Methods and example implementations described herein are generally directed to Field-Programmable Gate-Arrays (FPGAs) or other programmable logic devices (PLDs) or other devices based thereon, and more specifically, to the addition of networks-on-chip (NoC) to FPGAs to customize traffic and optimize performance. This includes both modifications to the FPGA architecture and design flow.
The number of components on a chip is rapidly growing due to increasing levels of integration, system complexity and shrinking transistor geometry. Complex System-on-Chips (SoCs) may involve a variety of components e.g., processor cores, DSPs, hardware accelerators, memory and I/O, while Chip Multi-Processors (CMPs) may involve a large number of homogenous processor cores, memory and I/O subsystems. In both SoC and CMP systems, the on-chip interconnect plays a role in providing high-performance communication between the various components. Due to scalability limitations of traditional buses and crossbar based interconnects, Network-on-Chip (NoC) has emerged as a paradigm to interconnect a large number of components on the chip. NoC is a global shared communication infrastructure made up of several routing nodes interconnected with each other using point-to-point physical links.
Messages are injected by the source and are routed from the source node to the destination over multiple intermediate nodes and physical links. The destination node then ejects the message and provides the message to the destination. For the remainder of this application, the terms ‘components’, ‘blocks’, ‘hosts’ or ‘cores’ will be used interchangeably to refer to the various system components which are interconnected using a NoC. Terms ‘routers’ and ‘nodes’ will also be used interchangeably. Without loss of generalization, the system with multiple interconnected components will itself be referred to as a ‘multi-core system’.
There are several topologies in which the routers can connect to one another to create the system network. Bi-directional rings (as shown in
Packets are message transport units for intercommunication between various components. Routing involves identifying a path that is a set of routers and physical links of the network over which packets are sent from a source to a destination. Components are connected to one or multiple ports of one or multiple routers; with each such port having a unique identification (ID). Packets can carry the destination's router and port ID for use by the intermediate routers to route the packet to the destination component.
Examples of routing techniques include deterministic routing, which involves choosing the same path from A to B for every packet. This form of routing is independent from the state of the network and does not load balance across path diversities, which might exist in the underlying network. However, such deterministic routing may implemented in hardware, maintains packet ordering and may be rendered free of network level deadlocks. Shortest path routing may minimize the latency as such routing reduces the number of hops from the source to the destination. For this reason, the shortest path may also be the lowest power path for communication between the two components. Dimension-order routing is a form of deterministic shortest path routing in 2-D, 2.5-D, and 3-D mesh networks. In this routing scheme, messages are routed along each coordinates in a particular sequence until the message reaches the final destination. For example in a 3-D mesh network, one may first route along the X dimension until it reaches a router whose X-coordinate is equal to the X-coordinate of the destination router. Next, the message takes a turn and is routed in along Y dimension and finally takes another turn and moves along the Z dimension until the message reaches the final destination router. Dimension ordered routing may be minimal turn and shortest path routing.
In heterogeneous mesh topology in which one or more routers or one or more links are absent, dimension order routing may not be feasible between certain source and destination nodes, and alternative paths may have to be taken. The alternative paths may not be shortest or minimum turn.
Source routing and routing using tables are other routing options used in NoC. Adaptive routing can dynamically change the path taken between two points on the network based on the state of the network. This form of routing may be complex to analyze and implement.
A NoC interconnect may contain multiple physical networks. Over each physical network, there exist multiple virtual networks, wherein different message types are transmitted over different virtual networks. In this case, at each physical link or channel, there are multiple virtual channels; each virtual channel may have dedicated buffers at both end points. In any given clock cycle, only one virtual channel can transmit data on the physical channel.
NoC interconnects may employ wormhole routing, wherein, a large message or packet is broken into small pieces known as flits (also referred to as flow control digits). The first flit is a header flit, which holds information about this packet's route and key message level info along with payload data and sets up the routing behavior for all subsequent flits associated with the message. Optionally, one or more body flits follows the header flit, containing remaining payload of data. The final flit is a tail flit, which, in addition to containing last payload, also performs some bookkeeping to close the connection for the message. In wormhole flow control, virtual channels are often implemented.
The physical channels are time sliced into a number of independent logical channels called virtual channels (VCs). VCs provide multiple independent paths to route packets, however they are time-multiplexed on the physical channels. A virtual channel holds the state needed to coordinate the handling of the flits of a packet over a channel. At a minimum, this state identifies the output channel of the current node for the next hop of the route and the state of the virtual channel (idle, waiting for resources, or active). The virtual channel may also include pointers to the flits of the packet that are buffered on the current node and the number of flit buffers available on the next node.
The term “wormhole” plays on the way messages are transmitted over the channels: the output port at the next router can be so short that received data can be translated in the head flit before the full message arrives. This allows the router to quickly set up the route upon arrival of the head flit and then opt out from the rest of the conversation. Since a message is transmitted flit by flit, the message may occupy several flit buffers along its path at different routers, creating a worm-like image.
Based upon the traffic between various end points, and the routes and physical networks that are used for various messages, different physical channels of the NoC interconnect may experience different levels of load and congestion. The capacity of various physical channels of a NoC interconnect is determined by the width of the channel (number of physical wires) and the clock frequency at which it is operating. Various channels of the NoC may operate at different clock frequencies, and various channels may have different widths based on the bandwidth requirement at the channel. The bandwidth requirement at a channel is determined by the flows that traverse over the channel and their bandwidth values. Flows traversing over various NoC channels are affected by the routes taken by various flows. In a mesh or Torus NoC, there exist multiple route paths of equal length or number of hops between any pair of source and destination nodes. For example, in
In a NoC with statically allocated routes for various traffic slows, the load at various channels may be controlled by intelligently selecting the routes for various flows. When a large number of traffic flows and substantial path diversity is present, routes can be chosen such that the load on all NoC channels is balanced nearly uniformly, thus avoiding a single point of bottleneck. Once routed, the NoC channel widths can be determined based on the bandwidth demands of flows on the channels. Unfortunately, channel widths cannot be arbitrarily large due to physical hardware design restrictions, such as timing or wiring congestion. There may be a limit on the maximum channel width, thereby putting a limit on the maximum bandwidth of any single NoC channel.
Additionally, wider physical channels may not help in achieving higher bandwidth if messages are short. For example, if a packet is a single flit packet with a 64-bit width, then no matter how wide a channel is, the channel will only be able to carry 64 bits per cycle of data if all packets over the channel are similar. Thus, a channel width is also limited by the message size in the NoC. Due to these limitations on the maximum NoC channel width, a channel may not have enough bandwidth in spite of balancing the routes.
To address the above bandwidth concern, multiple parallel physical NoCs may be used. Each NoC may be called a layer, thus creating a multi-layer NoC architecture. Hosts inject a message on a NoC layer; the message is then routed to the destination on the NoC layer, where it is delivered from the NoC layer to the host. Thus, each layer operates more or less independently from each other, and interactions between layers may only occur during the injection and ejection times.
In
In a multi-layer NoC, the number of layers needed may depend upon a number of factors such as the aggregate bandwidth requirement of all traffic flows in the system, the routes that are used by various flows, message size distribution, maximum channel width, etc. Once the number of NoC layers in NoC interconnect is determined in a design, different messages and traffic flows may be routed over different NoC layers. Additionally, one may design NoC interconnects such that different layers have different topologies in number of routers, channels and connectivity. The channels in different layers may have different widths based on the flows that traverse over the channel and their bandwidth requirements.
System on Chips (SoCs) are becoming increasingly sophisticated, feature rich, and high performance by integrating a growing number of standard processor cores, memory and I/O subsystems, and specialized acceleration IPs. To address this complexity, NoC approach of connecting SoC components is gaining popularity. A NoC can provide connectivity to a plethora of components and interfaces and simultaneously enable rapid design closure by being automatically generated from a high level specification. The specification describes interconnect requirements of SoC in terms of connectivity, bandwidth, and latency. In addition to this, information such as position of various components such as bridges or ports on boundary of hosts, traffic information, chip size information, etc. may be supplied. A NoC compiler (topology generation engine) can then use this specification to automatically design a NoC for the SoC. A number of NoC compilers were introduced in the related art that automatically synthesize a NoC to fit a traffic specification. In such design flows, the synthesized NoC is simulated to evaluate the performance under various operating conditions and to determine whether the specifications are met. This may be necessary because NoC-style interconnects are distributed systems and their dynamic performance characteristics under load are difficult to predict statically and can be very sensitive to a wide variety of parameters. Specifications can also be in the form of power specifications to define power domains, voltage domains, clock domains, and so on, depending on the desired implementation.
Placing hosts/IP cores in a SoC floorplan to optimize the interconnect performance can be important. For example, if two hosts communicate with each other frequently and require higher bandwidth than other interconnects, it may be better to place them closer to each other so that the transactions between these hosts can go over fewer router hops and links and the overall latency and the NoC cost can be reduced.
Assuming that two hosts with certain shapes and sizes cannot spatially overlap with each other on a 2D SoC plane, tradeoffs may need to be made. Moving certain hosts closer to improve inter-communication between them, may force certain other hosts to be further apart, thereby penalizing inter-communication between those other hosts. To make tradeoffs that improve system performance, certain performance metrics such as average global communication latency may be used as an objective function to optimize the SoC architecture with the hosts being placed in a NoC topology. Determining substantially optimal host positions that maximizes the system performance metric may involve analyzing the connectivity and inter-communication properties between all hosts and judiciously placing them onto the 2D NoC topology. In case if inter-communicating hosts are placed far from each other, this can leads to high average and peak structural latencies in number of hops. Such long paths not only increase latency but also adversely affect the interconnect bandwidth, as messages stay in the NoC for longer periods and consume bandwidth of a large number of links.
Also, existing integrated circuits such as programmable logic devices (PLDs) typically utilize “point-to-point” routing, meaning that a path between a source signal generator and one or more destinations is generally fixed at compile time. For example, a typical implementation of an A-to-B connection in a PLD involves connecting logic areas through an interconnect stack of pre—defined horizontal wires. These horizontal wires have a fixed length, are arranged into bundles, and are typically reserved for that A-to-B connection for the entire operation of the PLDs configuration bit stream. Even where a user is able to subsequently change some features of the point-to-point routing, e.g., through partial recompilation, such changes generally apply to block-level replacements, and not to cycle-by-cycle routing implementations.
