consumer electronics industry has seen explosive growth in network connectivity. As an example, Internet connectivity is virtually ubiquitous across many different device types for a variety of different applications and functionalities. The successful implementation of network connectivity over a myriad of different usage cases has been enabled by the principles of modular design and abstraction. Specifically, the conventional network communication paradigm incorporates multiple modular software “layers” into a “communication stack.” Each layer of the communication stack separately manages its own implementation specific considerations and provides an “abstracted” communication interface to the next layer. In this manner, different applications can communicate freely across different devices without considering the underlying network transport.
For a variety of reasons, network communication stacks have historically been executed as kernel space processes. Kernel space processes are executed at the highest priority and privilege levels. This treatment was necessary to, for example, efficiently use scarce network resources. Over time, networking connectivity has commoditized, and device expectations have become more aggressive. As a result, most network communications are low priority relative to other device tasks.
Incipient consumer devices, such as, the iPhone®, MacBook®, iPad®, etc. to provide some examples have modified their network communication stack to execute as non-kernel space processes. Non-kernel tasks can be executed according to various prioritizations and/or privileges. Within this context, new solutions for thread-level execution in non-kernel space are needed.
Some embodiments of this disclosure describe a computer system. The computer system includes a shared memory having a submission queue and a completion queue, a shared packet pool, a network interface within a kernel space, and a device driver within a non-kernel space. The network interface can write a data packet into the shared packet pool and queue a pointer into the submission queue that indicates a location of the data packet in the shared packet pool. The device driver can de-reference the pointer in the submission queue to read the data packet from the shared packet pool and write a completion status into the completion queue in response to reading the data packet from the shared packet pool.
In some embodiments, the device driver can return the data packet to the network interface in response to writing the completion status.
In some embodiments, the shared packet pool can include a transmit packet pool and a receive packet pool. In these embodiments, the network interface can write the data packet into the transmit packet pool and the device driver can de-reference the pointer to read the data packet from the transmit packet pool.
In some embodiments, the device driver can de-reference the pointer to read the data packet from the transmit packet pool on a per-packet basis.
In some embodiments, the network interface can allocate storage within the receive packet pool to write a second data packet and queue a second pointer into the submission queue that indicates a location of the second data packet in the receive packet pool. In these embodiments, the device driver can de-reference the second pointer in the submission queue to write data into the second data packet in the receive packet pool and write a second completion status into the completion queue in response to writing the data. In these embodiments, the device driver can de-reference the second pointer to write the data into a plurality of spans of a cloned object. In these embodiments, the second pointer can indicate a location of the plurality of spans of the cloned object. In these embodiments, the network interface can de-reference the second pointer to read the plurality of spans of the cloned object from the receive packet pool.
Some embodiments of this disclosure describe a method of operating a computer system. The method includes writing a data packet from a kernel space into a shared packet pool; queuing a pointer indicating a location of the data packet in the shared packet pool; de-referencing the pointer to read the data packet from the shared packet pool into a non-kernel space; and writing a completion status in response to reading the data packet from the shared packet pool.
In some embodiments, the method further includes returning the data packet to the kernel space in response to writing the completion status.
In some embodiments, writing the data packet includes writing the data packet into a transmit packet pool of the shared packet pool. In these embodiments, the de-referencing includes de-referencing the pointer to read the data packet from the transmit packet pool. In these embodiments, the de-referencing includes de-referencing the pointer to read the data packet from the transmit packet pool on a per-packet basis.
In some embodiments, the method further includes allocating storage within the receive packet pool to write a second data packet; queuing a second pointer that indicates a location of the second data packet in the receive packet pool; de-referencing the second pointer to write data from the non-kernel space into the second data packet in the receive packet pool; and writing a second completion status in response to writing the data. In some embodiments, the de-referencing the second pointer includes de-referencing the second pointer to write the data into a plurality of spans of a cloned object. In some embodiments, the second pointer can indicate a location of the plurality of spans of the cloned object. In some embodiments, the can method further include de-referencing the second pointer to read the clone object from the receive packet pool into the kernel space.
Some embodiments of this disclosure describe a non-transitory storage medium that can store one or more computer programs, the one or more computer programs, when executed by a computer system, configure the computer system to perform operations. The operations can include writing a data packet from a kernel space into a shared packet pool; queuing a pointer indicating a location of the data packet in the shared packet pool; de-referencing the pointer to read the data packet from the shared packet pool into a non-kernel space; and writing a completion status in response to reading the data packet from the shared packet pool.
In some embodiments, the operations can include returning the data packet to the kernel space in response to writing the completion status.
In some embodiments, the writing the data packet can include writing the data packet into a transmit packet pool of the shared packet pool. In these embodiments, the de-referencing can include de-referencing the pointer to read the data packet from the transmit packet pool. In these embodiments, the de-referencing can include de-referencing the pointer to read the data packet from the transmit packet pool on a per-packet basis. In these embodiments, the operations can include allocating space for a second data packet to be written into the receive packet pool; queuing a second pointer indicating a location of the second data packet in the receive packet pool; de-referencing the second pointer to write data from the non-kernel space into the second data packet in the receive packet pool; and writing a second completion status in response to writing the data. In these embodiments, the de-referencing the second pointer can include de-referencing the second pointer to write the data into a plurality of spans of a cloned object.
Other features and advantages of the present disclosure will immediately be recognized by persons of ordinary skill in the art with reference to the attached drawings and detailed description of exemplary embodiments as given below.
This Summary is provided merely for purposes of illustrating some embodiments to provide an understanding of the subject matter described herein. Accordingly, the above-described features are merely examples and should not be construed to narrow the scope of the subject matter in this disclosure. Other features, aspects, and advantages of this disclosure will become apparent from the following Detailed Description, Figures, and Claims.
The accompanying drawings, which are incorporated herein and form part of the specification, illustrate the disclosure and, together with the description, further serve to explain the principles of the disclosure and enable a person of skill in the relevant art(s) to make and use the disclosure.
The disclosure is described with reference to the accompanying drawings. In the drawings, generally, like reference numbers indicate identical or functionally similar elements. Additionally, generally, the left-most digit(s) of a reference number identifies the drawing in which the reference number first appears.
The disclosure is described with reference to the accompanying drawings. In the drawings, generally, like reference numbers indicate identical or functionally similar elements. Additionally, generally, the left-most digit(s) of a reference number identifies the drawing in which the reference number first appears.
Exemplary Network Socket Technologies
As shown in
As a brief aside, user space is a portion of system memory that a processor executes user processes from. User space is relatively freely and dynamically allocated for application software and a few device drivers. The kernel space is a portion of memory that a processor executes the kernel from. Kernel space is strictly reserved (usually during the processor boot sequence) for running privileged operating system (O/S) processes, extensions, and most device drivers. For example, each user space process normally runs in a specific memory space (its own “sandbox”) and cannot access the memory of other processes unless explicitly allowed. In contrast, the kernel is the core of a computer's operating system; the kernel can exert complete control over all other processes in the system.
The term “operating system” may refer without limitation to software that controls and manages access to hardware. An O/S commonly supports processing functions such as e.g., task scheduling, application execution, input and output management, memory management, security, and peripheral access. As used herein, the term “application” refers to software that can interact with the hardware only via procedures and interfaces offered by the O/S.
The term “privilege” may refer without limitation to any access restriction or permission which restricts or permits processor execution. System privileges are commonly used within the computing arts to, inter alia, mitigate the potential damage of a computer security vulnerability. For instance, a properly privileged computer system can prevent malicious software applications from affecting data and task execution associated with other applications and the kernel.
As used herein, the term “in-kernel” and/or “kernel space” may refer without limitation to data and/or processes that are stored in, and/or have privilege to access the kernel space memory allocations. In contrast, the terms “non-kernel” and/or “user space” refers to data and/or processes that are not privileged to access the kernel space memory allocations. In particular, user space represents the address space specific to the user process, whereas non-kernel space represents address space which is not in-kernel, but which may or may not be specific to user processes.
As previously noted, the illustrated socket 102 provides access to Transmission Control Protocol (TCP) 104, User Datagram Protocol (UDP) 106, and Inter-Processor Communication (IPC) 108. TCP, UDP, and IPC are various suites of transmission protocols each offering different capabilities and/or functionalities. For example, UDP is a minimal message-oriented encapsulation protocol that provides no guarantees to the upper layer protocol for message delivery and the UDP layer retains no state of UDP messages once sent. UDP is commonly used for real-time, interactive applications (e.g., video chat, voice over IP (VoIP)) where loss of packets is acceptable. In contrast, TCP provides reliable, ordered, and error-checked delivery of data via a retransmission and acknowledgement scheme; TCP is generally used for file transfers where packet loss is unacceptable, and transmission latency is flexible.
As used herein, the term “encapsulation protocol” may refer without limitation to modular communication protocols in which logically separate functions in the network are abstracted from their underlying structures by inclusion or information hiding within higher level objects. For example, in one exemplary embodiment, UDP provides extra information (ports numbering).
As used herein, the term “transport protocol” may refer without limitation to communication protocols that transport data between logical endpoints. A transport protocol may include encapsulation protocol functionality.
Both TCP and UDP are commonly layered over an Internet Protocol (IP) 110 for transmission. IP is a connectionless protocol for use on packet-switched networks that provides a “best effort delivery”. Best effort delivery does not guarantee delivery, nor does it assure proper sequencing or avoidance of duplicate delivery. Generally, these aspects are addressed by TCP or another transport protocol based on UDP.
As a brief aside, consider a web browser that opens a webpage; the web browser application would generally open a number of network sockets to download and/or interact with the various digital assets of the webpage (e.g., for a relatively common place webpage, this could entail instantiating ˜300 sockets). The web browser can write (or read) data to the socket; thereafter, the socket object executes system calls within kernel space to copy (or fetch) data to data structures in the kernel space.
