Addressable non-volatile random access memory

Information

  • Patent Grant
  • 11079962
  • Patent Number
    11,079,962
  • Date Filed
    Friday, February 21, 2020
    4 years ago
  • Date Issued
    Tuesday, August 3, 2021
    3 years ago
Abstract
A non-volatile solid-state storage is provided. The non-volatile solid state storage includes a non-volatile random access memory (NVRAM) addressable by a processor external to the non-volatile solid state storage. The NVRAM is configured to store user data and metadata relating to the user data. The non-volatile solid state storage includes a flash memory addressable by the processor. The flash memory is configured to store the user data responsive to the processor directing transfer of the user data from the NVRAM to the flash memory.
Description
BACKGROUND

Solid-state memory, such as flash, is currently in use in solid-state drives (SSD) to augment or replace conventional hard disk drives (HDD), writable CD (compact disk) or writable DVD (digital versatile disk) drives, collectively known as spinning media, and tape drives, for storage of large amounts of data. Flash and other solid-state memories have characteristics that differ from spinning media. Yet, many solid-state drives are designed to conform to hard disk drive standards for compatibility reasons, which makes it difficult to provide enhanced features or take advantage of unique aspects of flash and other solid-state memory.


It is within this context that the embodiments arise.


SUMMARY

In some embodiments a non-volatile solid-state storage is provided. The non-volatile solid state storage includes a non-volatile random access memory (NVRAM) addressable by a processor external to the non-volatile solid state storage. The NVRAM is configured to store user data and metadata relating to the user data. The non-volatile solid state storage includes a flash memory addressable by the processor. The flash memory is configured to store the user data responsive to the processor directing transfer of the user data from the NVRAM to the flash memory.


Other aspects and advantages of the embodiments will become apparent from the following detailed description taken in conjunction with the accompanying drawings which illustrate, by way of example, the principles of the described embodiments.





BRIEF DESCRIPTION OF THE DRAWINGS

The described embodiments and the advantages thereof may best be understood by reference to the following description taken in conjunction with the accompanying drawings. These drawings in no way limit any changes in form and detail that may be made to the described embodiments by one skilled in the art without departing from the spirit and scope of the described embodiments.



FIG. 1 is a perspective view of a storage cluster with multiple storage nodes and internal storage coupled to each storage node to provide network attached storage, in accordance with some embodiments.



FIG. 2 is a system diagram of an enterprise computing system, which can use one or more of the storage clusters of FIG. 1 as a storage resource in some embodiments.



FIG. 3 is a multiple level block diagram, showing contents of a storage node and contents of one of the non-volatile solid-state storages in accordance with some embodiments.



FIG. 4 is a block diagram showing a communication path for redundant copies of metadata, with further details of storage nodes and solid-state storages in accordance with some embodiments.



FIG. 5 is a flow diagram of a method for accessing a non-volatile solid-state storage, which can be practiced on or by embodiments of storage clusters, storage nodes and/or non-volatile solid-state storage units in accordance with some embodiments.



FIG. 6 is an illustration showing an exemplary computing device which may implement the embodiments described herein.





DETAILED DESCRIPTION

The embodiments below describe a storage cluster that stores user data, such as user data originating from one or more user or client systems or other sources external to the storage cluster. The storage cluster distributes user data across storage nodes housed within a chassis, using erasure coding and redundant copies of metadata. Erasure coding refers to a method of data protection in which data is broken into fragments, expanded and encoded with redundant data pieces and stored across a set of different locations, such as disks, storage nodes or geographic locations. Flash memory is one type of solid-state memory that may be integrated with the embodiments, although the embodiments may be extended to other types of solid-state memory or other storage medium, including non-solid state memory. Control of storage locations and workloads are distributed across the storage locations in a clustered peer-to-peer system. Tasks such as mediating communications between the various storage nodes, detecting when a storage node has become unavailable, and balancing I/Os (inputs and outputs) across the various storage nodes, are all handled on a distributed basis. Data is laid out or distributed across multiple storage nodes in data fragments or stripes that support data recovery in some embodiments. Ownership of data can be reassigned within a cluster, independent of input and output patterns. This architecture described in more detail below allows a storage node in the cluster to fail, with the system remaining operational, since the data can be reconstructed from other storage nodes and thus remain available for input and output operations. In various embodiments, a storage node may be referred to as a cluster node, a blade, or a server.