Such existing routing methods may render the device inefficient, e.g., when the routing is not used every cycle. A first form of inefficiency occurs because of inefficient wire use. In a first example, when an A-to-B connection is rarely used (for example, if the signal value generated by the source logic area at A rarely changes or the destination logic area at B is rarely programmed to be affected by the result), then the conductors used to implement the A-to-B connection may unnecessarily take up metal, power, and/or logic resources. In a second example, when a multiplexed bus having N inputs is implemented in a point-to-point fashion, metal resources may be wasted on routing data from each of the N possible input wires because the multiplexed bus, by definition, outputs only one of the N input wires and ignores the other N−1 input wires. Power resources may also be wasted in these examples when spent in connection with data changes that do not affect a later computation. A more general form of this inefficient wire use occurs when more than one producer generates data that is serialized through a single consumer or the symmetric case where one producer produces data that is used in a round-robin fashion by two or more consumers.
A second form of inefficiency, called slack-based inefficiency, occurs when a wire is used, but below its full potential, e.g., in terms of delay. For example, if the data between a producer and a consumer is required to be transmitted every 300 ps, and the conductor between them is capable of transmitting the data in a faster, 100 ps timescale, then the 200 ps of slack time in which the conductor is idle is a form of inefficiency or wasted bandwidth. These two forms of wire underutilization, e.g., inefficient wire use and slack-based inefficiency, can occur separately or together, leading to inefficient use of resources, and wasting valuable wiring, power, and programmable multiplexing resources.
In many cases, the high-level description of the logic implemented on a PLD may already imply sharing of resources, such as sharing access to an external memory or a high-speed transceiver. To do this, it is common to synthesize higher-level structures representing busses onto PLDs. In one example, a software tool may generate an industry-defined bus as Register-Transfer-Level (RTL)/Verilog logic, which is then synthesized into an FPGA device. In this case, however, that shared bus structure is still implemented in the manner discussed above, meaning that it is actually converted into point-to-point static routing. Even in a scheme involving time-multiplexing of FPGA wires, routing is still limited to an individual-wire basis and does not offer grouping capabilities.
In large-scale networks, efficiency and performance/area tradeoff is of main concern. Mechanisms such as machine learning approach, simulation annealing, among others, provide optimized topology for a system. However, such complex mechanisms have substantial limitations as they involve certain algorithms to automate optimization of layout network, which may violate previously mapped flow's latency constraint or the latency constraint of current flow. Further, it is also to be considered that each user has their own requirements and/or need for SoCs and/or NoCs depending on a diverse applicability of the same. Therefore, there is a need for systems and methods that significantly improve system efficiency by accurately indicating the best possible positions and configurations for hosts and ports within the hosts, along with indicating system level routes to be taken for traffic flows using the NoC interconnect architecture. Systems and methods are also required for automatically generating an optimized topology for a given SoC floor plan and traffic specification with an efficient layout. Further, systems and methods are also required that allows users to specify their requirements for a particular SoC and/or NoC, provides various options for satisfying their requirements and based on this automatically generating an optimized topology for a given SoC floor plan and traffic specification with an efficient layout.
Integrating NoC with FPGA since bandwidth requirements are increasing rapidly and FPGAs are becoming bigger and bigger. However, FPGAs are becoming bigger and bigger the conventional soft logic to provide sufficient bandwidth is also growing rapid which are not achieved by the conventional techniques. Thus there is requirement of provide a combination of hardened logic and soft logic to provide a probability of achieving the requirements.
Also, once the hardened NoC is built over the FPGA, there is a need for mapping the traffic incoming and outgoing to a particular layer or merchant channel of within layer routing their needs a flexibility to choose route for the traffic (since there are multiple routes present).
In a NoC interconnect, if the traffic profile is not uniform and there is a certain amount of heterogeneity (e.g., certain hosts talking to each other more frequently than the others), the interconnect performance may depend on the NoC topology and where various hosts are placed in the topology with respect to each other and to what routers they are connected to. For example, if two hosts talk to each other frequently and require higher bandwidth than other interconnects, then they should be placed next to each other. This will reduce the latency for this communication which thereby reduces the global average latency, as well as reduce the number of router nodes and links over which the higher bandwidth of this communication must be provisioned.
Moving two hosts closer together may make certain other hosts far apart since all hosts must fit into the 2D planar NoC topology without overlapping with each other. Thus, various tradeoffs must be made and the hosts must be placed after examining the pair-wise bandwidth and latency requirements between all hosts so that certain global cost and performance metrics is optimized. The cost and performance metrics can be, for example, average structural latency between all communicating hosts in number of router hops, or sum of bandwidth between all pair of hosts and the distance between them in number of hops, or some combination of these two. This optimization problem is known to be NP-hard and heuristic based approaches are often used. The hosts in a system may vary in shape and sizes with respect to each other, which puts additional complexity in placing them in a 2D planar NoC topology, packing them optimally while leaving little whitespaces, and avoiding overlapping hosts.
The optimization approaches introduced so far to determine the channel capacity, routes, host positions, etc., are useful when the exact traffic profile is known in advance at the NoC design time. If the precise traffic profile is not known at the design time, and the traffic profile changes during the NoC operation based on the SoC application's requirements, then the NoC design must allow these adjustments. For the NoC to allow these changes, the NoC must be designed so that it has knowledge of the changes that may occur in the traffic profile in a given system and ensure that any combination of allowable traffic profiles are supported by the NoC hardware architecture.
Therefore, there exists a need for methods, systems, and computer readable mediums for overcoming the above-mentioned issues with existing implementations of generating topology for a given NoC. Further, there exists a need for methods, systems, and computer readable mediums for having a programmable fabric and a communication network integrated with the programmable fabric for high-speed data passing.
Methods and example implementations described herein are generally directed to Field-Programmable Gate-Arrays (FPGAs) or other programmable logic devices (PLDs) or other devices based thereon, and more specifically, to the addition of networks-on-chip (NoC) to FPGAs to customize traffic and optimize performance. This includes both modifications to the FPGA architecture and design flow.
Aspects of the present application relate to methods, systems, and computer readable mediums for overcoming the above-mentioned issues with existing implementations of generating topology for a given NoC by significantly improving system efficiency by facilitating efficient creation of NoC designs utilizing existing or new circuit block information. The system and method provides a programmable fabric and a communication network integrated with the programmable fabric for high-speed data passing.
An aspect of the present application relates to a Field-Programmable Gate-Array (FPGA) system. The FPGA system can include an FPGA having one or more lookup tables (LUTs) and wires, and a Network-on-Chip (NoC) having a hardened network topology configured to provide connectivity at a higher frequency that the FPGA. The NoC is coupled to the FPGA to receive an profile information associated with an application, retrieve at least a characteristic, selected form any of combination of any or combination of a bandwidth requirement, latency requirement, protocol requirement and transactions, associated with the application from the profile information, generate at least one application traffic graph having mapping information based on the characteristic retrieved, and map the application traffic graph generated with into the FPGA using the hardened NoC.
In an aspect, while the hardened NoC is deployed in the FPGA, reconfiguring the hardened NoC in accordance with the application traffic graph. In another aspect, reconfiguring the hardened NoC comprises receiving mapping information for one or more characteristic associated with the application and transmitting the mapping information to the hardened NoC.
In an aspect, the application traffic graph includes a plurality of nodes indicative of representations of traffic associated with the application, wherein the plurality of nodes interacts based on bandwidth requirements, latency requirements, protocol requirements and transactions retrieved.
In an aspect, the mapping information comprises transaction assignments of one or more traffic profiles to each NoC layer in the hardened NoC and route assignments for each NoC layer in the hardened NoC.
In an aspect, the hardened NoC further determines all allowed subsets of the plurality of application traffic profiles, and determine a NoC configuration that is configured to support the determined all allowed subsets. In another aspect, the NoC configuration is further includes one or more physical channels, one or more virtual channels, one or more NoC layers, Quality of Service (QoS) parameters for each of the one or more physical channels and the one or more virtual channels, and weights for each of the one or more physical channels and the one or more virtual channels.
In an aspect, the application traffic graph is received from a user. In another aspect, the application traffic graph is generated based on the traffic profile fed to the FPGA system. In yet another aspect, the application traffic graph is generated based on one or more meta-data associated with one or more packet received by the FPGA system.
In an aspect, the system is further configured to determine at least a part of application graph to be mapped with the hardened NoC and at least a part of application graph to be mapped with the soft logic.
In an aspect, the NoC includes a mechanism for being configured by software to modify one or more functions associated with the NoC. In another aspect, the one or more functions of the NoC are associated with any of combination quality of service (QoS), priority, virtual channel (VC) allocation, rate limits, buffer sizing, layer/physical channel assignment.
In an aspect, the NoC includes virtual channel (VC) and physical layers allocated based at least on quality of service (QoS), latency, bandwidth requirements, number of inputs/outputs (I/Os), memories, soft intellectual properties (IPs) that are connected to the NoC.
In an aspect, the NoC includes one or more bridges configured to support multiple protocols.
In an aspect, the NoC includes at least a programmable decoding element to determine any or combination of a route, a layer and destination information from one or more messages transported over the NoC.
An aspect of the present application is to provide a method that include the steps of receiving an profile information associated with an application by a Network-on-Chip (NoC), retrieving at least a characteristic, selected from any or combination of a bandwidth requirement, latency requirement, protocol requirement and transactions, associated with the application from the profile information, generating at least one application traffic graph having mapping information based on the characteristic retrieved, and mapping the application traffic graph generated with into the FPGA using the hardened NoC.
In an aspect, while the hardened NoC is deployed in the FPGA, reconfiguring the hardened NoC in accordance with the application traffic graph. In another aspect, reconfiguring the hardened NoC comprises receiving mapping information for one or more characteristic associated with the application and transmitting the mapping information to the hardened NoC.
In an aspect, the application traffic graph includes a plurality of nodes indicative of representations of traffic associated with the application, wherein the plurality of nodes interacts based on bandwidth requirements, latency requirements, protocol requirements and transactions retrieved.
In an aspect, the mapping information comprises transaction assignments of one or more traffic profiles to each NoC layer in the hardened NoC and route assignments for each NoC layer in the hardened NoC.