As used herein, the term “domain” may refer without limitation to a self-contained memory allocation e.g., user space, driver space, kernel space, etc. A “domain crossing” may refer without limitation to a transaction, event, or process that “crosses” from one domain to another domain. For example, writing to a network socket from the user space to the kernel space constitutes a domain crossing access.
In the context of a Berkeley Software Distribution (BSD) based networking implementation, data that is transacted within the kernel space is stored in memory buffers that are also commonly referred to as “mbufs”. Each mbuf is a fixed size memory buffer that is used generically for transfers (mbufs are used regardless of the calling process e.g., TCP, UDP, etc.). Arbitrarily sized data can be split into multiple mbufs and retrieved one at a time or (depending on system support) retrieved using “scatter-gather” direct memory access (DMA) (“scatter-gather” refers to the process of gathering data from, or scattering data into, a given set of buffers). Each mbuf transfer is parameterized by a single identified mbuf.
Notably, each socket transfer can create multiple mbuf transfers, where each mbuf transfer copies (or fetches) data from a single mbuf at a time. As a further complication, because the socket spans both: (i) user space (limited privileges) and (ii) kernel space (privileged without limitation), the socket transfer verifies that each mbuf copy into/out of kernel space is valid. More directly, the verification process ensures that the data access is not malicious, corrupted, and/or malformed (i.e., that the transfer is appropriately sized and is to/from an appropriate area)
The processing overhead associated with domain crossing is a non-trivial processing cost. Processing cost affects user experience both directly and indirectly. A processor has a fixed amount of processing cycles every second; thus cycles that are used for transfer verification detract from more user perceptible tasks (e.g., rendering a video or audio stream). Additionally, processor activity consumes power; thus, increases in processing overhead increases power consumption.
Referring back to
Examples of sockets and/or extensions include without limitation: route (IP route handling), ndrv (packet 802.1X handling), key (key management), unix (translations for Unix systems), kernel control, kernel events, parental controls, intrusion detection, content filtering, hypervisors, and/or any number of other kernel tasking. Kernel extensions and public APIs enable, for example, third party software developers to develop a wide variety of applications that can interact with a computer system at even the lowest layers of abstraction. For example, kernel extensions can enable socket level filtering, IP level filtering, and even device interface filtering. In the current consumer applications space, many emerging technologies now rely on closely coupled interfaces to the hardware and kernel functionality. For example, many security applications “sniff” network traffic to detect malicious traffic or filter undesirable content; this requires access to other application sandboxes (a level of privilege that is normally reserved for the kernel).
Unfortunately, third party kernel extensions can be dangerous and/or undesirable. As previously noted, software applications are restricted for security and stability reasons; however the kernel is largely unrestricted. A third party kernel extension can introduce instability issues because the third party kernel extensions run in the same address space as the kernel itself (which is outside the purview of exemplary memory read/write protections based on memory allocations). Illegal memory accesses can result in segmentation faults and memory corruptions. Furthermore, unsecure kernel extension can create security vulnerabilities that can be exploited by malware. Additionally, even where correctly used, a kernel extension can expose a user's data to the third party software developer. This heightened level of access may raise privacy concerns (e.g., the third party developer may have access to browsing habits, etc.).
Exemplary Performance Optimization Technologies
During normal operation, the computer system can logically segment its tasks to optimize overall system operation. In particular, a processor can execute a task, and then “context switch” to another task, thereby ensuring that any single process thread does not monopolize processor resources from start to finish. More directly, a context switch is the process of storing the state of a process, or of a thread, so that it can be restored and execution resumed from the same point later. This allows multiple processes to share a single processor. However, excessive amounts of context switching can slow processor performance down. Notably, while the present discussion is primarily discussed within the context of a single processor for ease of understanding, multi-processor systems have analogous concepts (e.g., multiple processors also perform context switching, although contexts may not necessarily be resumed by the same processor).
For example, consider the following example of a packet reception. Packets arrive at the device driver 208A. The hardware managed by the device driver 208A may notify the processor via e.g., a doorbell signal (e.g., an interrupt). The device driver 208A work loop thread handles the hardware interrupt/doorbell, then signals the DLIL thread (Loop 1210). The processor services the device driver 208A with high priority, thereby ensuring that the device driver 208A operation is not bottlenecked (e.g., that the data does not overflow the device driver's memory and/or that the device driver does not stall). Once the data has been moved out of the device driver, the processor can context switch to other tasks.
At a later point, the processor can pick up the DLIL 206 execution process again. The processor determines which socket the packets should be routed to (e.g., socket 204A) and routes the packet data appropriately (Loop 2212). During this loop, the DLIL thread takes each packet, and moves each one sequentially into the socket memory space. Again, the processor can context switch to other tasks so as to ensure that the DLIL task does not block other concurrently executed processing. Subsequently thereafter, when the socket has the complete packet data transfer the processor can wake the user space application and deliver the packet into user space memory (Loop 3214). Generally, user space applications are treated at lower priority than kernel tasks; this can be reflected by larger time intervals between suspension and resumption. While the foregoing discussion is presented in the context of packet reception, artisans of ordinary skill in the related arts will readily appreciate, given the contents of the present disclosure, that the process is substantially reversed for packet transmission.
As demonstrated in the foregoing example, context switching ensures that tasks of different processing priority are allocated commensurate amounts of processing time. For example, a processor can spend significantly more time executing tasks of relatively high priority, and service lower priority tasks on an as-needed basis. As a brief aside, human perception is much more forgiving than hardware operation. Consequently, kernel tasks are generally performed at a much higher priority than user space applications. The difference in priority between kernel and user space allows the kernel to handle immediate system management (e.g., hardware interrupts, and queue overflow) in a timely manner, with minimal noticeable impact to the user experience.
Moreover,
Unfortunately, changing tastes in consumer expectations cannot be effectively addressed with the one-size-fits-all model and the conservative in-kernel exemplary networking stack. Artisans of ordinary skill in the related arts will readily appreciate, given the contents of the present disclosure, that different device platforms have different capabilities; for example, a desktop processor has significantly more processing and memory capability than a mobile phone processor. More directly, the “one-size-fits-all” solution does not account for the underlying platform capabilities and/or application requirements, and thus is not optimized for performance. Fine-tuning the exemplary networking stack for performance based on various “tailored” special cases results in an inordinate amount of software complexity which is untenable to support across the entire ecosystem of devices.
Exemplary Emerging Use Cases
As a brief aside, TLS is a record based protocol; in other words, TLS uses data records which are arbitrarily sized (e.g., up to 16 kilobytes). In contrast, TCP is a byte stream protocol (i.e., a byte has a fixed length of eight (8) bits). Consequently, the TCP layer subdivides TLS records into a sequentially ordered set of bytes for delivery. The receiver of the TCP byte stream reconstructs TLS records from the TCP byte stream by receiving each TCP packet, re-ordering the packets according to sequential numbering to recreate the byte stream and extracting the TLS record from the aggregated byte stream. Notably, every TCP packet of the sequence should be present before the TLS record can be reconstructed. Even though TCP can provide reliable delivery under lossy network conditions, there are a number of situations where TLS record delivery could fail. For example, under ideal conditions TCP isolates packet loss from its client (TLS in this example), and a single TCP packet loss should not result in failed TLS record delivery. However, the TLS layer or the application above may incorporate a timeout strategy in a manner that is unaware of the underlying TCP conditions. Thus, if there's significant packet loss in the network, the TLS timeout may be hit (and thus result in a failure to the application) even though TCP would normally provide reliable delivery.
Referring back to
Ideally, the TLS layer should set TLS record sizes based on network condition information. In particular, large TLS records can efficiently use network bandwidth, but require many successful TCP packet deliveries. In contrast, small TLS records incur significantly more network overhead, but can survive poor bandwidth conditions. Unfortunately, networking condition information is lower layer information that is available to the kernel space (e.g., the DLIL and device drivers), but generally restricted from user space applications. Some third party application developers and device manufacturers have incorporated kernel extensions (or similar operating system capabilities) to provide network condition information to the TLS user space applications; however, kernel extensions are undesirable due to the aforementioned security and privacy concerns. Alternately, some third party applications infer the presence of lossy network conditions based on historic TLS record loss. Such inferences are an indirect measure and significantly less accurate and lag behind real-time information (i.e., previous packet loss often does not predict future packet loss).
As illustrated within
It is well understood within the networking arts that different application types are associated with different capabilities and requirements. One such example is real time applications 502, commonly used for example, streaming audio/visual and/or other “live” data. Real time data has significant latency and/or throughput restrictions; moreover, certain real time applications may not require (and/or support) retransmission for reliable delivery of lost or corrupted data. Instead, real time applications may lower bandwidth requirements to compensate for poor transmission quality (resulting in lower quality, but timely, delivered data).
Another such example is interactive applications 504, commonly used for example, human input/output. Interactive data should be delivered at latencies that are below the human perceptible threshold (within several milliseconds) to ensure that the human experience is relatively seamless. This latency interval may be long enough for a retransmission, depending on the underlying physical technology. Additionally, human perception can be more or less tolerant of certain types of data corruptions; for example, audio delays below 20 ms are generally imperceptible, whereas audio corruptions (pops and clicks) are noticeable. Consequently, some interactive applications may allow for some level of error correction and/or adopt less aggressive bandwidth management mechanisms depending on the acceptable performance requirements for human perception.
In contrast to real time applications and interactive applications, file transfer applications 506 require perfect data fidelity without latency restrictions. To these ends, most file transfer technologies support retransmission of lost or corrupted data, and retransmission can have relatively long attempt intervals (e.g., on the order of multiple seconds to a minute). Similarly, within the communication arts, different communication technologies are associated with different capabilities and requirements. For example, Wi-Fi 516 (wireless local area networking based on IEEE 802.11) is heavily based on contention based access and is best suited for high bandwidth deliveries with reasonable latency. Wi-Fi is commonly used for file transfer type applications. Bluetooth 518 (personal area networking) is commonly used for low data rate and low latency applications. Bluetooth is commonly used for human interface devices (e.g., headphones, keyboards, and mice). Cellular network technologies 520 often provide non-contention-based access (e.g., dedicated user access) and can be used over varying geographic ranges. Cellular voice or video delivery is a good example of streaming data applications. Artisans of ordinary skill in the related arts will readily recognize that the foregoing examples are purely illustrative, and that different communication technologies are often used to support a variety of different types of application data. For example, Wi-Fi 516 can support file transfer, real time data transmission and/or interactive data with equivalent success.