The storage cluster is contained within a chassis, i.e., an enclosure housing one or more storage nodes. A mechanism to provide power to each storage node, such as a power distribution bus, and a communication mechanism, such as a communication bus that enables communication between the storage nodes are included within the chassis. The storage cluster can run as an independent system in one location according to some embodiments. In one embodiment, a chassis contains at least two instances of the power distribution and the internal and external communication bus which may be enabled or disabled independently. The internal communication bus may be an Ethernet bus, however, other technologies such as Peripheral Component Interconnect (PCI) Express, InfiniBand, and others, are equally suitable. The chassis provides a port for an external communication bus for enabling communication between multiple chassis, directly or through a switch, and with client systems. The external communication may use a technology such as Ethernet, InfiniBand, Fibre Channel, etc. In some embodiments, the external communication bus uses different communication bus technologies for inter-chassis and client communication. If a switch is deployed within or between chassis, the switch may act as a translation between multiple protocols or technologies. When multiple chassis are connected to define a storage cluster, the storage cluster may be accessed by a client using either proprietary interfaces or standard interfaces such as network file system (NFS), common internet file system (CIFS), small computer system interface (SCSI) or hypertext transfer protocol (HTTP). Translation from the client protocol may occur at the switch, chassis external communication bus or within each storage node.


Each storage node may be one or more storage servers and each storage server is connected to one or more non-volatile solid state memory units, which may be referred to as storage units. One embodiment includes a single storage server in each storage node and between one to eight non-volatile solid state memory units, however this one example is not meant to be limiting. The storage server may include a processor, dynamic random access memory (DRAM) and interfaces for the internal communication bus and power distribution for each of the power buses. Inside the storage node, the interfaces and storage unit share a communication bus, e.g., PCI Express, in some embodiments. The non-volatile solid state memory units may directly access the internal communication bus interface through a storage node communication bus, or request the storage node to access the bus interface. The non-volatile solid state memory unit contains an embedded central processing unit (CPU), solid state storage controller, and a quantity of solid state mass storage, e.g., between 2-32 terabytes (TB) in some embodiments. An embedded volatile storage medium, such as DRAM, and an energy reserve apparatus are included in the non-volatile solid state memory unit. In some embodiments, the energy reserve apparatus is a capacitor, super-capacitor, or battery that enables transferring a subset of DRAM contents to a stable storage medium in the case of power loss. In some embodiments, the non-volatile solid state memory unit is constructed with a storage class memory, such as phase change or other resistive random access memory (RRAM) or magnetoresistive random access memory (MRAM) that substitutes for DRAM and enables a reduced power hold-up apparatus.


The storage nodes have one or more non-volatile solid-state storage units, each of which has non-volatile random-access memory (NVRAM) and flash memory, in some embodiments. The NVRAM and the flash memory are independently addressable by the storage node, or more specifically, by a processor of the storage node. The storage node writes user data into the NVRAM, for storage in the flash memory. The storage node, e.g., the processor of the storage node, also writes metadata into the NVRAM, which is usable as a workspace for the processor. Direct memory access (DMA) is applied to transfer user data from the NVRAM to the flash memory, for storage of the user data. DMA is also applied to transfer contents of the NVRAM to the flash memory in case of power loss. In some embodiments, a controller in the non-volatile solid-state storage manages a mapping or translation table and performs various duties to manage the user data in the flash memory.