In an aspect, the hardened NoC further determines all allowed subsets of the plurality of application traffic profiles, and determine a NoC configuration that is configured to support the determined all allowed subsets. In another aspect, the NoC configuration is further includes one or more physical channels, one or more virtual channels, one or more NoC layers, Quality of Service (QoS) parameters for each of the one or more physical channels and the one or more virtual channels, and weights for each of the one or more physical channels and the one or more virtual channels.
In an aspect, the application traffic graph is received from a user. In another aspect, the application traffic graph is generated based on the traffic profile fed to the FPGA system. In yet another aspect, the application traffic graph is generated based on one or more meta-data associated with one or more packet received by the FPGA system.
In an aspect, the method can further determine at least a part of application graph to be mapped with the hardened NoC and at least a part of application graph to be mapped with the soft logic.
In an aspect, the NoC includes a mechanism for being configured by software to modify one or more functions associated with the NoC. In another aspect, the one or more functions of the NoC are associated with any of combination quality of service (QoS), priority, virtual channel (VC) allocation, rate limits, buffer sizing, layer/physical channel assignment.
In an aspect, the NoC includes virtual channel (VC) and physical layers allocated based at least on quality of service (QoS), latency, bandwidth requirements, number of inputs/outputs (I/Os), memories, soft intellectual properties (IPs) that are connected to the NoC.
In an aspect, the NoC includes one or more bridges configured to support multiple protocols.
In an aspect, the NoC includes at least a programmable decoding element to determine any or combination of a route, a layer and destination information from one or more messages transported over the NoC.
An aspect of the present application relates to a non-transitory computer readable storage medium storing instructions for executing a process. The instructions include the steps of receiving an profile information associated with an application, retrieving at least a characteristic, selected from any or combination of a bandwidth requirement, latency requirement, protocol requirement and transactions, associated with the application from the profile information, generating at least one application traffic graph having mapping information based on the characteristic retrieved, and mapping the application traffic graph generated with into the FPGA using the hardened NoC.
The foregoing and other objects, features and advantages of the example implementations will be apparent and the following more particular descriptions of example implementations as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts of exemplary implementations of the application.
The following detailed description provides further details of the figures and example implementations of the present application. Reference numerals and descriptions of redundant elements between figures are omitted for clarity. Terms used throughout the description are provided as examples and are not intended to be limiting. For example, the use of the term “automatic” may involve fully automatic or semi-automatic implementations involving user or administrator control over certain aspects of the implementation, depending on the desired implementation of one of ordinary skill in the art practicing implementations of the present application.
Network-on-Chip (NoC) has emerged as a paradigm to interconnect a large number of components on the chip. NoC is a global shared communication infrastructure made up of several routing nodes interconnected with each other using point-to-point physical links. In example implementations, a NoC interconnect is generated from a specification by utilizing design tools. The specification can include constraints such as bandwidth/Quality of Service (QoS)/latency attributes that is to be met by the NoC, and can be in various software formats depending on the design tools utilized. Once the NoC is generated through the use of design tools on the specification to meet the specification requirements, the physical architecture can be implemented either by manufacturing a chip layout to facilitate the NoC or by generation of a register transfer level (RTL) for execution on a chip to emulate the generated NoC, depending on the desired implementation. Specifications may be in common power format (CPF), Unified Power Format (UPF), or others according to the desired specification. Specifications can be in the form of traffic specifications indicating the traffic, bandwidth requirements, latency requirements, interconnections, etc. depending on the desired implementation. Specifications can also be in the form of power specifications to define power domains, voltage domains, clock domains, and so on, depending on the desired implementation.
Methods and example implementations described herein are generally directed to Field-Programmable Gate-Arrays (FPGAs) or other programmable logic devices (PLDs) or other devices based thereon, and more specifically, to the addition of networks-on-chip (NoC) to FPGAs to customize traffic and optimize performance. This includes both modifications to the FPGA architecture and design flow.
Aspects of the present application relate to methods, systems, and computer readable mediums for overcoming the above-mentioned issues with existing implementations of generating topology for a given NoC by significantly improving system efficiency by facilitating efficient creation of NoC designs utilizing existing or new circuit block information. The system and method provides a programmable fabric and a communication network integrated with the programmable fabric for high-speed data passing.
An aspect of the present application relates to a Field-Programmable Gate-Array (FPGA) system. The FPGA system can include an FPGA having one or more lookup tables (LUTs) and wires, and a Network-on-Chip (NoC) having a hardened network topology configured to provide connectivity at a higher frequency that the FPGA. The NoC is coupled to the FPGA to receive an profile information associated with an application, retrieve at least a characteristic, selected form any of combination of any or combination of a bandwidth requirement, latency requirement, protocol requirement and transactions, associated with the application from the profile information, generate at least one application traffic graph having mapping information based on the characteristic retrieved, and map the application traffic graph generated with into the FPGA using the hardened NoC.
In an aspect, while the hardened NoC is deployed in the FPGA, reconfiguring the hardened NoC in accordance with the application traffic graph. In another aspect, reconfiguring the hardened NoC comprises receiving mapping information for one or more characteristic associated with the application and transmitting the mapping information to the hardened NoC.
In an aspect, the application traffic graph includes a plurality of nodes indicative of representations of traffic associated with the application, wherein the plurality of nodes interacts based on bandwidth requirements, latency requirements, protocol requirements and transactions retrieved.
In an aspect, the mapping information comprises transaction assignments of one or more traffic profiles to each NoC layer in the hardened NoC and route assignments for each NoC layer in the hardened NoC.
In an aspect, the hardened NoC further determines all allowed subsets of the plurality of application traffic profiles, and determine a NoC configuration that is configured to support the determined all allowed subsets. In another aspect, the NoC configuration is further includes one or more physical channels, one or more virtual channels, one or more NoC layers, Quality of Service (QoS) parameters for each of the one or more physical channels and the one or more virtual channels, and weights for each of the one or more physical channels and the one or more virtual channels.
In an aspect, the application traffic graph is received from a user. In another aspect, the application traffic graph is generated based on the traffic profile fed to the FPGA system. In yet another aspect, the application traffic graph is generated based on one or more meta-data associated with one or more packet received by the FPGA system.
In an aspect, the system is further configured to determine at least a part of application graph to be mapped with the hardened NoC and at least a part of application graph to be mapped with the soft logic.
In an aspect, the NoC includes a mechanism for being configured by software to modify one or more functions associated with the NoC. In another aspect, the one or more functions of the NoC are associated with any of combination quality of service (QoS), priority, virtual channel (VC) allocation, rate limits, buffer sizing, layer/physical channel assignment.
In an aspect, the NoC includes virtual channel (VC) and physical layers allocated based at least on quality of service (QoS), latency, bandwidth requirements, number of inputs/outputs (I/Os), memories, soft intellectual properties (IPs) that are connected to the NoC.
In an aspect, the NoC includes one or more bridges configured to support multiple protocols.
In an aspect, the NoC includes at least a programmable decoding element to determine any or combination of a route, a layer and destination information from one or more messages transported over the NoC.
An aspect of the present application is to provide a method that include the steps of receiving an profile information associated with an application by a Network-on-Chip (NoC), retrieving at least a characteristic, selected from any or combination of a bandwidth requirement, latency requirement, protocol requirement and transactions, associated with the application from the profile information, generating at least one application traffic graph having mapping information based on the characteristic retrieved, and mapping the application traffic graph generated with into the FPGA using the hardened NoC.
In an aspect, while the hardened NoC is deployed in the FPGA, reconfiguring the hardened NoC in accordance with the application traffic graph. In another aspect, reconfiguring the hardened NoC comprises receiving mapping information for one or more characteristic associated with the application and transmitting the mapping information to the hardened NoC.
In an aspect, the application traffic graph includes a plurality of nodes indicative of representations of traffic associated with the application, wherein the plurality of nodes interacts based on bandwidth requirements, latency requirements, protocol requirements and transactions retrieved.
In an aspect, the mapping information comprises transaction assignments of one or more traffic profiles to each NoC layer in the hardened NoC and route assignments for each NoC layer in the hardened NoC.
In an aspect, the hardened NoC further determines all allowed subsets of the plurality of application traffic profiles, and determine a NoC configuration that is configured to support the determined all allowed subsets. In another aspect, the NoC configuration is further includes one or more physical channels, one or more virtual channels, one or more NoC layers, Quality of Service (QoS) parameters for each of the one or more physical channels and the one or more virtual channels, and weights for each of the one or more physical channels and the one or more virtual channels.
In an aspect, the application traffic graph is received from a user. In another aspect, the application traffic graph is generated based on the traffic profile fed to the FPGA system. In yet another aspect, the application traffic graph is generated based on one or more meta-data associated with one or more packet received by the FPGA system.
In an aspect, the system is further configured to determine at least a part of application graph to be mapped with the hardened NoC and at least a part of application graph to be mapped with the soft logic.
In an aspect, the NoC includes a mechanism for being configured by software to modify one or more functions associated with the NoC. In another aspect, the one or more functions of the NoC are associated with any of combination quality of service (QoS), priority, virtual channel (VC) allocation, rate limits, buffer sizing, layer/physical channel assignment.
In an aspect, the NoC includes virtual channel (VC) and physical layers allocated based at least on quality of service (QoS), latency, bandwidth requirements, number of inputs/outputs (I/Os), memories, soft intellectual properties (IPs) that are connected to the NoC.
In an aspect, the NoC includes one or more bridges configured to support multiple protocols.
In an aspect, the NoC includes at least a programmable decoding element to determine any or combination of a route, a layer and destination information from one or more messages transported over the NoC.
An aspect of the present application relates to a non-transitory computer readable storage medium storing instructions for executing a process. The instructions include the steps of receiving an profile information associated with an application, retrieving at least a characteristic, selected from any or combination of a bandwidth requirement, latency requirement, protocol requirement and transactions, associated with the application from the profile information, generating at least one application traffic graph having mapping information based on the characteristic retrieved, and mapping the application traffic graph generated with into the FPGA using the hardened NoC.
The present application provides devices having a programmable fabric and a communication network integrated with the programmable fabric for high-speed data passing.
According to an example implementation, an FPGA incorporates one or more programmable NoCs or NoC components integrated within the FPGA fabric. In one example implementation, the NoC is used as system-level interconnect to connect computer and communication modules to one another and integrate large systems on the FPGA. The FPGA design flow is altered to target the NoC components either manually through designer intervention, or automatically. The computation and communication modules may be either constructed out of the FPGA's logic blocks block Random Access Memory (RAM) modules, multipliers, processor cores, input/output (I/O) controllers, I/O ports or any other computation or communication modules that can be found on FPGAs or heterogeneous devices based thereon.