Referring back to
Unfortunately, each of the applications has different latency, throughput and processing utilization requirements. Since, each of the network interfaces is sending and receiving data at different times, in different amounts, and with different levels of priority. From a purely logistical standpoint, the kernel is constantly juggling between high priority kernel threads (to ensure that the high priority hardware activities do not stall out) while still servicing each of its concurrently running applications to attempt to provide acceptable levels of service. In some cases, however, the kernel is bottlenecked by the processor's capabilities. Under such situations, some threads can be deprioritized; currently, the exemplary networking stack architecture is unable it clearly identify which threads can be deprioritized while still providing acceptable user service. For example, consider an “expected use” device of
Unfortunately, the addition of an unexpected amount of additional secondary interactive applications 504 (e.g., remote control interface, headphones, and/or other interface devices) and/or background file transfer applications can easily overwhelm the processor. Specifically, the primary real time application does not get enough CPU cycles to run within its time budget, because the kernel threads handling networking are selected at a higher priority. In other words, the user space application is not able to depress the priority of kernel networking threads (which are servicing both the primary and secondary processes). This can result in significantly worse user experience when the video rendering stalls out (video frame misses or video frame drops); whereas simply slowing down a file transfer or degrading the interaction interface may have been preferable.
Prior art solutions have tailored software for specific device implementations (e.g., the Apple TV®). For example, the device can be specifically programmed for an expected use. However, tailored solutions are becoming increasingly common and by extension the exceptions have swallowed the more generic use case. Moreover, tailored solutions are undesirable from multiple software maintenance standpoints. Devices have limited productive lifetimes, and software upkeep is non-trivial. Ideally, a per-application or per-profile workload optimization would enable a single processor (or multiple processors) to intelligently determine when and/or how too intelligently context switch and/or prioritize its application load (e.g., in the example of
Exemplary User Space Networking Architecture
A networking stack architecture and technology that caters to the needs of non-kernel-based networking use cases is disclosed herein. Unlike prior art monolithic networking stacks, the exemplary networking stack architecture described hereinafter includes various components that span multiple domains (both in-kernel, and non-kernel), with varying transport compositions, workload characteristics and parameters. The user space networking stack architecture provides an efficient infrastructure to transfer data across domains (user space, non-kernel, and kernel). Unlike the exemplary networking paradigm that hides the underlying networking tasks within the kernel and substantially limits control thereof by any non-kernel applications, the various embodiments described herein enable faster and more efficient cross domain data transfers.
Various embodiments of the present disclosure provide a faster and more efficient packet input/output (I/O) infrastructure than prior art techniques. Specifically, unlike exemplary networking stacks that use a “socket” based communication, disclosed embodiments can transfer data directly between the kernel and user space domains. Direct transfer reduces the per-byte and per-packet costs relative to socket-based communication. Additionally, direct transfer can improve observability and accountability with traffic monitoring.
As shown, a user space application 602 can initiate a network connection by instancing user space protocol stacks 604. Each user space protocol stacks includes network extensions for example, TCP/UDP/QUIC/IP, cryptography, framing, multiplexing, tunneling, and/or any number of other networking stack functionalities. Each user space protocol stack 604 communicates with one or more nexuses 608 via a channel input/output (I/O) 606. Each nexus 608 manages access to the network drivers 610. Additionally, shown is legacy application 612 support via the exemplary network socket technologies 614. While the illustrated embodiment shows nexus connections to both user space and in-kernel networking stacks, it is appreciated that the nexus may also enable e.g., non-kernel networking stacks (such as may be used by a daemon or other non-kernel, non-user process).
The following topical sections hereinafter describe the salient features of the various logical constructs in greater detail.
Exemplary User Space I/O Infrastructure
In one embodiment, the non-kernel networking stack provides a direct channel input output (I/O) 606. In one such implementation, the channel I/O 606 is included as part of the user space protocol stack 604. More directly, the channel I/O 606 enables the delivery of packets as a raw data I/O into kernel space with a single validation (e.g., only when the user stack provides the data to the one or more nexuses 608). The data can be directly accessed and/or manipulated in situ, the data need not be copied to an intermediary buffer.
In one exemplary implementation, a channel is an I/O scheme leveraging kernel managed shared memory. During an access, the channel I/O is presented to the process (e.g., the user process or kernel process) as a file descriptor-based object, rather than as data. In order to access the data, the process de-references the file descriptor for direct access to the shared memory within kernel space. In one such implementation, the file descriptor-based object based I/O is compatible with exemplary operating system signaling and “eventing” (event notification/response) mechanisms. In one exemplary variant, the channel I/O is based on Inter Process Communication (IPC) packets.
As used herein, the term “descriptor” may refer without limitation to data structures that indicate how other data is stored. Descriptors generally include multiple parameters and can be used to identify more complex data structures; for example, a descriptor may include one or more of type, size, address, tag, flag, headers, footers, metadata, structural links to other data descriptors or locations, and/or any other number of format or construction information.
Within the context of the present disclosure, as used herein, the term “pointer” may refer without limitation to a specific reference data type that “points” or “references” a location of data in memory. Typically, a pointer stores a memory address that is interpreted by a compiler as an absolute location in system memory or a relative location in system memory based on e.g., a base address, reference address, memory window, or other memory subset. During operation, a pointer is “de-referenced” to recover the data that is stored in the location of memory.
As used herein, the term “metadata” refers to data that describes data. Metadata varies widely in application, but generally falls into one of the descriptive, structural, and/or administrative categories. Descriptive metadata describes data in a manner to enable e.g., discovery and/or identification. Common examples include without limitation e.g., type, size, index tags, and keywords. Structural metadata describes the structure of the data e.g., how compound objects are put together. Common examples include without limitation e.g., prefix, postfix, table of contents, order, and/or any other information that describes the relationships and other characteristics of digital materials. Administrative metadata provides information to help manage a resource; common examples include e.g., authorship and creation information, access privileges, and/or error checking and security-based information (e.g., cyclic redundancy checks (CRC), parity, etc.).
In one embodiment, the channel I/O can be further leveraged to provide direct monitoring of its corresponding associated memory. More directly, unlike exemplary data transfers which are based on mbuf based divide/copy/move, etc., the channel I/O can provide (with appropriate viewing privileges) a direct window into the memory accesses of the system. Such implementations further simplify software development as debugging and/or traffic monitoring can be performed directly on traffic. Direct traffic monitoring can reduce errors attributed to false positives/false negatives caused by e.g., different software versioning, task scheduling, compiler settings, and/or other software introduced inaccuracies.
In one embodiment, the in-kernel network device drivers (e.g. Wi-Fi, Cellular, Ethernet) use simplified data movement models based on the aforementioned channel I/O scheme. More directly, the user space networking stacks can directly interface to each of the various different technology-based network drivers via channel I/O; in this manner, the user space networking stacks do not incur the exemplary data mbuf based divide/copy/move penalties. Additionally, user space applications can directly access user space networking components for immediate traffic handling and processing.
Exemplary Nexus
In one embodiment, the networking stack connects to one or more nexus 608. In one such implementation, the nexus 608 is a kernel space process that arbitrates access to system resources including, without limitation e.g., shared memory within kernel space, network drivers, and/or other kernel or user processes. In one such variant, the nexus 608 aggregates one or more channels 606 together for access to the network drivers 610 and/or shared kernel space memory.
In one exemplary implementation, a nexus is a kernel process that determines the format and/or parameters of the data flowing through its connected channels. In some variants, the nexus may further perform ingress and/or egress filtering.
The nexus may use the determined format and/or parameter information to facilitate one-to-one and one-to-many topologies. For example, the nexus can create user pipes for process-to-process channels; kernel-pipes for process-to-kernel channels; network interfaces for direct channel connection from a process to in-kernel network drivers, or legacy networking stack interfaces; and/or flow-switches for multiplexing flows across channels (e.g., switching a flow from one channel to one or more other channels).
Additionally, in some variants the nexus may provide the format, parameter, and/or ingress egress information to kernel processes and/or one or more appropriately privileged user space processes.
In one embodiment, the nexus 608 may additionally ensure that there is fairness and/or appropriately prioritize each of its connected stacks. For example, within the context of
In one such embodiment, in-kernel, non-kernel, and/or user space infrastructures ensure fairness and can reduce latency due to e.g., buffer bloat (across channels in a given nexus, as well as flows within a channel). In other words, the in-kernel and/or user space infrastructures can negotiate proper buffering sizes based on the expected amount of traffic and/or network capabilities for each flow. By buffering data according to traffic and/or network capability, buffers are not undersized or oversized.
As a brief aside, “buffer bloat” is commonly used to describe e.g., high latency caused by excessive buffering of packets. Specifically, buffer bloat may occur when excessively large buffers are used to support a real time streaming application. As a brief aside, TCP retransmission mechanism relies on measuring the occurrence of packet drops to determine the available bandwidth. Under certain congestion conditions, excessively large buffers can prevent the TCP feedback mechanism from correctly inferring the presence of a network congestion event in a timely manner (the buffered packets “hide” the congestion, since they are not dropped). Consequently, the buffers have to drain before TCP congestion control resets and the TCP connection can correct itself.
Referring back to
While the foregoing example is based on “fairness” standard, artisans of ordinary skill in the related arts will readily appreciate that other schemes may be substituted with equivalent success given the contents of the present disclosure. For example, some embodiments may dynamically or statically service the user application networking space with greater or less weight compared to the legacy socket-based access. For example, user application networking space may be more heavily weighted to improve overall performance or functionality, whereas legacy socket-based access may be preferred where legacy applications are preferentially supported.