FIG. 1 is a perspective view of a storage cluster 160, with multiple storage nodes 150 and internal solid-state memory coupled to each storage node to provide network attached storage or storage area network, in accordance with some embodiments. A network attached storage, storage area network, or a storage cluster, or other storage memory, could include one or more storage clusters 160, each having one or more storage nodes 150, in a flexible and reconfigurable arrangement of both the physical components and the amount of storage memory provided thereby. The storage cluster 160 is designed to fit in a rack, and one or more racks can be set up and populated as desired for the storage memory. The storage cluster 160 has a single chassis 138 having multiple slots 142. It should be appreciated that chassis 138 may be referred to as a housing, enclosure, or rack unit. In one embodiment, the chassis 138 has fourteen slots 142, although other numbers of slots are readily devised. For example, some embodiments have four slots, eight slots, sixteen slots, thirty-two slots, or other suitable number of slots. Each slot 142 can accommodate one storage node 150 in some embodiments. Chassis 138 includes flaps 148 that can be utilized to mount the chassis 138 on a rack. Fans 144 provide air circulation for cooling of the storage nodes 150 and components thereof, although other cooling components could be used, or an embodiment could be devised without cooling components. A switch fabric 146 couples storage nodes 150 within chassis 138 together and to a network for communication to the memory. In an embodiment depicted in FIG. 1, the slots 142 to the left of the switch fabric 146 and fans 144 are shown occupied by storage nodes 150, while the slots 142 to the right of the switch fabric 146 and fans 144 are empty and available for insertion of storage node 150 for illustrative purposes. This configuration is one example, and one or more storage nodes 150 could occupy the slots 142 in various further arrangements. The storage node arrangements need not be sequential or adjacent in some embodiments. Storage nodes 150 are hot pluggable, meaning that a storage node 150 can be inserted into a slot 142 in the chassis 138, or removed from a slot 142, without stopping or powering down the system. Upon insertion or removal of storage node 150 from slot 142, the system automatically reconfigures in order to recognize and adapt to the change. Reconfiguration, in some embodiments, includes restoring redundancy and/or rebalancing data or load.


Each storage node 150 can have multiple components. In the embodiment shown here, the storage node 150 includes a printed circuit board 158 populated by a CPU 156, i.e., processor, a memory 154 coupled to the CPU 156, and a non-volatile solid state storage 152 coupled to the CPU 156, although other mountings and/or components could be used in further embodiments. The memory 154 has instructions which are executed by the CPU 156 and/or data operated on by the CPU 156. As further explained below, the non-volatile solid state storage 152 includes flash or, in further embodiments, other types of solid-state memory.


Storage cluster 160 is scalable, meaning that storage capacity with non-uniform storage sizes is readily added, as described above. One or more storage nodes 150 can be plugged into or removed from each chassis and the storage cluster self-configures in some embodiments. Plug-in storage nodes 150, whether installed in a chassis as delivered or later added, can have different sizes. For example, in one embodiment a storage node 150 can have any multiple of 4 TB, e.g., 8 TB, 12 TB, 16 TB, 32 TB, etc. In further embodiments, a storage node 150 could have any multiple of other storage amounts or capacities. Storage capacity of each storage node 150 is broadcast, and influences decisions of how to stripe the data. For maximum storage efficiency, an embodiment can self-configure as wide as possible in the stripe, subject to a predetermined requirement of continued operation with loss of up to one, or up to two, non-volatile solid state storage units 152 or storage nodes 150 within the chassis.



FIG. 2 is a system diagram of an enterprise computing system 102, which can use one or more of the storage nodes, storage clusters and/or non-volatile solid-state storage of FIG. 1 as a storage resource 108. For example, flash storage 128 of FIG. 2 may integrate the storage nodes, storage clusters and/or non-volatile solid-state storage of FIG. 1 in some embodiments. The enterprise computing system 102 has processing resources 104, networking resources 106 and storage resources 108, including flash storage 128. A flash controller 130 and flash memory 132 are included in the flash storage 128. In various embodiments, the flash storage 128 could include one or more storage nodes or storage clusters, with the flash controller 130 including the CPUs, and the flash memory 132 including the non-volatile solid-state storage of the storage nodes. In some embodiments flash memory 132 may include different types of flash memory or the same type of flash memory. The enterprise computing system 102 illustrates an environment suitable for deployment of the flash storage 128, although the flash storage 128 could be used in other computing systems or devices, larger or smaller, or in variations of the enterprise computing system 102, with fewer or additional resources. The enterprise computing system 102 can be coupled to a network 140, such as the Internet, in order to provide or make use of services. For example, the enterprise computing system 102 could provide cloud services, physical computing resources, or virtual computing services.