The NoC or NoCs added to the FPGA involve routers and links, and optionally fabric ports. Routers refer to any circuitry that switches and optionally buffers data from one port to another. NoC routers may involve, but are not limited to, any of the following: crossbars, buffered crossbars, circuit-switched routers or packet-switched routers. Links are the connections between routers. In one example implementation NoC links are constructed out of the conventional FPGA interconnect which can involve different-length wire segments and multiplexers. In another example implementation, NoC links can involve dedicated metal wiring between two router ports. Both example implementations of the NoC links may include buffers or pipeline registers. The fabric port connects the NoC to the FPGA fabric and thus performs two key bridging functions. The first function of the fabric port is width adaptation between the computation or communication module and the NoC. In one example implementation, this is implemented as a multiplexer, a demultiplexer and a counter to perform time-domain multiplexing (TDM) and demultiplexing. The second function is clock-domain crossing; in one example implementation this is implemented as an asynchronous first-in first-out (FIFO) queue. Although the NoC targets digital electronic systems, all or parts of the presented NoC can be replaced using an optical network on chip. The NoC can also be implemented on a separate die in a 3D die stack.
Changes to the FPGA design flow to target NoCs may be divided into two categories; logical design and physical design. The logical design step concerns the functional design of the implemented system. In the logical design step all or part of the designed system is made latency-insensitive by adding wrappers to the modules. The logical design step also includes generating the required interfaces to connect modules to a NoC and programming the NoC for use. Programming the NoC includes, but is not limited to the following: configuring the routers, assigning priorities to data classes, assigning virtual channels to data classes and specifying the routes taken through the NoC. The physical design flow then implements the output of the logical design step on physical circuitry. It includes mapping computation and communication modules to NoC routers, and floor planning the mentioned modules onto the FPGA device. Together, these architecture and design flow changes due to the addition of NoCs to FPGAs will raise the level of abstraction of system-level communication, making design integration of large systems simpler and more automated and making system-level interconnect more efficient.
In an example implementation, a field-programmable gate array (FPGA) is an integrated circuit designed to be configured by a customer or a designer after manufacturing—hence “field-programmable”. The FPGA configuration is generally specified using a hardware description language (HDL), similar to that used for an application-specific integrated circuit (ASIC). (Circuit diagrams were previously used to specify the configuration, as they were for ASICs, but this is increasingly rare.)
FPGAs contain an array of programmable logic blocks, and a hierarchy of reconfigurable interconnects that allow the blocks to be “wired together”, like many logic gates that can be inter-wired in different configurations. Logic blocks can be configured to perform complex combinational functions, or logic gates such as AND, XOR, and so on. In most FPGAs, logic blocks also include memory elements, which may be simple flip-flops or more complete blocks of memory.
FPGA includes a Lookup table (LUT) having bunch of inputs and bunch of outputs, wherein both inputs and outputs are programmable. Basically, one can configure input and output to achieve a specific/desired functioning. For example, if 1 Bit adder logic is to be implemented then there are four different logics i.e., (0, 0), (0, 1), (1, 0), (1, 1) and four different outputs.
In an example implementation, the One-bit Full-Adder (FA) is used widely in systems with operations such as counter, addition, subtraction, multiplication and division etc. It is the basic core component of Arithmetic-Logic-Unit (ALU). Thus, the innovation and acceleration of FA means that the speed of the Central-Processor-Unit (CPU) and the speed of the whole system in general are accelerated. FA is a basic cell in the CPU and is so fundamental that changes to it are difficult to make. However, this cannot prevent researchers to try to increase the speed for FA.
In order to create one bit FA in the traditional methods, two's component gate must be used. This makes the circuit more complex, and when there is a subtraction of n bits, there should be an addition of n XOR gates. The FPGA device is becoming increasing popular, and the acceleration of the multiplexer and improvement in FPGA allow the configuration of the Look Up Table (LUT) in FPGA that functions as a memory or a logic functions. This especially allows the formation of many small LUT's inside a big LUT. New designs have the aim to increase the speed of FA based on LUT and Multiplexer.
Thus, FPGA works at the logic and tries to program the logic in the LUT by just exhaustively listing all the possible inputs and all the possible outputs. However, in a real system, there are many complex and many functionalities that need to be performed. Thus, multiple LUTs need to be internally connected to able to achieve multiple functions. However, to provide these connections in functionalities (programmable connections) there is a requirement of programmable set of wires.
For example, at FPGA there can be many LUTs (e.g., hundreds of millions) and can also involve plurality of wires, grids of wires and cross-points of wires that needs to be programmed and connected to work in sync with each other. Thus, there are needs for connecting multiple small logics together via, LUTs. Thus, the present invention provides a mechanism which enables to connect these FPGA's by way programming.
In an example implementation, as shown, LUT1 432 and LUT2 434 can be connected using programmable wires (cross-points) 436 to achieve connection to work in sync with each other.
460 illustrates a flow diagram for connecting LUTs using programmable wires as shown in
However, while connecting the LUTs and programmable wires, there is a need to determine how many size/pieces of the logic are to be made, as well as how many connections are needed. If the size/pieces are too large then the LUT mapping may not be possible. One of the biggest obstacles is that LUTs may be upgraded/programmed with high frequencies. However, the wires are normally not upgraded/programmed with high frequencies.
Thus, the LUT and wires implement soft logic since it is programmable and are provided with less transparency and low frequency.
Example implementations described herein facilitate communication, which is required in FPGA, by packetizing the communication and can be transported over a hardened network voucher that is present in FPGA along with the soft logic. The example implementations facilitate the achievement of hardened logic (non-re-programmable) based on the soft logic. Such implementations can achieve a benefit that it has much high frequency which is achieved by low latency and higher bandwidth for the same number of wires.
FPGAs are embedded/incorporated with NoCs wherein the NoCs give an ability to transfer packets from one point to other point.
Also, once the Hardened NoC is built over the FPGA there is a need for mapping the traffic incoming and outgoing to a particular layer or merchant channel of within layer routing their needs a flexibility to choose route for the traffic (since there are multiple routes present). The flow can have different requirements in terms of bandwidth or burstiness etc. Hardened NoC can have layer flexibility, VC flexibility, and route flexibility. Application Mapping indicates how these layers, VCs and routes used for a particular application efficiently and meeting all the requirements and constraints of the system.
Referring now to
In an example implementation, the inputs can be received by from Ethernet interface, Peripheral Component Interconnect (PCI) interface, Serializer/Deserializer (SerDes) interface, and the like.
In an example implementation, the input received can be in a particular specific protocol format having source and destination information which can directly routed to the destination without any alteration in the particular specific protocol format using a hardened network topology of the NoC. In another example implementation, the input received can be a particular specific protocol format having source but no destination information, cannot be directly routed to the destination but through using soft logic (cross-connection) and needs to be analyzed and then without any alteration in the particular specific protocol format routed to its destination.
In an example implementation, the packets coming in FPGA and going out are in the form of messages so they are suitable candidate over the hard NoC. The packets inside FPGA core assessing the memory can also be routed over the NoC.
In an example implementation, the present application allows the system to decide which packets are to be sent to NoC and which needs to be routed through FPGA. The packets which are in the form of messages and which has fixed source destination or rout to be followed can be routed through the NoC. More specifically, the messages which have specific details and destination are far away from each other passes through the NoC.
In an example implementation, in NoC there are bridges along with other sub-components. The bridges are used for receiving packets and convert the packet into NoC protocol format. Those bridges also have some cost for example in terms of area.
In an example implementation, a cost of a NoC is compared with the cost of a soft logic and if it is much greater than that of soft logic the NoC are not much beneficial.
In an example implementation, bridges in the NoC are provided to support certain protocols. The bridges included in the NoC can have 4 exemplary design choices. First exemplary design choice is a superset bridge that can support all the protocols however such bridge is excessively large and not cost effective. Second exemplary design choice is a bridge which can be built based on the requirements/compatibility. The soft logic in this type is aware about the placement of the bridges to satisfy the requirements of sufficiency of the bridges for communications. Third exemplary design choice is to not hardened at all but to have bridges that includes only soft logic. However, even if NoC is operating at higher frequency, the bridges may run at lower frequency. Fourth exemplary design choice for bridges is to divide bridges in protocol part and packet switching part so packet switching can be hardened and protocol part can be soft switching which may not give you ideal design but can provide a descent achievable performance.
In an example implementation, the topology for NoC depends on plurality of factors. Few of the exemplary factors can include but are not limited to types of applications that are being performed using the FPGA. For example, applications functionality can be examined to decide topology based on data/traffic flow for applications, message sizes, functions of the applications, distance of the applications etc.
600 illustrates an example flow diagram for the Field-Programmable Gate-Array (FPGA) system. The method at step 602 receives profile information associated with an application by a Network-on-Chip (NoC), at step 604 retrieves at least a characteristic, selected from any one or any combination of a bandwidth requirement, latency requirement, protocol requirement and transactions, associated with the application from the profile information, at step 606 generates at least one application traffic graph having mapping information based on the characteristic retrieved, and at step 608 maps the application traffic graph generated with into the FPGA using the hardened NoC.
In an aspect, while the hardened NoC is deployed in the FPGA, reconfiguring the hardened NoC in accordance with the application traffic graph. In another aspect, reconfiguring the hardened NoC comprises receiving mapping information for one or more characteristic associated with the application and transmitting the mapping information to the hardened NoC.
In an aspect, the application traffic graph includes a plurality of nodes indicative of representations of traffic associated with the application, wherein the plurality of nodes interacts based on bandwidth requirements, latency requirements, protocol requirements and transactions retrieved.
In an aspect, the mapping information comprises transaction assignments of one or more traffic profiles to each NoC layer in the hardened NoC and route assignments for each NoC layer in the hardened NoC.
In an aspect, the hardened NoC further determines all allowed subsets of the plurality of application traffic profiles, and determine a NoC configuration that is configured to support the determined all allowed subsets. In another aspect, the NoC configuration is further includes one or more physical channels, one or more virtual channels, one or more NoC layers, Quality of Service (QoS) parameters for each of the one or more physical channels and the one or more virtual channels, and weights for each of the one or more physical channels and the one or more virtual channels.