Exemplary Network Extensions
In one embodiment of the present disclosure, a network extension is disclosed. A network extension is an agent-based extension that is tightly coupled to network control policies. The agent is executed by the kernel and exposes libraries of network control functionality to user space applications. During operation, user space software can access kernel space functionality through the context and privileges of the agent.
As used herein, the term “agent” may refer without limitation to a software agent that acts for a user space application or other program in a relationship of agency with appropriate privileges. The agency relationship between the agent and the user space application implies the authority to decide which, if any, action is appropriate given the user application and kernel privileges. A software agent is privileged to negotiate with the kernel and other software agents regarding without limitation e.g., scheduling, priority, collaboration, visibility, and/other sharing of user space and kernel space information. While the agent negotiates with the kernel on behalf of the application, the kernel ultimately decides on scheduling, priority, etc.
Various benefits and efficiencies can be gained through the use of network extensions. In particular, user space applications can control the protocol stack down to the resolution of exposed threads (i.e., the threads that are made available by the agent). In other words, software agents expose specific access to lower layer network functionality which was previously hidden or abstracted away from user space applications. For example, consider the previous examples of TLS record sizing (see e.g.,
Similarly, consider the previous examples of multi-threading within the context of expected use devices (see e.g.,
As a related benefit, since a software agent represents the application to the kernel; the agent can trust the kernel, but the kernel may or may not trust the agent. For example, a software agent can be used by the kernel to convey network congestion information in a trusted manner to the application; similarly, a software agent can be used by an application to request a higher network priority. Notably, since a software agent operates from user space, the agent's privilege is not promoted to kernel level permissions. In other words, the agent does not permit the user application to exceed its privileges (e.g., the agent cannot commandeer the network driver at the highest network priority or force a read/write to another application's memory space without the other kernel and/or other application's consent).
Networking extensions allow the user space application to execute networking communications functionality within the user space and interpose a network extension between the user space application and the kernel space. As a result, the number of cross domain accesses for complex layering of different protocol stacks can be greatly reduced. Limiting cross domain accesses prevents context switching and allows the user space to efficiently police its own priorities. For example, consider the previous example of a VPN session as was previously illustrated in
As used herein, the term “interposition” may refer without limitation to the insertion of an entity between two or more layers. For example, an agent is interposed between the application and the user space networking stack. Depending on the type of agent or network extension, the interposition can be explicit or implicit. Explicit interposition occurs where the application explicitly instances the agent or network extension. For example, the application may explicitly call a user space tunnel extension. In contrast, implicit interposition occurs where the application did not explicitly instance the agent or network extension. Common examples of implicit interposition occur where one user space application sniffs the traffic or filters the content of another user space application.
As used herein, an “instance” may refer without limitation to a single copy of a software program or other software object; “instancing” and “instantiations” refers to the creation of the instance. Multiple instances of a program can be created; e.g., copied into memory several times. Software object instances are instantiations of a class; for example, a first software agent and second software instance are each distinct instances of the software agent class.
Exemplary User Space Networking Stack
Referring now to
In one exemplary embodiment, the user space networking stack 700 is instantiated within an application user space 718. More directly, the user space networking stack 700 is treated identically to any one of multiple threads 710 within the application user space 718. Each of the coexisting threads 720 has access to the various functions and libraries offered by the user space networking stack via a direct function call.
As a brief aside, each of the threads 720 reside within the same address space. By virtue of their shared addressability, each of the threads may grant or deny access to their portions of shared address space via existing user space memory management schemes and/or virtual machine type protections. Additionally, threads can freely transfer data structures from one to the other, without e.g., incurring cross domain penalties. For example, TCP data 710 can be freely passed to TLS 706 as a data structure within a user space function call.
As previously noted, the user space networking stack 700 may grant or deny access to other coexistent user space threads; e.g., a user space thread is restricted to the specific function calls and privileges made available via the application interface 702. Furthermore, the user space networking stack 700 is further restricted to interfacing the operating system via the specific kernel function calls and privileges made available via the operating system interface 704. In this manner, both the threads and the user space networking stack have access and visibility into the kernel space, without compromising the kernel's security and stability.
One significant benefit of the user space networking stack 700 is that networking function calls can be made without acquiring various locks that are present in the inkernel networking stack. As previously noted, the “locking” mechanism is used by the kernel to enforce access limits on multiple threads from multiple different user space applications; however in the user space, access to shared resources are handled within the context of only one user application space at a time, consequently access to shared resources are inherently handled by the single threading nature of user space execution. More directly, only one thread can access the user space networking stack 700 at a time; consequently, kernel locking is entirely obviated by the user space networking stack.
Another benefit of user space network stack operation is cross platform compatibility. For example, certain types of applications (e.g., iTunes®, Apple Music® developed by the Assignee hereof) are deployed over a variety of different operating systems. Similarly, some emerging transport protocols (e.g. QUIC) are ideally served by portable and common software between the client and server endpoints. Consistency in the user space software implementation allows for better and more consistent user experience, improves statistical data gathering and analysis, and provides a foundation for enhancing, experimenting and developing network technologies used across such services. In other words, a consistent user space networking stack can be deployed over any operating system platform without regard for the native operating system stack (e.g., which may vary widely).
Another important advantage of the exemplary user space networking stack is the flexibility to extend and improve the core protocol functionalities, and thus deliver specialized stacks based on the application's requirements. For example, a video conferencing application (e.g., FaceTime® developed by the Assignee hereof) may benefit from a networking stack catered to optimize performance for real-time voice and video-streaming traffics (e.g., by allocating more CPU cycles for video rendering, or conversely deprioritizing unimportant ancillary tasks). In one such variant, a specialized stack can be deployed entirely within the user space application, without specialized kernel extensions or changes to the kernel. In this manner, the specialized user space networking stack can be isolated from networking stacks. This is important both from a reliability standpoint (e.g., updated software doesn't affect other software), as well as to minimize debugging and reduce development and test cycle times.
Furthermore, having the network transport layer (e.g. TCP, QUIC) reside in user space can open up many possibilities for improving performance. For example, as previously alluded to, applications (such as TLS) can be modified depending on the underlying network connections. User space applications can be collapsed or tightly integrated into network transports. In some variants, data structure sizes can be adjusted based on immediate lower layer network condition information (e.g., to accommodate or compensate for poor network conditions). Similarly, overly conservative or under conservative transport mechanisms can be avoided (e.g., too much or not enough buffering previously present at the socket layer). Furthermore, unnecessary data copies and/or transforms can be eliminated and protocol signaling (congestion, error, etc.) can be delivered more efficiently.
In yet another embodiment, the exemplary user space networking stack further provides a framework for both networking clients and networking providers. In one such variant, the networking client framework allows the client to interoperate with any network provider (including the legacy BSD stack). In one such variant, the network provider framework provides consistent methods of discovery, connection, and data transfer to networking clients. By providing consistent frameworks for clients and providers which operate seamlessly over a range of different technologies (such as a VPN, Bluetooth, Wi-Fi, cellular, etc.), the client software can be greatly simplified while retaining compatibility with many different technologies.
Asymmetric Memory Usage and Security Considerations for Device Drivers
Certain aspects of device driver operation require special access; for example, device drivers often require direct read/write access to physical memory locations (as opposed to virtualized memory allocations). As but another example, device drivers may have latency and/or throughput requirements that are more stringent than user space processes. Historically, third party device drivers have been executed from kernel space consistent with heightened privileges and/or device access; however, this arrangement is dangerous.
As a brief aside, in order to facilitate integration, third party vendors often provide ready-to-use device drivers and/or firmware. Unfortunately, in some situations, vendors develop and release features without full verification. In other situations, the components and/or driver software may be used in a manner inconsistent with the vendor's intended use case and/or design assumptions. Malicious actors have learned to exploit and/or leverage third party device driver vulnerabilities in consumer electronics. Specifically, the aforementioned instability and/or vulnerability of third party drivers can be easily attacked; once compromised, the malicious actor has full access to the kernel via the third party driver's kernel access.
Kernel vulnerability can be reduced by ensuring that all non-kernel processes are isolated from kernel space.
The exemplary networking architecture of
As illustrated in
In one embodiment, the driver library application programming interface (API) is parameterized so as to support a broad spectrum of technologies. For example, the device driver library exposes shared memory space, for example, a packet pool 904A, a submission queue 904B, and a completion queue 904C. The memory spaces are allocated from a shared memory space based on the instantiating driver's requirements. More generally, artisans of ordinary skill in the related arts will readily appreciate that most device drivers are heavily optimized for their technology specific operation. Each technology may require different timing, buffering, and/or operation from other technologies. As a practical matter, these differences may be reflected in ring segment sizes, the number of memory segments per ring, etc. For example, larger memory rings may enable higher throughput at higher latency, while smaller memory rings may provide lower throughput at lower latency, etc.
During data transfer operations, the network interface writes data packets into a shared packet pool 904A. Pointers and/or indexes (or other referential data structures) to the packets are queued into the submission queue 904B. The device driver 903 de-references the pointers from the submission queue 904B and reads the data packets from the shared pool 904A. The data packets are delivered to the device 902. Subsequently thereafter, the driver 903 writes completion status into the completion ring 904C. The completed packets are returned to the network interface 906.
The foregoing example is presented in the context of the flow switch 908 providing packets to the device 902 (uplink), however the reverse direction (downlink) uses an analogous delivery mechanism. Specifically, the network interface allocates data packets for a read into a shared packet pool 904A. The driver 903 de-references the pointers from the submission queue 904B and writes into the allocated data packets. Subsequently thereafter, the driver 903 writes completion status into the completion ring 904C. The completed packets are returned to the network interface 906 for reading.
A graphical representation of the shared packet pool 904A is illustrated. Notably, the exemplary kernel space objects are sized to 2 KB which corresponds to the maximum transmission unit size for the de facto standard Ethernet packet (1500 bytes) and its associated metadata. Under the memory allocation scheme of
As a brief aside, executing device drivers in non-kernel space is both more secure and may provide opportunities for more efficient resource utilization. However, non-kernel space memory allocations are “virtualized” from physical memory.