In the enterprise computing system 102, various resources are arranged and managed by various controllers. A processing controller 110 manages the processing resources 104, which include processors 116 and random-access memory (RAM) 118. Networking controller 112 manages the networking resources 106, which include routers 120, switches 122, and servers 124. A storage controller 114 manages storage resources 108, which include hard drives 126 and flash storage 128. Other types of processing resources, networking resources, and storage resources could be included with the embodiments. In some embodiments, the flash storage 128 completely replaces the hard drives 126. The enterprise computing system 102 can provide or allocate the various resources as physical computing resources, or in variations, as virtual computing resources supported by physical computing resources. For example, the various resources could be implemented using one or more servers executing software. Files or data objects, or other forms of data, are stored in the storage resources 108.


In various embodiments, an enterprise computing system 102 could include multiple racks populated by storage clusters, and these could be located in a single physical location such as in a cluster or a server farm. In other embodiments the multiple racks could be located at multiple physical locations such as in various cities, states or countries, connected by a network. Each of the racks, each of the storage clusters, each of the storage nodes, and each of the non-volatile solid-state storage could be individually configured with a respective amount of storage space, which is then reconfigurable independently of the others. Storage capacity can thus be flexibly added, upgraded, subtracted, recovered and/or reconfigured at each of the non-volatile solid-state storages. As mentioned previously, each storage node could implement one or more servers in some embodiments.



FIG. 3 is a multiple level block diagram, showing contents of a storage node 150 and contents of a non-volatile solid state storage 152 of the storage node 150. Data is communicated to and from the storage node 150 by a network interface controller (NIC) 202 in some embodiments. Each storage node 150 has a CPU 156, and one or more non-volatile solid state storage 152, as discussed above. Moving down one level in FIG. 3, each non-volatile solid state storage 152 has a relatively fast non-volatile solid state memory, such as nonvolatile random access memory (NVRAM) 204, and flash memory 206. In some embodiments, NVRAM 204 may be a component that does not require program/erase cycles (DRAM, MRAM, PCM), and can be a memory that can support being written vastly more often than the memory is read from. Moving down another level in FIG. 3, the NVRAM 204 is implemented in one embodiment as high speed volatile memory, such as dynamic random access memory (DRAM) 216, backed up by energy reserve 218. Energy reserve 218 provides sufficient electrical power to keep the DRAM 216 powered long enough for contents to be transferred to the flash memory 206 in the event of power failure. In some embodiments, energy reserve 218 is a capacitor, super-capacitor, battery, or other device, that supplies a suitable supply of energy sufficient to enable the transfer of the contents of DRAM 216 to a stable storage medium in the case of power loss. The flash memory 206 is implemented as multiple flash dies 222, which may be referred to as packages of flash dies 222 or an array of flash dies 222. It should be appreciated that the flash dies 222 could be packaged in any number of ways, with a single die per package, multiple dies per package (i.e. multichip packages), in hybrid packages, as bare dies on a printed circuit board or other substrate, as encapsulated dies, etc. In the embodiment shown, the non-volatile solid state storage 152 has a controller 212 or other processor, and an input output (I/O) port 210 coupled to the controller 212. I/O port 210 is coupled to the CPU 156 and/or the network interface controller 202 of the flash storage node 150. Flash input output (I/O) port 220 is coupled to the flash dies 222, and a direct memory access unit (DMA) 214 is coupled to the controller 212, the DRAM 216 and the flash dies 222. In the embodiment shown, the I/O port 210, controller 212, DMA unit 214 and flash I/O port 220 are implemented on a programmable logic device (PLD) 208, e.g., a field programmable gate array (FPGA). In this embodiment, each flash die 222 has pages, organized as sixteen kB (kilobyte) pages 224, and a register 226 through which data can be written to or read from the flash die 222. In further embodiments, other types of solid-state memory are used in place of, or in addition to flash memory illustrated within flash die 222.


In NVRAM 204, redundancy is not organized by segments but instead by messages, where each message (128 bytes to 128 kB) establishes its own data stripe, in some embodiments. NVRAM is maintained at the same redundancy as segment storage and operates within the same storage node groups in some embodiments. Because messages are stored individually the stripe width is determined both by message size and the storage cluster configuration. Larger messages may be more efficiently stored as wider strips.