In an aspect, the application traffic graph is received from a user. In another aspect, the application traffic graph is generated based on the traffic profile fed to the FPGA system. In yet another aspect, the application traffic graph is generated based on one or more meta-data associated with one or more packet received by the FPGA system.
In an aspect, the method can further determine at least a part of application graph to be mapped with the hardened NoC and at least a part of application graph to be mapped with the soft logic.
In an aspect, the NoC includes a mechanism for being configured by software to modify one or more functions associated with the NoC. In another aspect, the one or more functions of the NoC are associated with any of combination quality of service (QoS), priority, virtual channel (VC) allocation, rate limits, buffer sizing, layer/physical channel assignment.
In an aspect, the NoC includes virtual channel (VC) and physical layers allocated based at least on quality of service (QoS), latency, bandwidth requirements, number of inputs/outputs (I/Os), memories, soft intellectual properties (IPs) that are connected to the NoC.
In an aspect, the NoC includes one or more bridges configured to support multiple protocols.
In an aspect, the NoC includes at least a programmable decoding element to determine any or combination of a route, a layer and destination information from one or more messages transported over the NoC.
In an aspect, computer system 700 includes a server 702 that may involve an I/O unit 714, storage 716, and a processor 704 operable to execute one or more units as known to one skilled in the art. The term “computer-readable medium” as used herein refers to any medium that participates in providing instructions to processor 704 for execution, which may come in the form of computer-readable storage mediums, such as, but not limited to optical disks, magnetic disks, read-only memories, random access memories, solid state devices and drives, or any other types of tangible media suitable for storing electronic information, or computer-readable signal mediums, which can include transitory media such as carrier waves. The I/O unit processes input from user interfaces 718 and operator interfaces 720 which may utilize input devices such as a keyboard, mouse, touch device, or verbal command.
The server 702 may also be connected to an external storage 722, which can contain removable storage such as a portable hard drive, optical media (CD or DVD), disk media or any other medium from which a computer can read executable code. The server may also be connected an output device 724, such as a display to output data and other information to a user, as well as request additional information from a user. The connections from the server 702 to the user interface 718, the operator interface 720, the external storage 722, and the output device 724 may via wireless protocols, such as the 802.11 standards, Bluetooth® or cellular protocols, or via physical transmission media, such as cables or fiber optics. The output device 724 may therefore further act as an input device for interacting with a user.
The processor 704 may execute one or more modules including includes a receiving module 706 receive an profile information associated with an application, a retrieving module 708 to retrieve at least a characteristic, selected form any of combination of any or combination of a bandwidth requirement, latency requirement, protocol requirement and transactions, associated with the application from the profile information, a generating module 710 to generate at least one application traffic graph having mapping information based on the characteristic retrieved, and a mapping module 712 to map the application traffic graph generated with into the FPGA using the hardened NoC.
In an aspect, while the hardened NoC is deployed in the FPGA, reconfiguring the hardened NoC in accordance with the application traffic graph. In another aspect, reconfiguring the hardened NoC comprises receiving mapping information for one or more characteristic associated with the application and transmitting the mapping information to the hardened NoC.
In an aspect, the application traffic graph includes a plurality of nodes indicative of representations of traffic associated with the application, wherein the plurality of nodes interacts based on bandwidth requirements, latency requirements, protocol requirements and transactions retrieved.
In an aspect, the mapping information comprises transaction assignments of one or more traffic profiles to each NoC layer in the hardened NoC and route assignments for each NoC layer in the hardened NoC.
In an aspect, the hardened NoC further determines all allowed subsets of the plurality of application traffic profiles, and determine a NoC configuration that is configured to support the determined all allowed subsets. In another aspect, the NoC configuration is further includes one or more physical channels, one or more virtual channels, one or more NoC layers, Quality of Service (QoS) parameters for each of the one or more physical channels and the one or more virtual channels, and weights for each of the one or more physical channels and the one or more virtual channels.
In an aspect, the application traffic graph is received from a user. In another aspect, the application traffic graph is generated based on the traffic profile fed to the FPGA system. In yet another aspect, the application traffic graph is generated based on one or more meta-data associated with one or more packet received by the FPGA system.
In an aspect, the system is further configured to determine at least a part of application graph to be mapped with the hardened NoC and at least a part of application graph to be mapped with the soft logic.
In an aspect, the NoC includes a mechanism for being configured by software to modify one or more functions associated with the NoC. In another aspect, the one or more functions of the NoC are associated with any of combination quality of service (QoS), priority, virtual channel (VC) allocation, rate limits, buffer sizing, layer/physical channel assignment.
In an aspect, the NoC includes virtual channel (VC) and physical layers allocated based at least on quality of service (QoS), latency, bandwidth requirements, number of inputs/outputs (I/Os), memories, soft intellectual properties (IPs) that are connected to the NoC.
In an aspect, the NoC includes one or more bridges configured to support multiple protocols.
In an aspect, the NoC includes at least a programmable decoding element to determine any or combination of a route, a layer and destination information from one or more messages transported over the NoC.
It may be appreciated that, the nodes of the application graph are floating since the positions of the nodes are not specified in FPGA all the time. For examples, cores are not frozen.
It may also be appreciated that, there is also a requirement of application load balancing in automated manner. Thus, the present application enables to decide mapping, however once mapping is decided, it is required to program those mapping in the IOs of the FPGA. Therefore there is requirement of hardware built in FPGA which is programmable so that the mapping can be performed when FPGA is deployed.
Unless specifically stated otherwise, as apparent from the discussion, it is appreciated that throughout the description, discussions utilizing terms such as “processing,” “computing,” “calculating,” “determining,” “displaying,” or the like, can include the actions and processes of a computer system or other information processing device that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system's memories or registers or other information storage, transmission or display devices.
Example implementations may also relate to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, or it may include one or more general-purpose computers selectively activated or reconfigured by one or more computer programs. Such computer programs may be stored in a computer readable medium, such as a computer-readable storage medium or a computer-readable signal medium. A computer-readable storage medium may involve tangible mediums such as, but not limited to optical disks, magnetic disks, read-only memories, random access memories, solid state devices and drives, or any other types of tangible or non-transitory media suitable for storing electronic information. A computer readable signal medium may include mediums such as carrier waves. The algorithms and displays presented herein are not inherently related to any particular computer or other apparatus. Computer programs can involve pure software implementations that involve instructions that perform the operations of the desired implementation.
Various general-purpose systems may be used with programs and modules in accordance with the examples herein, or it may prove convenient to construct a more specialized apparatus to perform desired method steps. In addition, the example implementations are not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the example implementations as described herein. The instructions of the programming language(s) may be executed by one or more processing devices, e.g., central processing units (CPUs), processors, or controllers.
As is known in the art, the operations described above can be performed by hardware, software, or some combination of software and hardware. Various aspects of the example implementations may be implemented using circuits and logic devices (hardware), while other aspects may be implemented using instructions stored on a machine-readable medium (software), which if executed by a processor, would cause the processor to perform a method to carry out implementations of the present application. Further, some example implementations of the present application may be performed solely in hardware, whereas other example implementations may be performed solely in software. Moreover, the various functions described can be performed in a single unit, or can be spread across a number of components in any number of ways. When performed by software, the methods may be executed by a processor, such as a general purpose computer, based on instructions stored on a computer-readable medium. If desired, the instructions can be stored on the medium in a compressed and/or encrypted format.
Moreover, other implementations of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the example implementations disclosed herein. Various aspects and/or components of the described example implementations may be used singly or in any combination. It is intended that the specification and examples be considered as examples, with a true scope and spirit of the application being indicated by the following claims.