Virtualization allows the kernel space to manage its physical memory resources, while providing transparent and seamless memory mappings for non-kernel applications. In other words, the kernel can allocate, de-allocate, and/or suspend memory allocations as needed; the non-kernel space application (user application, device driver, etc.) is unaware of the physical memory it is residing in. In many cases, virtualization is necessary to maximize overall device performance, as well as to prevent unauthorized access (security and robust software design). Unfortunately, device drivers often are tightly coupled to physical memory resource usage; thus, device drivers may need e.g., physical memory access, contiguous memory allocations, and/or other memory access privileges, etc.
While non-kernel space networking stacks already provide substantial improvements over kernel space networking stacks for generic networking, various embodiments of the present disclosure may further improve network performance for certain types of device drivers and/or applications. As but one such example, some networking technologies are asymmetric in the amount of data that is transmitted and received. Asymmetry may result in substantial differences in transmit and receive complexity, as well as different packet processing optimizations. For example, certain cellular technologies (e.g., 4G, 5G) rely on OFDMA (Orthogonal Frequency Division Multiple Access) to maximize downlink bandwidth, but SC-FDMA (Single Carrier Frequency Division Multiple Access) to reduce uplink interference between user equipment.
As a brief aside, polylithic networking for consumer electronics tends to be asymmetrically distributed across multiple stacks. For example, a user consuming video may be downloading large amounts of data for just a single network stack. However, multiple other background services may be providing periodic upstream traffic (e.g., location updates, keep alive signaling, text media, etc.) Ideally, in such scenarios, most of the received traffic can be batched and routed to its corresponding endpoint application, whereas upstream traffic may be generated by multiple different stacks and sent a packet at a time. In other words, the large volume of downlink packet processing may benefit from packet aggregation (batch processing), whereas uplink packet processing may prefer to process packets on an individual basis.
Additionally, while non-kernel device driver operation is more stable than kernel space device driver operation, compromised device drivers may still consume system resources in an undesirable manner. For example, a compromised third party device driver could overwrite receive or transmit data; this can result in excessive retransmissions, wasted network bandwidth, wasted device resources (processing, memory, bandwidth), etc.
Still further, shared packet pool configurations have a finite number of resources (e.g., packet objects). In the aforementioned implementation, packet objects from the shared set of resources are allocated based on the submission queue, and freed based on the completion queue. For highly asymmetric traffic, reception can starve transmission and vice versa; e.g., transmit data cannot be packetized when all the packet objects are allocated to received traffic (transmission should be delayed until received packets are completed).
Split Receive Transmit Memory Allocations
Unlike the aforementioned shared memory interface for non-kernel space drivers (described in
Referring now to
As a brief aside,
As used herein, the terms “clone”, “cloned”, “cloning” (and related linguistic variants) refer to a discrete memory allocation for processing in a first domain (e.g., kernel space) that contains multiple similar data structures that are configured for the same control and/or data path endpoint processing in a second domain (e.g., non-kernel). For example, a driver application may request (or be granted) one or more discrete 32 KB objects that store up to sixteen 2 KB packets; the kernel can process the 32 KB object in aggregate using the cloned packet metadata. However, once delivered to an endpoint (e.g., an endpoint user application or the device driver) the object can be parsed for its constituent packets. Cloned packets can be directly manipulated by the endpoint/driver (independent of kernel space memory management) and routed/transported in aggregate by the intermediary kernel space entities. The packet cloning optimizations described herein provide multiple benefits over non-cloned operation. For example, non-kernel space networking architectures can greatly improve performance by batching similar traffic together thereby reducing per-packet costs (e.g., ACK/NACK, retransmission, etc.) and/or per-byte costs (copy, fragmentation, defragmentation, checksum, etc.)
In one embodiment, the endpoint specific subdivisions are stored in metadata 1310 that identifies the “span” of the subdivision. For example, in the illustrated implementation, a device driver that is allocated a 32 KB object 1308 may subdivide the buffer into three spans of 9 KB (also “Jumbo” ethernet frames) and an unused space (as shown) for a first usage, but re-divide the 32 KB object 1308 into sixteen spans of 2 KB for default use. In other words, the device driver may freely modify spans independent of kernel space memory management.
Notably, since spans may be used for specific (non-generic) data transfers between the endpoint and/or the device driver, spans may widely vary based on user space negotiated parameters. In other words, the device driver can adjust its span selection according to user space networking stack considerations and/or other cross-layer considerations. For example, spans may be symmetric/uniform or asymmetric (e.g., vary in size, access (R/W), etc.) Spans may be statically set, dynamically adjusted, or some variant thereof. As but one such example, a device driver may allocate a fixed number of spans based on its own considerations; alternatively, the device driver may flexibly allocate spans based on an as-needed-basis, based on its served endpoint requirements. Still other variants may consider any number of driver, client, kernel, and/or network considerations.
In some variants, the kernel may additionally provide supplemental information and/or kernel support via degenerate or redundant data structures. In one such implementation, the degenerate data structure may be a “packet” pointer that points to the object (instead of its packet). As but one such example, degenerate pointers may be used by the kernel space to reference the same object for multiple data packets. The kernel space entity can use the degenerate pointers to e.g., provide kernel space updates that correspond to the endpoint packets without de-referencing or otherwise manipulating the packets of the object. Kernel space updates may be stored in metadata for the object and handled by the endpoint non-kernel space application when necessary (thereby avoiding per-packet kernel processing). While the foregoing example is presented in the context of a degenerate pointer (a packet pointer that does not point to its packet), any data structure that lacks a key characteristic of its type may be substituted with equal success by artisans of ordinary skill in the related arts, given the contents of the present disclosure. Examples of such data structures include referential data structures that do not reference a data structure, value data structures that are nulled, etc.
Referring back to
Similarly, in the transmit direction, the network interface 1206 writes packets into packet objects of the transmit packet pool 1204TX. Notably, each packet is its own kernel space object (e.g., packets may originate from different stacks of the polylithic networking architecture). At transmission events, the device driver reads packet objects from the transmit packet pool 1204TX based on the submission queue. Successfully transmitted packets are completed and returned to the transmit packet pool 1204TX.
More generally, splitting the receive and transmit packet pools in accordance with the various principles described herein may be particularly useful where kernel treatment of the packets is different. For example, kernel treatment of the receive packet pool can be based on buffer cloning and substantially larger kernel space objects (32 KB) that enable packet aggregation and routing on a per-flow basis whereas the transmit packet pool does not support cloning, uses a smaller kernel object granularity (2 KB), and routes packets on a per-packet basis. Additionally, splitting packet pool allocations between transmit and receive ensures that receive data does not starve transmit data or vice versa. Each data pipe has its own set of resources which are separately allocated and/or freed.
While the foregoing is presented in the context of transmit and receive operation, artisans of ordinary skill in the related arts will readily appreciate that any distinct hardware functionality may be implemented with distinct packet pools. Such functionality may differentiate resources based on different priorities, protocols, capabilities, and/or optimizations. For example, bulk cellular data may be allocated a set of pools (transmit and/or receive) and messaging service (e.g., SMS) data may be allocated a separate set of pools. Similarly, TCP and UDP traffic may be transacted across different pools. Other examples capabilities and/or optimizations may include e.g., packet aggregation, just in time transformation, and or other processing optimizations.
As a related benefit, certain variants may monitor device driver operation to ensure that the driver complies with its intended behavior. Notably, unlike exemplary systems that implement drivers as kernel space entities (which bypasses memory management and usage restrictions checks), the exemplary non-kernel space drivers described herein can be monitored with user space/non-kernel space memory usage mechanisms. For example, a receive packet pool should only be written to by the device driver and read from by the network interface; unsanctioned transfers (e.g., a device driver that reads from the receive packet pool, etc.) may be flagged and/or disabled using the memory management unit (MMU). Preventing unsanctioned memory accesses greatly improves overall system security and stability.
Split packet pool operation provides a plethora of advantages that improve the functioning of a computer process. Notably, the exemplary split packet pool scheme described herein provides unconventional technical solutions for configuring memory allocations based on differences in receive and transmit hardware implementations. Separating transmit and receive operation may enable substantial improvements in device performance that were not heretofore possible within the monolithic networking stack and global resource processing paradigm (i.e., where all resources are uniform). In one specific example, the exemplary split packet pool scheme described herein enables different memory treatments for asymmetric networking technologies (e.g., OFDMA downlink, SC-FDMA uplink). In another such example, the exemplary split packet pool scheme described herein may provide for more robust and secure integration of third party components. More generally, the various principles described herein address specific privilege, prioritization, and/or utilization issues that are specific to polylithic networking architectures; these are unique and distinct from well-understood, routine, and/or conventional solutions implemented within monolithic networking architectures.
At operation 1402, the operational control flow 1400 writes data packets into a shared packet pool. In some embodiments, a network interface, such as the flow switch 806 as described above in
At operation 1404, the operational control flow 1400 queues pointers, or other referential data structures, to the data packets into a submission queue. In some embodiments, the network interface in the kernel space can queues the pointers, or the other referential data structures, to the data packets into a submission queue.
At operation 1406, the operational control flow 1400 de-references the pointers, or the other referential data structures, from the submission queue. In some embodiments, a device driver, such as the device driver 810 as described above in
At operation 1408, the operational control flow 1400 reads data packets from the shared packet pool. In some embodiments, the device driver in the non-kernel space can read the data packets from the shared packet pool. In some embodiments, the operational control flow 1400 reads the data packets into the transmit packet pool from operation 1402.
At operation 1410, the operational control flow 1400 writes completion status into a completion queue. In some embodiments, the device driver in the non-kernel space can write the completion status into the completion queue. In some embodiments, the data packets can be returned to the network interface.