This U.S. patent application is based on and claims the benefit of domestic priority under 35 U.S.C 119(e) from provisional U.S. patent application No. 62/634,587, filed on Feb. 23, 2018, the disclosure of which is hereby incorporated by reference herein in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
4409838 | Schomberg | Oct 1983 | A |
4933933 | Dally et al. | Jun 1990 | A |
5105424 | Flaig et al. | Apr 1992 | A |
5163016 | Har'El et al. | Nov 1992 | A |
5355455 | Hilgendorf et al. | Oct 1994 | A |
5432785 | Ahmed et al. | Jul 1995 | A |
5563003 | Suzuki et al. | Oct 1996 | A |
5583990 | Birrittella et al. | Dec 1996 | A |
5588152 | Dapp et al. | Dec 1996 | A |
5764740 | Holender | Jun 1998 | A |
5790554 | Pitcher et al. | Aug 1998 | A |
5859981 | Levin et al. | Jan 1999 | A |
5991308 | Fuhrmann et al. | Nov 1999 | A |
5999530 | LeMaire et al. | Dec 1999 | A |
6003029 | Agrawal et al. | Dec 1999 | A |
6029220 | Iwamura et al. | Feb 2000 | A |
6058385 | Koza et al. | May 2000 | A |
6101181 | Passint et al. | Aug 2000 | A |
6108739 | James et al. | Aug 2000 | A |
6249902 | Igusa et al. | Jun 2001 | B1 |
6314487 | Hahn et al. | Nov 2001 | B1 |
6377543 | Grover et al. | Apr 2002 | B1 |
6415282 | Mukherjea et al. | Jul 2002 | B1 |
6674720 | Passint et al. | Jan 2004 | B1 |
6701361 | Meier | Mar 2004 | B1 |
6711717 | Nystrom et al. | Mar 2004 | B2 |
6778531 | Kodialam et al. | Aug 2004 | B1 |
6925627 | Longway et al. | Aug 2005 | B1 |
6967926 | Williams, Jr. et al. | Nov 2005 | B1 |
6983461 | Hutchison et al. | Jan 2006 | B2 |
7046633 | Carvey | May 2006 | B2 |
7065730 | Alpert et al. | Jun 2006 | B2 |
7143221 | Bruce et al. | Nov 2006 | B2 |
7318214 | Prasad et al. | Jan 2008 | B1 |
7379424 | Krueger | May 2008 | B1 |
7437518 | Tsien | Oct 2008 | B2 |
7461236 | Wentzlaff | Dec 2008 | B1 |
7509619 | Miller et al. | Mar 2009 | B1 |
7564865 | Radulescu | Jul 2009 | B2 |
7583602 | Bejerano et al. | Sep 2009 | B2 |
7590959 | Tanaka | Sep 2009 | B2 |
7693064 | Thubert et al. | Apr 2010 | B2 |
7701252 | Chow et al. | Apr 2010 | B1 |
7724735 | Locatelli et al. | May 2010 | B2 |
7725859 | Lenahan et al. | May 2010 | B1 |
7774783 | Toader | Aug 2010 | B2 |
7808968 | Kalmanek, Jr. et al. | Oct 2010 | B1 |
7853774 | Wentzlaff | Dec 2010 | B1 |
7917885 | Becker | Mar 2011 | B2 |
7957381 | Clermidy et al. | Jun 2011 | B2 |
7973804 | Mejdrich et al. | Jul 2011 | B2 |
8018249 | Koch et al. | Sep 2011 | B2 |
8020163 | Nollet et al. | Sep 2011 | B2 |
8020168 | Hoover et al. | Sep 2011 | B2 |
8050256 | Bao et al. | Nov 2011 | B1 |
8059551 | Milliken | Nov 2011 | B2 |
8098677 | Pleshek et al. | Jan 2012 | B1 |
8099757 | Riedle et al. | Jan 2012 | B2 |
8136071 | Solomon | Mar 2012 | B2 |
8203938 | Gibbings | Jun 2012 | B2 |
8261025 | Mejdrich et al. | Sep 2012 | B2 |
8281297 | Dasu et al. | Oct 2012 | B2 |
8306042 | Abts | Nov 2012 | B1 |
8312402 | Okhmatovski et al. | Nov 2012 | B1 |
8352774 | Elrabaa | Jan 2013 | B2 |
8407425 | Gueron et al. | Mar 2013 | B2 |
8412795 | Mangano et al. | Apr 2013 | B2 |
8438578 | Hoover et al. | May 2013 | B2 |
8448102 | Kornachuk et al. | May 2013 | B2 |
8490110 | Hoover et al. | Jul 2013 | B2 |
8492886 | Or-Bach et al. | Jul 2013 | B2 |
8503445 | Lo | Aug 2013 | B2 |
8514889 | Jayasimha | Aug 2013 | B2 |
8541819 | Or-Bach et al. | Sep 2013 | B1 |
8543964 | Ge et al. | Sep 2013 | B2 |
8572353 | Bratt et al. | Oct 2013 | B1 |
8601423 | Philip et al. | Dec 2013 | B1 |
8614955 | Gintis et al. | Dec 2013 | B2 |
8619622 | Harrand et al. | Dec 2013 | B2 |
8635577 | Kazda et al. | Jan 2014 | B2 |
8661455 | Mejdrich et al. | Feb 2014 | B2 |
8667439 | Kumar et al. | Mar 2014 | B1 |
8705368 | Abts et al. | Apr 2014 | B1 |
8711867 | Guo et al. | Apr 2014 | B2 |
8717875 | Bejerano et al. | May 2014 | B2 |
8726295 | Hoover et al. | May 2014 | B2 |
8738860 | Griffin et al. | May 2014 | B1 |
8793644 | Michel et al. | Jul 2014 | B2 |
8798038 | Jayasimha et al. | Aug 2014 | B2 |
8819611 | Philip et al. | Aug 2014 | B2 |
8885510 | Kumar et al. | Nov 2014 | B2 |
9210048 | Marr et al. | Dec 2015 | B1 |
9223711 | Philip et al. | Dec 2015 | B2 |
9244845 | Rowlands et al. | Jan 2016 | B2 |
9244880 | Philip et al. | Jan 2016 | B2 |
9253085 | Kumar et al. | Feb 2016 | B2 |
9294354 | Kumar | Mar 2016 | B2 |
9319232 | Kumar | Apr 2016 | B2 |
9444702 | Raponi et al. | Sep 2016 | B1 |
9471726 | Kumar et al. | Oct 2016 | B2 |
9473359 | Kumar et al. | Oct 2016 | B2 |
9473388 | Kumar et al. | Oct 2016 | B2 |
9473415 | Kumar | Oct 2016 | B2 |
9477280 | Gangwar et al. | Oct 2016 | B1 |
9529400 | Kumar et al. | Dec 2016 | B1 |
9535848 | Rowlands et al. | Jan 2017 | B2 |
9568970 | Kaushal et al. | Feb 2017 | B1 |
9569579 | Kumar | Feb 2017 | B1 |
9571341 | Kumar et al. | Feb 2017 | B1 |
9571402 | Kumar et al. | Feb 2017 | B2 |
9571420 | Kumar | Feb 2017 | B2 |
9590813 | Kumar et al. | Mar 2017 | B1 |
9660942 | Kumar | May 2017 | B2 |
9699079 | Chopra et al. | Jul 2017 | B2 |
9742630 | Philip et al. | Aug 2017 | B2 |
20020071392 | Grover et al. | Jun 2002 | A1 |
20020073380 | Cooke et al. | Jun 2002 | A1 |
20020083159 | Ward et al. | Jun 2002 | A1 |
20020095430 | Egilsson et al. | Jul 2002 | A1 |
20020150094 | Cheng et al. | Oct 2002 | A1 |
20030005149 | Haas et al. | Jan 2003 | A1 |
20030088602 | Dutta et al. | May 2003 | A1 |
20030145314 | Nguyen et al. | Jul 2003 | A1 |
20030200315 | Goldenberg et al. | Oct 2003 | A1 |
20040006584 | Vandeweerd | Jan 2004 | A1 |
20040019814 | Pappalardo et al. | Jan 2004 | A1 |
20040049565 | Keller et al. | Mar 2004 | A1 |
20040103218 | Blumrich et al. | May 2004 | A1 |
20040156376 | Nakagawa | Aug 2004 | A1 |
20040156383 | Nakagawa et al. | Aug 2004 | A1 |
20040216072 | Alpert et al. | Oct 2004 | A1 |
20050147081 | Acharya et al. | Jul 2005 | A1 |
20050203988 | Nollet et al. | Sep 2005 | A1 |
20050228930 | Ning et al. | Oct 2005 | A1 |
20050286543 | Coppola et al. | Dec 2005 | A1 |
20060002303 | Bejerano et al. | Jan 2006 | A1 |
20060031615 | Bruce et al. | Feb 2006 | A1 |
20060053312 | Jones et al. | Mar 2006 | A1 |
20060075169 | Harris et al. | Apr 2006 | A1 |
20060104274 | Caviglia et al. | May 2006 | A1 |
20060161875 | Rhee | Jul 2006 | A1 |
20060206297 | Ishiyama et al. | Sep 2006 | A1 |
20060209846 | Clermidy et al. | Sep 2006 | A1 |
20060268909 | Langevin et al. | Nov 2006 | A1 |
20070038987 | Ohara et al. | Feb 2007 | A1 |
20070088537 | Lertora et al. | Apr 2007 | A1 |
20070118320 | Luo et al. | May 2007 | A1 |
20070147379 | Lee et al. | Jun 2007 | A1 |
20070162903 | Babb, II et al. | Jul 2007 | A1 |
20070189283 | Agarwal et al. | Aug 2007 | A1 |
20070244676 | Shang et al. | Oct 2007 | A1 |
20070256044 | Coryer et al. | Nov 2007 | A1 |
20070267680 | Uchino et al. | Nov 2007 | A1 |
20070274331 | Locatelli et al. | Nov 2007 | A1 |
20080072182 | He et al. | Mar 2008 | A1 |
20080120129 | Seubert et al. | May 2008 | A1 |
20080126569 | Rhim et al. | May 2008 | A1 |
20080127014 | Pandey et al. | May 2008 | A1 |
20080184259 | Lesartre et al. | Jul 2008 | A1 |
20080186998 | Rijpkema | Aug 2008 | A1 |
20080211538 | Lajolo et al. | Sep 2008 | A1 |
20080232387 | Rijpkema et al. | Sep 2008 | A1 |
20090037888 | Tatsuoka et al. | Feb 2009 | A1 |
20090046727 | Towles | Feb 2009 | A1 |
20090067331 | Watsen et al. | Mar 2009 | A1 |
20090067348 | Vasseur et al. | Mar 2009 | A1 |
20090070726 | Mehrotra et al. | Mar 2009 | A1 |
20090083263 | Felch et al. | Mar 2009 | A1 |
20090089725 | Khan | Apr 2009 | A1 |
20090109996 | Hoover et al. | Apr 2009 | A1 |
20090122703 | Gangwal et al. | May 2009 | A1 |
20090125574 | Mejdrich et al. | May 2009 | A1 |
20090125703 | Mejdrich et al. | May 2009 | A1 |
20090125706 | Hoover et al. | May 2009 | A1 |
20090135739 | Hoover et al. | May 2009 | A1 |
20090138567 | Hoover et al. | May 2009 | A1 |
20090150647 | Mejdrich et al. | Jun 2009 | A1 |
20090157976 | Comparan et al. | Jun 2009 | A1 |
20090172304 | Gueron et al. | Jul 2009 | A1 |
20090182944 | Comparan et al. | Jul 2009 | A1 |
20090182954 | Mejdrich et al. | Jul 2009 | A1 |
20090182986 | Schwinn et al. | Jul 2009 | A1 |
20090182987 | Mejdrich et al. | Jul 2009 | A1 |
20090187716 | Comparan et al. | Jul 2009 | A1 |
20090187734 | Mejdrich et al. | Jul 2009 | A1 |
20090187756 | Nollet et al. | Jul 2009 | A1 |
20090201302 | Hoover et al. | Aug 2009 | A1 |
20090210184 | Medardoni et al. | Aug 2009 | A1 |
20090210883 | Hoover et al. | Aug 2009 | A1 |
20090228681 | Mejdrich et al. | Sep 2009 | A1 |
20090228682 | Mejdrich et al. | Sep 2009 | A1 |
20090228689 | Muff et al. | Sep 2009 | A1 |
20090228690 | Muff et al. | Sep 2009 | A1 |
20090231348 | Mejdrich et al. | Sep 2009 | A1 |
20090231349 | Mejdrich et al. | Sep 2009 | A1 |
20090240920 | Muff et al. | Sep 2009 | A1 |
20090245257 | Comparan et al. | Oct 2009 | A1 |
20090256836 | Fowler et al. | Oct 2009 | A1 |
20090260013 | Heil et al. | Oct 2009 | A1 |
20090268677 | Chou et al. | Oct 2009 | A1 |
20090271172 | Mejdrich et al. | Oct 2009 | A1 |
20090276572 | Heil et al. | Nov 2009 | A1 |
20090282139 | Mejdrich et al. | Nov 2009 | A1 |
20090282197 | Comparan et al. | Nov 2009 | A1 |
20090282211 | Hoover et al. | Nov 2009 | A1 |
20090282214 | Kuesel et al. | Nov 2009 | A1 |
20090282221 | Heil et al. | Nov 2009 | A1 |
20090282222 | Hoover et al. | Nov 2009 | A1 |
20090282226 | Hoover et al. | Nov 2009 | A1 |
20090282227 | Hoover et al. | Nov 2009 | A1 |
20090282419 | Mejdrich et al. | Nov 2009 | A1 |
20090285222 | Hoover et al. | Nov 2009 | A1 |
20090287885 | Kriegel et al. | Nov 2009 | A1 |
20090292907 | Schwinn et al. | Nov 2009 | A1 |
20090293061 | Schwinn et al. | Nov 2009 | A1 |
20090300292 | Fang | Dec 2009 | A1 |
20090300335 | Muff et al. | Dec 2009 | A1 |
20090307714 | Hoover et al. | Dec 2009 | A1 |
20090313592 | Murali et al. | Dec 2009 | A1 |
20090315908 | Comparan et al. | Dec 2009 | A1 |
20100023568 | Hickey et al. | Jan 2010 | A1 |
20100031009 | Muff et al. | Feb 2010 | A1 |
20100040162 | Suehiro | Feb 2010 | A1 |
20100042812 | Hickey et al. | Feb 2010 | A1 |
20100042813 | Hickey et al. | Feb 2010 | A1 |
20100070714 | Hoover et al. | Mar 2010 | A1 |
20100091787 | Muff et al. | Apr 2010 | A1 |
20100100707 | Mejdrich et al. | Apr 2010 | A1 |
20100100712 | Mejdrich et al. | Apr 2010 | A1 |
20100100770 | Mejdrich et al. | Apr 2010 | A1 |
20100100934 | Mejdrich et al. | Apr 2010 | A1 |
20100106940 | Muff et al. | Apr 2010 | A1 |
20100125722 | Hickey et al. | May 2010 | A1 |
20100158005 | Mukhopadhyay et al. | Jun 2010 | A1 |
20100162019 | Kumar et al. | Jun 2010 | A1 |
20100189111 | Muff et al. | Jul 2010 | A1 |
20100191940 | Mejdrich et al. | Jul 2010 | A1 |
20100211718 | Gratz et al. | Aug 2010 | A1 |
20100223505 | Andreev et al. | Sep 2010 | A1 |
20100228781 | Fowler et al. | Sep 2010 | A1 |
20100239185 | Fowler et al. | Sep 2010 | A1 |
20100239186 | Fowler et al. | Sep 2010 | A1 |
20100242003 | Kwok | Sep 2010 | A1 |
20100269123 | Mejdrich et al. | Oct 2010 | A1 |
20100284309 | Allan et al. | Nov 2010 | A1 |
20100333099 | Kupferschmidt et al. | Dec 2010 | A1 |
20110022754 | Cidon et al. | Jan 2011 | A1 |
20110035523 | Feero et al. | Feb 2011 | A1 |
20110044336 | Umeshima | Feb 2011 | A1 |
20110060831 | Ishii et al. | Mar 2011 | A1 |
20110063285 | Hoover et al. | Mar 2011 | A1 |
20110064077 | Wen | Mar 2011 | A1 |
20110072407 | Keinert et al. | Mar 2011 | A1 |
20110085550 | Lecler et al. | Apr 2011 | A1 |
20110085561 | Ahn et al. | Apr 2011 | A1 |
20110103799 | Shacham et al. | May 2011 | A1 |
20110119322 | Li et al. | May 2011 | A1 |
20110154282 | Chang et al. | Jun 2011 | A1 |
20110173258 | Arimilli et al. | Jul 2011 | A1 |
20110191088 | Hsu et al. | Aug 2011 | A1 |
20110191774 | Hsu et al. | Aug 2011 | A1 |
20110235531 | Vangal et al. | Sep 2011 | A1 |
20110243147 | Paul | Oct 2011 | A1 |
20110276937 | Waller | Nov 2011 | A1 |
20110289485 | Mejdrich et al. | Nov 2011 | A1 |
20110292063 | Mejdrich et al. | Dec 2011 | A1 |
20110302345 | Boucard et al. | Dec 2011 | A1 |
20110302450 | Hickey et al. | Dec 2011 | A1 |
20110307734 | Boesen et al. | Dec 2011 | A1 |
20110316864 | Mejdrich et al. | Dec 2011 | A1 |
20110320719 | Mejdrich et al. | Dec 2011 | A1 |
20110320724 | Mejdrich et al. | Dec 2011 | A1 |
20110320771 | Mejdrich et al. | Dec 2011 | A1 |
20110320854 | Elrabaa | Dec 2011 | A1 |
20110320991 | Hsu et al. | Dec 2011 | A1 |
20110321057 | Mejdrich et al. | Dec 2011 | A1 |
20120022841 | Appleyard | Jan 2012 | A1 |
20120023473 | Brown et al. | Jan 2012 | A1 |
20120026917 | Guo et al. | Feb 2012 | A1 |
20120054511 | Brinks et al. | Mar 2012 | A1 |
20120072635 | Yoshida et al. | Mar 2012 | A1 |
20120079147 | Ishii et al. | Mar 2012 | A1 |
20120099475 | Tokuoka | Apr 2012 | A1 |
20120110106 | De Lescure et al. | May 2012 | A1 |
20120110541 | Ge et al. | May 2012 | A1 |
20120144065 | Parker et al. | Jun 2012 | A1 |
20120155250 | Carney et al. | Jun 2012 | A1 |
20120173846 | Wang et al. | Jul 2012 | A1 |
20120176364 | Schardt et al. | Jul 2012 | A1 |
20120195321 | Ramanujam et al. | Aug 2012 | A1 |
20120198408 | Chopra | Aug 2012 | A1 |
20120209944 | Mejdrich et al. | Aug 2012 | A1 |
20120218998 | Sarikaya | Aug 2012 | A1 |
20120221711 | Kuesel et al. | Aug 2012 | A1 |
20120260252 | Kuesel et al. | Oct 2012 | A1 |
20120311512 | Michel et al. | Dec 2012 | A1 |
20130021896 | Pu et al. | Jan 2013 | A1 |
20130028083 | Yoshida et al. | Jan 2013 | A1 |
20130028090 | Yamaguchi et al. | Jan 2013 | A1 |
20130028261 | Lee | Jan 2013 | A1 |
20130036296 | Hickey et al. | Feb 2013 | A1 |
20130044117 | Mejdrich et al. | Feb 2013 | A1 |
20130046518 | Mejdrich et al. | Feb 2013 | A1 |
20130051397 | Guo et al. | Feb 2013 | A1 |
20130054811 | Harrand | Feb 2013 | A1 |
20130073771 | Hanyu et al. | Mar 2013 | A1 |
20130073878 | Jayasimha et al. | Mar 2013 | A1 |
20130080073 | de Corral | Mar 2013 | A1 |
20130080671 | Ishii et al. | Mar 2013 | A1 |
20130086399 | Tychon et al. | Apr 2013 | A1 |
20130103369 | Huynh et al. | Apr 2013 | A1 |
20130103912 | Jones et al. | Apr 2013 | A1 |
20130111190 | Muff et al. | May 2013 | A1 |
20130111242 | Heller et al. | May 2013 | A1 |
20130117543 | Venkataramanan et al. | May 2013 | A1 |
20130138925 | Hickey et al. | May 2013 | A1 |
20130145128 | Schardt et al. | Jun 2013 | A1 |
20130148506 | Lea | Jun 2013 | A1 |
20130151215 | Mustapha | Jun 2013 | A1 |
20130159668 | Muff et al. | Jun 2013 | A1 |
20130159669 | Comparan et al. | Jun 2013 | A1 |
20130159674 | Muff et al. | Jun 2013 | A1 |
20130159675 | Muff et al. | Jun 2013 | A1 |
20130159676 | Muff et al. | Jun 2013 | A1 |
20130159944 | Uno et al. | Jun 2013 | A1 |
20130160026 | Kuesel et al. | Jun 2013 | A1 |
20130160114 | Greenwood et al. | Jun 2013 | A1 |
20130163615 | Mangano et al. | Jun 2013 | A1 |
20130174113 | Lecler et al. | Jul 2013 | A1 |
20130179613 | Boucard et al. | Jul 2013 | A1 |
20130179902 | Hoover et al. | Jul 2013 | A1 |
20130185542 | Mejdrich et al. | Jul 2013 | A1 |
20130191572 | Nooney et al. | Jul 2013 | A1 |
20130191600 | Kuesel et al. | Jul 2013 | A1 |
20130191649 | Muff et al. | Jul 2013 | A1 |
20130191651 | Muff et al. | Jul 2013 | A1 |
20130191824 | Muff et al. | Jul 2013 | A1 |
20130191825 | Muff et al. | Jul 2013 | A1 |
20130207801 | Barnes | Aug 2013 | A1 |
20130219148 | Chen et al. | Aug 2013 | A1 |
20130250792 | Yoshida et al. | Sep 2013 | A1 |
20130254488 | Kaxiras et al. | Sep 2013 | A1 |
20130263068 | Cho et al. | Oct 2013 | A1 |
20130268990 | Urzi et al. | Oct 2013 | A1 |
20130294458 | Yamaguchi et al. | Nov 2013 | A1 |
20130305207 | Hsieh et al. | Nov 2013 | A1 |
20130311819 | Ishii et al. | Nov 2013 | A1 |
20130326458 | Kazda et al. | Dec 2013 | A1 |
20140013293 | Hsu et al. | Jan 2014 | A1 |
20140068132 | Philip et al. | Mar 2014 | A1 |
20140068134 | Philip et al. | Mar 2014 | A1 |
20140082237 | Wertheimer et al. | Mar 2014 | A1 |
20140086260 | Dai et al. | Mar 2014 | A1 |
20140092740 | Wang et al. | Apr 2014 | A1 |
20140098683 | Kumar et al. | Apr 2014 | A1 |
20140112149 | Urzi et al. | Apr 2014 | A1 |
20140115218 | Philip et al. | Apr 2014 | A1 |
20140115298 | Philip et al. | Apr 2014 | A1 |
20140126572 | Hutton et al. | May 2014 | A1 |
20140143557 | Kuesel et al. | May 2014 | A1 |