At operation 1452, the operational control flow 1450 allocates data packets within a shared packet pool. In some embodiments, a network interface, such as the flow switch 806 as described above in
At operation 1454, the operational control flow 1450 queues pointers, or other referential data structures, to the data packets into a submission queue. In some embodiments, the network interface in the kernel space can queues the pointers, or the other referential data structures, to the data packets into a submission queue.
At operation 1456, the operational control flow 1450 de-references the pointers, or the other referential data structures, from the submission queue. In some embodiments, a device driver, such as the device driver 810 as described above in
At operation 1458, the operational control flow 1450 writes the data packets into the allocated data packets. In some embodiments, the device driver in the non-kernel space can write the data packets from into the allocated data packets. In some embodiments, the operational control flow 1450 writes into the allocated data packets of the receive packet pool from operation 1452.
At operation 1460, the operational control flow 1450 writes completion status into a completion queue. In some embodiments, the device driver in the non-kernel space can write the completion status into the completion queue. In some embodiments, the data packets can be returned to the network interface.
It is to be appreciated that the Detailed Description section, and not the Summary and Abstract sections, is intended to be used to interpret the claims. The Summary and Abstract sections may set forth one or more but not all exemplary embodiments of the disclosure as contemplated by the inventor(s), and thus, are not intended to limit the disclosure and the appended claims in any way.
The disclosure has been described above with the aid of functional building blocks illustrating the implementation of specified functions and relationships thereof. The boundaries of these functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternate boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed.
The foregoing description of the specific embodiments will so fully reveal the general nature of the disclosure that others can, by applying knowledge within the skill of the art, readily modify and/or adapt for various applications such specific embodiments, without undue experimentation, without departing from the general concept of the disclosure. Therefore, such adaptations and modifications are intended to be within the meaning and range of equivalents of the disclosed embodiments, based on the teaching and guidance presented herein. It is to be understood that the phraseology or terminology herein is for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by the skilled artisan in light of the teachings and guidance.
It will be recognized the specific embodiments can be described in terms of a sequence of steps or operations, these descriptions are only illustrative of the broader steps or operations described herein, and may be modified as required by the particular application. Certain steps or operations may be rendered unnecessary or optional under certain circumstances. Additionally, certain steps or operations may be added to the disclosed embodiments, or the order of performance of two or more steps permuted. All such variations are considered to be encompassed within the disclosure herein.
The breadth and scope of the disclosure should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.
The present disclosure contemplates that the entities responsible for the collection, analysis, disclosure, transfer, storage, or other use of such personal information data will comply with well-established privacy policies and/or privacy practices. In particular, such entities should implement and consistently use privacy policies and practices that are generally recognized as meeting or exceeding industry or governmental requirements for maintaining personal information data private and secure. Such policies should be easily accessible by users, and should be updated as the collection and/or use of data changes. Personal information from users should be collected for legitimate and reasonable uses of the entity and not shared or sold outside of those legitimate uses. Further, such collection/sharing should only occur after receiving the informed consent of the users. Additionally, such entities should consider taking any needed steps for safeguarding and securing access to such personal information data and ensuring that others with access to the personal information data adhere to their privacy policies and procedures. Further, such entities can subject themselves to evaluation by third parties to certify their adherence to widely accepted privacy policies and practices. In addition, policies and practices should be adapted for the particular types of personal information data being collected and/or accessed and adapted to applicable laws and standards, including jurisdiction-specific considerations. For instance, in the United States, collection of, or access to, certain health data may be governed by federal and/or state laws, such as the Health Insurance Portability and Accountability Act (HIPAA); whereas health data in other countries may be subject to other regulations and policies and should be handled accordingly. Hence different privacy practices should be maintained for different personal data types in each country.
The present application claims the benefit of United States Provisional Patent Application No. 63/078,247, filed Sep. 14, 2020, which is incorporated herein by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
4805137 | Grant et al. | Feb 1989 | A |
4949299 | Pickett | Aug 1990 | A |
5367688 | Croll | Nov 1994 | A |
5467459 | Alexander et al. | Nov 1995 | A |
5485578 | Sweazey | Jan 1996 | A |
5506968 | Dukes | Apr 1996 | A |
5613086 | Frey et al. | Mar 1997 | A |
5659542 | Bell et al. | Aug 1997 | A |
5708779 | Graziano et al. | Jan 1998 | A |
5731973 | Takaishi et al. | Mar 1998 | A |
5850395 | Hauser et al. | Dec 1998 | A |
5903564 | Ganmukhi et al. | May 1999 | A |
5943507 | Cornish et al. | Aug 1999 | A |
6008992 | Kawakami | Dec 1999 | A |
6032179 | Osborne | Feb 2000 | A |
6216178 | Stracovsky et al. | Apr 2001 | B1 |
6233702 | Horst et al. | May 2001 | B1 |
6260152 | Cole et al. | Jul 2001 | B1 |
6349355 | Draves et al. | Feb 2002 | B1 |
6359863 | Varma et al. | Mar 2002 | B1 |
6411997 | Dawes et al. | Jun 2002 | B1 |
6485081 | Bingle et al. | Nov 2002 | B1 |
6523073 | Kammer et al. | Feb 2003 | B1 |
6553446 | Miller | Apr 2003 | B1 |
6693895 | Crummey et al. | Feb 2004 | B1 |
6815873 | Johnson et al. | Nov 2004 | B2 |
6874075 | Jerding et al. | Mar 2005 | B2 |
6948094 | Schultz et al. | Sep 2005 | B2 |
6973701 | Momoda et al. | Dec 2005 | B2 |
6990594 | Kim | Jan 2006 | B2 |
7013536 | Golden et al. | Mar 2006 | B2 |
7032282 | Powell et al. | Apr 2006 | B2 |
7100020 | Brightman et al. | Aug 2006 | B1 |
7111307 | Wang | Sep 2006 | B1 |
7127600 | Zimmer et al. | Oct 2006 | B2 |
7152231 | Galluscio et al. | Dec 2006 | B1 |
7281172 | Chujo | Oct 2007 | B2 |
7397774 | Holland et al. | Jul 2008 | B1 |
7398382 | Rothman et al. | Jul 2008 | B2 |
7403542 | Thompson | Jul 2008 | B1 |
7506084 | Moerti et al. | Mar 2009 | B2 |
7509391 | Chauvel et al. | Mar 2009 | B1 |
7587575 | Moertl et al. | Sep 2009 | B2 |
7590817 | Moertl et al. | Sep 2009 | B2 |
7617377 | Moertl et al. | Nov 2009 | B2 |
7681012 | Verma et al. | Mar 2010 | B2 |
7685476 | Andre et al. | Mar 2010 | B2 |
7802256 | Havens | Sep 2010 | B2 |
7853731 | Zeng | Dec 2010 | B1 |
7899941 | Hendry et al. | Mar 2011 | B2 |
7941682 | Adams | May 2011 | B2 |
8214707 | Munson et al. | Jul 2012 | B2 |
8230248 | Dance et al. | Jul 2012 | B2 |
8239947 | Glick et al. | Aug 2012 | B1 |
8255725 | Shimazaki et al. | Aug 2012 | B2 |
8271996 | Gould et al. | Sep 2012 | B1 |
8352624 | Zimmerman et al. | Jan 2013 | B2 |
8468285 | Kobayashi | Jun 2013 | B2 |
8555099 | Marinkovic et al. | Oct 2013 | B2 |
8561090 | Schneider | Oct 2013 | B2 |
8635412 | Wilshire | Jan 2014 | B1 |
8656228 | Check et al. | Feb 2014 | B2 |
8769168 | Moertl et al. | Jul 2014 | B2 |
8788822 | Riddle | Jul 2014 | B1 |
8799537 | Zhu et al. | Aug 2014 | B1 |
8806640 | Wang | Aug 2014 | B2 |
8819386 | Mather | Aug 2014 | B1 |
8848809 | Whitby-Strevens | Sep 2014 | B2 |
8855120 | Robbins | Oct 2014 | B2 |
8876062 | Baghdasarian | Nov 2014 | B1 |
9049179 | Luna | Jun 2015 | B2 |
9130864 | Keith | Sep 2015 | B2 |
9135059 | Ballard et al. | Sep 2015 | B2 |
9152580 | Chau et al. | Oct 2015 | B1 |
9170957 | Touzni et al. | Oct 2015 | B2 |
9280360 | Xu et al. | Mar 2016 | B2 |
9319090 | Whitby-Strevens | Apr 2016 | B2 |
9483305 | Shmidt et al. | Nov 2016 | B1 |
9544069 | Whitby-Strevens et al. | Jan 2017 | B2 |
9547535 | Wilt | Jan 2017 | B1 |
9594718 | Kaushik et al. | Mar 2017 | B2 |
9769756 | Cui et al. | Sep 2017 | B1 |
9830289 | Pulyala et al. | Nov 2017 | B2 |
9910475 | Kurts et al. | Mar 2018 | B2 |
9913305 | Pinheiro et al. | Mar 2018 | B2 |
9932757 | Hager | Apr 2018 | B2 |
9959124 | Herbeck et al. | May 2018 | B1 |
9985904 | Shalev et al. | May 2018 | B2 |
10078361 | Sanghi et al. | Sep 2018 | B2 |
10230608 | Tsirkin | Mar 2019 | B2 |
10289555 | Michaud et al. | May 2019 | B1 |
10331600 | Rajadnya et al. | Jun 2019 | B1 |
10331612 | Petkov et al. | Jun 2019 | B1 |
10534601 | Venkata et al. | Jan 2020 | B1 |
10552072 | Bono et al. | Feb 2020 | B1 |
10678432 | Dreier et al. | Jun 2020 | B1 |
10798059 | Singh et al. | Oct 2020 | B1 |
10798224 | Masputra et al. | Oct 2020 | B2 |
10819831 | Masputra et al. | Oct 2020 | B2 |
10877823 | Lawrence | Dec 2020 | B1 |
10999132 | Sagar et al. | May 2021 | B1 |
11095758 | Masputra et al. | Aug 2021 | B2 |
11146665 | Masputra et al. | Oct 2021 | B2 |
11159651 | Masputra et al. | Oct 2021 | B2 |
11178259 | Masputra et al. | Nov 2021 | B2 |
11178260 | Masputra et al. | Nov 2021 | B2 |
11212373 | Masputra et al. | Dec 2021 | B2 |
11368560 | Masputra et al. | Jun 2022 | B2 |
11477123 | Masputra et al. | Oct 2022 | B2 |
11558348 | Masputra et al. | Jan 2023 | B2 |
20010037410 | Gardner | Nov 2001 | A1 |
20020013868 | West | Jan 2002 | A1 |
20020044553 | Chakravorty | Apr 2002 | A1 |
20020053011 | Aiken et al. | May 2002 | A1 |
20020065867 | Chauvel | May 2002 | A1 |
20020169938 | Scott et al. | Nov 2002 | A1 |
20020195177 | Hinkley et al. | Dec 2002 | A1 |
20030014607 | Slavin et al. | Jan 2003 | A1 |
20030061395 | Kingsbury et al. | Mar 2003 | A1 |
20030120935 | Teal et al. | Jun 2003 | A1 |
20030200413 | Gurumoorthy et al. | Oct 2003 | A1 |
20040010473 | Hsu et al. | Jan 2004 | A1 |
20040010545 | Pandya | Jan 2004 | A1 |
20040044929 | Chujo | Mar 2004 | A1 |
20040105384 | Gallezot et al. | Jun 2004 | A1 |
20040128568 | O'Shea | Jul 2004 | A1 |
20040179546 | McDaniel et al. | Sep 2004 | A1 |
20040201749 | Malloy Desormeaux | Oct 2004 | A1 |
20040221056 | Kobayashi | Nov 2004 | A1 |
20040228365 | Kobayashi | Nov 2004 | A1 |
20040249957 | Ekis et al. | Dec 2004 | A1 |
20050055406 | Singhai et al. | Mar 2005 | A1 |
20050068897 | Arita et al. | Mar 2005 | A1 |
20050076196 | Zimmer et al. | Apr 2005 | A1 |
20050076244 | Watanabe | Apr 2005 | A1 |
20050108385 | Wechter et al. | May 2005 | A1 |
20050114620 | Justen | May 2005 | A1 |
20050117601 | Anderson et al. | Jun 2005 | A1 |
20050138628 | Bradford et al. | Jun 2005 | A1 |
20050140683 | Collins et al. | Jun 2005 | A1 |
20050149711 | Zimmer et al. | Jul 2005 | A1 |
20050157781 | Ho et al. | Jul 2005 | A1 |
20050198777 | Mabe | Sep 2005 | A1 |
20050278498 | Ahluwalia et al. | Dec 2005 | A1 |
20050285862 | Noda et al. | Dec 2005 | A1 |
20060039285 | Chapman et al. | Feb 2006 | A1 |
20060047989 | Delgado et al. | Mar 2006 | A1 |
20060075119 | Hussain et al. | Apr 2006 | A1 |
20060107071 | Girish et al. | May 2006 | A1 |
20060136570 | Pandya | Jun 2006 | A1 |
20060186700 | Browne et al. | Aug 2006 | A1 |
20060186706 | Browne et al. | Aug 2006 | A1 |
20060215697 | Olderdissen | Sep 2006 | A1 |
20060218301 | O'Toole et al. | Sep 2006 | A1 |
20060232051 | Morris et al. | Oct 2006 | A1 |
20060248542 | Wang et al. | Nov 2006 | A1 |
20070005869 | Balraj et al. | Jan 2007 | A1 |
20070008983 | Van Doren et al. | Jan 2007 | A1 |
20070043901 | Wu et al. | Feb 2007 | A1 |
20070063540 | Browne et al. | Mar 2007 | A1 |
20070063541 | Browne et al. | Mar 2007 | A1 |
20070070997 | Weitz et al. | Mar 2007 | A1 |
20070080013 | Melz et al. | Apr 2007 | A1 |
20070086480 | Elzur | Apr 2007 | A1 |
20070118831 | Kondo | May 2007 | A1 |
20070180041 | Suzuoki | Aug 2007 | A1 |
20070183418 | Riddoch et al. | Aug 2007 | A1 |
20070201492 | Kobayashi | Aug 2007 | A1 |
20070226375 | Chu et al. | Sep 2007 | A1 |
20070226417 | Davis | Sep 2007 | A1 |
20070255802 | Aloni et al. | Nov 2007 | A1 |
20070255866 | Aloni et al. | Nov 2007 | A1 |
20070261307 | Alexander | Nov 2007 | A1 |
20070286246 | Kobayashi | Dec 2007 | A1 |
20080005794 | Inoue et al. | Jan 2008 | A1 |
20080007081 | Shibata et al. | Jan 2008 | A1 |
20080010563 | Nishimura | Jan 2008 | A1 |
20080046689 | Chen et al. | Feb 2008 | A1 |
20080077816 | Ravichandran | Mar 2008 | A1 |
20080100079 | Herrera et al. | May 2008 | A1 |
20080100092 | Gao et al. | May 2008 | A1 |
20080120911 | Browne et al. | May 2008 | A1 |
20080127292 | Cooper et al. | May 2008 | A1 |
20080148291 | Huang et al. | Jun 2008 | A1 |
20080183931 | Verm et al. | Jul 2008 | A1 |
20080231711 | Glen et al. | Sep 2008 | A1 |
20080235355 | Spanier et al. | Sep 2008 | A1 |
20080244259 | Zimmer et al. | Oct 2008 | A1 |
20080301148 | Lee et al. | Dec 2008 | A1 |
20090006920 | Munson et al. | Jan 2009 | A1 |
20090024924 | Kim | Jan 2009 | A1 |
20090064177 | Bauer | Mar 2009 | A1 |
20090092057 | Doctor et al. | Apr 2009 | A1 |
20090113141 | Bullman et al. | Apr 2009 | A1 |
20090138650 | Lin et al. | May 2009 | A1 |
20090172674 | Bobak et al. | Jul 2009 | A1 |
20090177847 | Ceze et al. | Jul 2009 | A1 |
20090189442 | Chi | Jul 2009 | A1 |
20090225818 | Dapper et al. | Sep 2009 | A1 |
20090240874 | Pong | Sep 2009 | A1 |
20090265723 | Mochizuki et al. | Oct 2009 | A1 |
20090322531 | Estevez et al. | Dec 2009 | A1 |
20100005014 | Castle et al. | Jan 2010 | A1 |
20100017655 | Gooding et al. | Jan 2010 | A1 |
20100049876 | Pope et al. | Feb 2010 | A1 |
20100057932 | Pope et al. | Mar 2010 | A1 |
20100082859 | Hendry et al. | Apr 2010 | A1 |
20100098419 | Levy et al. | Apr 2010 | A1 |
20100118041 | Chen et al. | May 2010 | A1 |
20100329319 | Dai et al. | Dec 2010 | A1 |
20110029696 | Uehara | Feb 2011 | A1 |
20110035575 | Kwon | Feb 2011 | A1 |
20110052142 | Sultenfuss et al. | Mar 2011 | A1 |
20110083002 | Albers et al. | Apr 2011 | A1 |
20110161619 | Kaminski et al. | Jun 2011 | A1 |
20110219208 | Asaad et al. | Sep 2011 | A1 |
20110242425 | Zeng | Oct 2011 | A1 |
20110246742 | Kogen et al. | Oct 2011 | A1 |
20110276710 | Mighani et al. | Nov 2011 | A1 |
20110292936 | Wang et al. | Dec 2011 | A1 |
20110310296 | Lee et al. | Dec 2011 | A1 |
20110320861 | Bayer et al. | Dec 2011 | A1 |
20120017063 | Hummel et al. | Jan 2012 | A1 |
20120036334 | Horman et al. | Feb 2012 | A1 |
20120072658 | Hashimoto | Mar 2012 | A1 |
20120084483 | Sanjive | Apr 2012 | A1 |
20120084484 | Post et al. | Apr 2012 | A1 |
20120102307 | Wong | Apr 2012 | A1 |
20120124252 | Kayama | May 2012 | A1 |
20120151472 | Koch | Jun 2012 | A1 |
20120203880 | Kluyt et al. | Aug 2012 | A1 |
20120224640 | Sole Rojals et al. | Sep 2012 | A1 |
20120229076 | Zhu et al. | Sep 2012 | A1 |
20120260017 | Mine et al. | Oct 2012 | A1 |
20130039278 | Bouazizi et al. | Feb 2013 | A1 |
20130050216 | Whitby-Strevens et al. | Feb 2013 | A1 |
20130057567 | Frank et al. | Mar 2013 | A1 |
20130067188 | Mehra et al. | Mar 2013 | A1 |
20130091772 | Berger et al. | Apr 2013 | A1 |