20140143558 | Kuesel et al. | May 2014 | A1 |
20140149720 | Muff et al. | May 2014 | A1 |
20140164465 | Muff et al. | Jun 2014 | A1 |
20140164704 | Kuesel et al. | Jun 2014 | A1 |
20140164732 | Muff et al. | Jun 2014 | A1 |
20140164734 | Muff et al. | Jun 2014 | A1 |
20140211622 | Kumar et al. | Jul 2014 | A1 |
20140229709 | Kuesel et al. | Aug 2014 | A1 |
20140229712 | Muff et al. | Aug 2014 | A1 |
20140229713 | Muff et al. | Aug 2014 | A1 |
20140229714 | Muff et al. | Aug 2014 | A1 |
20140229720 | Hickey et al. | Aug 2014 | A1 |
20140230077 | Muff et al. | Aug 2014 | A1 |
20140232188 | Cheriyan et al. | Aug 2014 | A1 |
20140241376 | Balkan et al. | Aug 2014 | A1 |
20140254388 | Kumar et al. | Sep 2014 | A1 |
20140281243 | Shalf et al. | Sep 2014 | A1 |
20140281402 | Comparan et al. | Sep 2014 | A1 |
20140307590 | Dobbelaere et al. | Oct 2014 | A1 |
20140359641 | Clark et al. | Dec 2014 | A1 |
20140376569 | Philip et al. | Dec 2014 | A1 |
20150020078 | Kuesel et al. | Jan 2015 | A1 |
20150026435 | Muff et al. | Jan 2015 | A1 |
20150026494 | Bainbridge et al. | Jan 2015 | A1 |
20150026500 | Muff et al. | Jan 2015 | A1 |
20150032988 | Muff et al. | Jan 2015 | A1 |
20150032999 | Muff et al. | Jan 2015 | A1 |
20150043575 | Kumar et al. | Feb 2015 | A1 |
20150081941 | Brown et al. | Mar 2015 | A1 |
20150103822 | Gianchandani et al. | Apr 2015 | A1 |
20150109024 | Abdelfattah et al. | Apr 2015 | A1 |
20150159330 | Weisman et al. | Jun 2015 | A1 |
20150178435 | Kumar | Jun 2015 | A1 |
20150331831 | Solihin | Nov 2015 | A1 |
20150348600 | Bhatia et al. | Dec 2015 | A1 |
20150381707 | How | Dec 2015 | A1 |
20160344629 | Gray | Nov 2016 | A1 |
20170061053 | Kumar et al. | Mar 2017 | A1 |
20170063625 | Philip et al. | Mar 2017 | A1 |
20170063697 | Kumar | Mar 2017 | A1 |
Number | Date | Country |
---|---|---|
103684961 | Mar 2014 | CN |
5936793 | May 2016 | JP |
6060316 | Jan 2017 | JP |
6093867 | Feb 2017 | JP |
10-2013-0033898 | Apr 2013 | KR |
101652490 | Aug 2016 | KR |
101707655 | Feb 2017 | KR |
2010074872 | Jul 2010 | WO |
2013063484 | May 2013 | WO |
2014059024 | Apr 2014 | WO |
Entry |
---|
Ababei, C., et al., Achieving Network on Chip Fault Tolerance by Adaptive Remapping, Parallel & Distributed Processing, 2009, IEEE International Symposium, 4 pgs. |
Abts, D., et al., Age-Based Packet Arbitration in Large-Radix k-ary n-cubes, Supercomputing 2007 (SC07), Nov. 10-16, 2007, 11 pgs. |
Beretta, I, et al., A Mapping Flow for Dynamically Reconfigurable Multi-Core System-on-Chip Design, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Aug. 2011, 30(8), pp. 1211-1224. |
Das, R., et al., Aergia: Exploiting Packet Latency Slack in On-Chip Networks, 37th International Symposium on Computer Architecture (ISCA '10), Jun. 19-23, 2010, 11 pgs. |
Ebrahimi, E., et al., Fairness via Source Throttling: A Configurable and High-Performance Fairness Substrate for Multi-Core Memory Systems, ASPLOS '10, Mar. 13-17, 2010, 12 pgs. |
Gindin, R., et al., NoC-Based FPGA: Architecture and Routing, Proceedings of the First International Symposium on Networks-on-Chip (NOCS'07), May 2007, pp. 253-262. |
Grot, B., Preemptive Virtual Clock: A Flexible, Efficient, and Cost-Effective QOS Scheme for Networks-on-Chip, Micro '09, Dec. 16, 2009, 12 pgs. |
Grot, B., Kilo-NOC: A Heterogeneous Network-on-Chip Architecture for Scalability and Service Guarantees, ISCA 11, Jun. 4-8, 2011, 12 pgs. |
Grot, B., Topology-Aware Quality-of-Service Support in Highly Integrated Chip Multiprocessors, 6th Annual Workshop on the Interaction between Operating Systems and Computer Architecture, Jun. 2006, 11 pgs. |
Hestness, J., et al., Netrace: Dependency-Tracking for Efficient Network-on-Chip Experimentation, The University of Texas at Austin, Dept. of Computer Science, May 2011, 20 pgs. |
Jiang, N., et al., Performance Implications of Age-Based Allocations in On-Chip Networks, CVA MEMO 129, May 24, 2011, 21 pgs. |
Lee, J. W., et al., Globally-Synchronized Frames for Guaranteed Quality-of-Service in On-Chip Networks, 35th IEEE/ACM International Symposium on Computer Architecture (ISCA), Jun. 2008, 12 pgs. |
Lee, M. M., et al., Approximating Age-Based Arbitration in On-Chip Networks, PACT '10, Sep. 11-15, 2010, 2 pgs. |
Li, B., et al., CoQoS: Coordinating QoS-Aware Shared Resources in NoC-based SoCs, J. Parallel Distrib. Comput., 71(5), May 2011, 14 pgs. |
Lin, S., et al., Scalable Connection-Based Flow Control Scheme for Application-Specific Network-on-Chip, The Journal of China Universities of Posts and Telecommunications, Dec. 2011, 18(6), pp. 98-105. |
Bolotin, Evgency, et al., “QNoC: QoS Architecture and Design Process for Network on Chip” 2004, 24 pages, Journal of Systems Architecture 50 (2004) 105-128 Elsevier. |
Holsmark, Shashi Kumar Rickard, et al., “HiRA: A Methodology for Deadlock Free Routing in Hierarchical Networks on Chip”, 10 pages, (978-1-4244-4143-3/09 2009 IEEE). |
Munirul, H.M., et al., Evaluation of Multiple-Valued Packet Multiplexing Scheme for Network-on-Chip Architecture, Proceedings of the 36th International Symposium on Multiple-Valued Logic (ISMVL '06), 2006, 6 pgs. |
Rajesh BV, Shivaputra, “NOC: Design and Implementation of Hardware Network Interface With Improved Communication Reliability”, 7 pages, International Journal of VLSI and Embedded Systems, Ijives (vol. 04, Article 06116; Jun. 2013). |
Yang, J., et al., Homogeneous NoC-based FPGA: The Foundation for Virtual FPGA, 10th IEEE International Conference on Computer and Information Technology (CIT 2010), Jun. 2010, pp. 62-67. |
Zaman, Aanam, “Formal Verification of Circuit-Switched Network on Chip (NoC) Architectures using SPIN”, Oosman Hasan, IEEE © 2014, 8 pages. |
Benini, Luca, et al., “Networks on Chips: A New SoC Paradigm”, IEEE Computers, SOC Designs, pp. 70-78, Copyright 2002 IEEE. 0018-9162/02. |
Sethuraman, Ranga Vemuri Balasubramanian, “optiMap: A Tool for Automated Generation of NoC Architecture Using Multi-Port Routers for FPGAs”, IEEE, pp. 1-6, 2006. |
International Search Report and Written Opinion for PCT/US2014/060745, dated Jan. 21, 2015, 10 pgs. |
International Search Report and Written Opinion for PCT/US2014/060879, dated Jan. 21, 2015, 10 pgs. |
International Search Report and Written Opinion for PCT/US2014/060892, dated Jan. 27, 2015, 10 pgs. |
International Search Report and Written Opinion for PCT/US2014/060886, dated Jan. 26, 2015, 10 pgs. |
International Search Report and Written Opinion for PCT/US2013/064140, dated Jan. 22, 2014, 9 pgs. |
International Search Report and Written Opinion for PCT/US2014/012003, dated Mar. 26, 2014, 9 pgs. |
International Search Report and Written Opinion for PCT/US2014/012012, dated May 14, 2014, 9 pgs. |
International Search Report and Written Opinion for PCT/US2014/023625, dated Jul. 10, 2014, 9 pgs. |
International Preliminary Report on Patentability for International Application No. PCT/US2013/064140, dated Apr. 14, 2015, 5 pages. |
Office Action for Korean Patent Application No. 10-2016-7019093 dated Sep. 8, 2016, 3 pages plus 1 page English translation. KIPO, Korea. |
Notice of Allowance for for Korean Patent Application No. 10-2016-7019093 dated Sep. 8, 2016, 4 pages. KIPO, Korea. |
International Search Report and Written Opinion for PCT/US2014/037902, dated Sep. 30, 2014, 14 pgs. |
Office Action for Japanese Patent Application No. 2015-535898 dated Oct. 25, 2016, 2 pages English, 2 pages untranslated copy. Japan Patent Office. |
Notice of Grant for Japanese Patent Application No. 2015-535898 dated Jan. 17, 2017, 3 pages, untranslated. Japan Patent Office. |
International Search Report and Written Opinion for PCT/US2014/048190, dated Nov. 28, 2014, 11 pgs. |
Office Action for Japanese Patent Application No. 2016-516030 dated Aug. 30, 2016, 2 pages, Japan Patent Office. |
Decision to Grant for Japanese Patent Application No. 2016-516030 dated Nov. 22, 2016, 6 pages, untranslated, Japan Patent Office. |
Number | Date | Country | |
---|---|---|---|
20190266089 A1 | Aug 2019 | US |
Number | Date | Country | |
---|---|---|---|
62634587 | Feb 2018 | US |