20130111014 | Lawrie et al. | May 2013 | A1 |
20130138840 | Kegel et al. | May 2013 | A1 |
20130162911 | Glen | Jun 2013 | A1 |
20130204927 | Kruglikov et al. | Aug 2013 | A1 |
20130205113 | Ahmad et al. | Aug 2013 | A1 |
20130275976 | Dawson et al. | Oct 2013 | A1 |
20130290947 | Li | Oct 2013 | A1 |
20130347131 | Mooring et al. | Dec 2013 | A1 |
20140033220 | Campbell et al. | Jan 2014 | A1 |
20140068624 | Fuller et al. | Mar 2014 | A1 |
20140068636 | Dupont et al. | Mar 2014 | A1 |
20140122695 | Kulikov et al. | May 2014 | A1 |
20140122828 | Kagan et al. | May 2014 | A1 |
20140173236 | Kegel | Jun 2014 | A1 |
20140189057 | Sankoda et al. | Jul 2014 | A1 |
20140211894 | Yang | Jul 2014 | A1 |
20140247983 | MacInnis et al. | Sep 2014 | A1 |
20140355606 | Riddoch et al. | Dec 2014 | A1 |
20150007262 | Aissi et al. | Jan 2015 | A1 |
20150036051 | Broberg et al. | Feb 2015 | A1 |
20150058444 | Willmann | Feb 2015 | A1 |
20150081985 | Archer et al. | Mar 2015 | A1 |
20150156122 | Singh et al. | Jun 2015 | A1 |
20150172345 | Mantin et al. | Jun 2015 | A1 |
20150189109 | Whitby-Strevens et al. | Jul 2015 | A1 |
20150205749 | Whitby-Strevens et al. | Jul 2015 | A1 |
20150212806 | Hsieh | Jul 2015 | A1 |
20150244804 | Warfield et al. | Aug 2015 | A1 |
20150261588 | Liu et al. | Sep 2015 | A1 |
20150309940 | Kumar | Oct 2015 | A1 |
20150326542 | Serebrin | Nov 2015 | A1 |
20150363110 | Batra et al. | Dec 2015 | A1 |
20150370582 | Kinsella et al. | Dec 2015 | A1 |
20150378737 | Debbage et al. | Dec 2015 | A1 |
20160028635 | Wang | Jan 2016 | A1 |
20160034195 | Li et al. | Feb 2016 | A1 |
20160041852 | Suarez Gracia et al. | Feb 2016 | A1 |
20160044143 | Narasimhamurthy | Feb 2016 | A1 |
20160063258 | Ackerly | Mar 2016 | A1 |
20160077989 | Pulyala et al. | Mar 2016 | A1 |
20160103480 | Sanghi et al. | Apr 2016 | A1 |
20160103689 | Sanghi et al. | Apr 2016 | A1 |
20160103743 | Sanghi et al. | Apr 2016 | A1 |
20160142988 | Powell et al. | May 2016 | A1 |
20160208539 | Hofmann et al. | Jul 2016 | A1 |
20160224442 | Sanghi et al. | Aug 2016 | A1 |
20160226957 | Zhang et al. | Aug 2016 | A1 |
20160226967 | Zhang et al. | Aug 2016 | A1 |
20160231929 | Tsirkin | Aug 2016 | A1 |
20160261632 | Kölhi et al. | Sep 2016 | A1 |
20160269991 | Van Greunen et al. | Sep 2016 | A1 |
20160357443 | Li et al. | Dec 2016 | A1 |
20160363955 | Stevens et al. | Dec 2016 | A1 |
20160364350 | Sanghi et al. | Dec 2016 | A1 |
20160378545 | Ho | Dec 2016 | A1 |
20170003977 | Sumida et al. | Jan 2017 | A1 |
20170003997 | Kelly et al. | Jan 2017 | A1 |
20170075856 | Suzue et al. | Mar 2017 | A1 |
20170089641 | Humfeld et al. | Mar 2017 | A1 |
20170108912 | Li et al. | Apr 2017 | A1 |
20170111283 | Kumar et al. | Apr 2017 | A1 |
20170124327 | Kumbhar et al. | May 2017 | A1 |
20170126726 | Han | May 2017 | A1 |
20170147282 | Seo | May 2017 | A1 |
20170149890 | Shamis et al. | May 2017 | A1 |
20170187621 | Shalev et al. | Jun 2017 | A1 |
20170187846 | Shalev et al. | Jun 2017 | A1 |
20170249098 | Petkov et al. | Aug 2017 | A1 |
20170264497 | Lim | Sep 2017 | A1 |
20170286300 | Doshi et al. | Oct 2017 | A1 |
20170286322 | Garg et al. | Oct 2017 | A1 |
20170286323 | Garg et al. | Oct 2017 | A1 |
20170308460 | Guthula et al. | Oct 2017 | A1 |
20170337588 | Chittilappilly et al. | Nov 2017 | A1 |
20170353499 | Huang et al. | Dec 2017 | A1 |
20170371591 | Xia et al. | Dec 2017 | A1 |
20180004690 | Kaminski et al. | Jan 2018 | A1 |
20180070341 | Islam et al. | Mar 2018 | A1 |
20180081829 | Kaplan | Mar 2018 | A1 |
20180129261 | Garg et al. | May 2018 | A1 |
20180129269 | Garg et al. | May 2018 | A1 |
20180129270 | Garg et al. | May 2018 | A1 |
20180173643 | Yu et al. | Jun 2018 | A1 |
20180196648 | Henderson et al. | Jul 2018 | A1 |
20180219805 | MacNeil et al. | Aug 2018 | A1 |
20180219976 | Decenzo et al. | Aug 2018 | A1 |
20180239657 | Petrbok et al. | Aug 2018 | A1 |
20180248847 | Guri et al. | Aug 2018 | A1 |
20180253315 | Norton et al. | Sep 2018 | A1 |
20180285561 | Frank et al. | Oct 2018 | A1 |
20180295052 | Laurent | Oct 2018 | A1 |
20180329743 | Pope et al. | Nov 2018 | A1 |
20180343206 | White et al. | Nov 2018 | A1 |
20180357176 | Wang | Dec 2018 | A1 |
20190007850 | DenBoer et al. | Jan 2019 | A1 |
20190036893 | Jiang | Jan 2019 | A1 |
20190052659 | Weingarten et al. | Feb 2019 | A1 |
20190065301 | Tsirkin et al. | Feb 2019 | A1 |
20190097938 | Talla et al. | Mar 2019 | A1 |
20190102303 | Wang et al. | Apr 2019 | A1 |
20190102568 | Hausauer et al. | Apr 2019 | A1 |
20190109714 | Clark et al. | Apr 2019 | A1 |
20190140983 | Tu et al. | May 2019 | A1 |
20190141041 | Bhabbur et al. | May 2019 | A1 |
20190147066 | Ben Dayan et al. | May 2019 | A1 |
20190147069 | Ben Dayan et al. | May 2019 | A1 |
20190205533 | Diehl et al. | Jul 2019 | A1 |
20190213044 | Cui et al. | Jul 2019 | A1 |
20190213166 | Petkov et al. | Jul 2019 | A1 |
20190253351 | Ihlar et al. | Aug 2019 | A1 |
20190286466 | Tsirkin et al. | Sep 2019 | A1 |
20190303204 | Masputra et al. | Oct 2019 | A1 |
20190303205 | Masputra et al. | Oct 2019 | A1 |
20190303221 | Masputra et al. | Oct 2019 | A1 |
20190303222 | Masputra et al. | Oct 2019 | A1 |
20190303280 | Masputra et al. | Oct 2019 | A1 |
20190303562 | Masputra et al. | Oct 2019 | A1 |
20190303576 | Masputra | Oct 2019 | A1 |
20190306076 | Masputra et al. | Oct 2019 | A1 |
20190306087 | Masputra et al. | Oct 2019 | A1 |
20190306109 | Masputra et al. | Oct 2019 | A1 |
20190306281 | Masputra et al. | Oct 2019 | A1 |
20190306282 | Masputra et al. | Oct 2019 | A1 |
20200019695 | Sovio et al. | Jan 2020 | A1 |
20200036615 | Lewis | Jan 2020 | A1 |
20200045015 | Nukala et al. | Feb 2020 | A1 |
20200065244 | Sanghi et al. | Feb 2020 | A1 |
20200073829 | Tsirkin et al. | Mar 2020 | A1 |
20200195684 | Linz | Jun 2020 | A1 |
20210011856 | Xia et al. | Jan 2021 | A1 |
20210097006 | Masputra et al. | Apr 2021 | A1 |
20210099391 | Masputra et al. | Apr 2021 | A1 |
20210099427 | Masputra et al. | Apr 2021 | A1 |
20210303375 | Stevens | Sep 2021 | A1 |
20220030095 | Masputra et al. | Jan 2022 | A1 |
20220046117 | Masputra et al. | Feb 2022 | A1 |
20230155980 | Masputra et al. | May 2023 | A1 |
Number | Date | Country |
---|---|---|
3013008 | Apr 2016 | EP |
H02306082 | Dec 1990 | JP |
H03169996 | Jul 1991 | JP |
2004086792 | Mar 2004 | JP |
2012108677 | Jun 2012 | JP |
2013246642 | Dec 2013 | JP |
2015001867 | Jan 2015 | JP |
WO 2008070138 | Jun 2008 | WO |
Entry |
---|
Moon-Sang Lee, Joonwon Lee and S. Maeng, “Context-aware address translation for high-performance SMP cluster system,” 2008 IEEE International Conference on Cluster Computing, Tsukuba, 2008, pp. 292-297, doi: 10.1109/CLUSTR.2008.4663784. (Year: 2008). |
Honda et al., “Rekindling Network Protocol Innovation with User-Level Stacks”, ACM SIGCOMM Computer Communication Review, vol. 44, No. 2, Apr. 2014. |
Gopalakrishnan R., et al., “Efficient User-Space Protocol Implementations with QoS Guarantees Using Real-Time Upcalls”, IEEE/ACM Transactions on Networking, Aug. 1998, vol. 6 (4), pp. 374-388. |
ECN L1 PM Substates with CLKREQ approved Aug. 23, 2012. |
Jackson, “PCI Express Technology”, Sep. 2012 (Sep. 2012), MindShare Press, xP002777351, pp. 49,86,87,712-723. |
PCI Express base Specification Revision 3.0, published Nov. 10, 2010. |
PCI Express Base Specification Revision 3.1, published Oct. 8, 2014. |
Universal Serial Bus, Communication Class, Subclass Specifications for Network Control Model (NCM) Devices; Revision 1.0 (Errata 1), Nov. 24, 2010, published by USB Implementers Forum, Inc. |
Whitworth, “Improving Networking by moving the network stack to userspace”, Imperial College London, Jun. 14, 2010 [Mar. 17, 2022]; retrieved from the Internet: <URL https://www.doc.ic.ac.uk/teaching/distinguished-projects/2010/m.whitworth.pdf> (Year: 2010). |
Number | Date | Country | |
---|---|---|---|
20220083388 A1 | Mar 2022 | US |
Number | Date | Country | |
---|---|---|---|
63078247 | Sep 2020 | US |