Two of the many tasks of the CPU 156 on a storage node 150 are to break up write data, and reassemble read data. When the system has determined that data is to be written, an authority for that data is located in one of the non-volatile solid-state storages 152. The authority may be embodied as metadata, including one or more lists such as lists of data segments which the nonvolatile solid-state storage 152 manages. When a segment ID for data is already determined the request to write is forwarded to the non-volatile solid-state storage 152 currently determined to be the host of the authority determined from the segment. The host CPU 156 of the storage node 150, on which the non-volatile solid-state storage 152 and corresponding authority reside, then breaks up or shards the data and transmits the data out to various non-volatile solid-state storage 152. The transmitted data is written as a data stripe in accordance with an erasure coding scheme. In some embodiments, data is requested to be pulled, and in other embodiments, data is pushed. In reverse, when data is read, the authority for the segment ID containing the data is located as described above. The host CPU 156 of the storage node 150 on which the non-volatile solid-state storage 152 and corresponding authority reside requests the data from the non-volatile solid-state storage and corresponding storage nodes pointed to by the authority. In some embodiments the data is read from flash storage as a data stripe. The host CPU 156 of storage node 150 then reassembles the read data, correcting any errors (if present) according to the appropriate erasure coding scheme, and forwards the reassembled data to the network. In further embodiments, some or all of these tasks can be handled in the non-volatile solid-state storage 152. In some embodiments, the segment host requests the data be sent to storage node 150 by requesting pages from storage and then sending the data to the storage node making the original request.


In some systems, for example in UNIX-style file systems, data is handled with an index node or inode, which specifies a data structure that represents an object in a file system. The object could be a file or a directory, for example. Metadata may accompany the object, as attributes such as permission data and a creation timestamp, among other attributes. A segment number could be assigned to all or a portion of such an object in a file system. In other systems, data segments are handled with a segment number assigned elsewhere. For purposes of discussion, the unit of distribution is an entity, and an entity can be a file, a directory or a segment. That is, entities are units of data or metadata stored by a storage system. Entities are grouped into sets called authorities. Each authority has an authority owner, which is a storage node that has the exclusive right to update the entities in the authority. In other words, a storage node contains the authority, and that the authority, in turn, contains entities.


A segment is a logical container of data in accordance with some embodiments. A segment may be an address space between medium address space and physical flash locations. Each data segment is protected, e.g., from memory and other failures, by breaking the segment into a number of data and parity shards, where applicable. The data and parity shards are distributed, i.e., striped, across non-volatile solid-state storages 152 coupled to the host CPUs 156 in accordance with an erasure coding scheme. Usage of the term segments refers to the container and its place in the address space of segments in some embodiments. Usage of the term stripe refers to the same set of shards as a segment and includes how the shards are distributed along with redundancy or parity information in accordance with some embodiments.


A series of address-space transformations takes place across an entire storage system. At the top is the inode address space, which the filesystem uses to translate file paths to inode IDs (Identifications). Inodes point into medium address space, where data is logically stored. Medium addresses are mapped into segment address space. Segment addresses are then translated into physical flash locations. Physical flash locations have an address range bounded by the amount of flash in the system in accordance with some embodiments. Medium addresses and segment addresses are logical containers, and in some embodiments use a 128 bit or larger identifier so as to be practically infinite, with a likelihood of reuse calculated as longer than the expected life of the system. Addresses from logical containers are allocated in a hierarchical fashion in some embodiments. Initially, each non-volatile solid-state storage 152 may be assigned a range of address space. Within this assigned range, the non-volatile solid-state storage 152 is able to allocate addresses without synchronization with other non-volatile solid-state storage 152.


Data and metadata are stored by a set of underlying storage layouts that are optimized for varying workload patterns and storage devices. These layouts incorporate multiple redundancy schemes, compression formats and index algorithms. Some of these layouts store information about authorities and authority masters, while others store file metadata and file data. The redundancy schemes include error correction codes that tolerate corrupted bits within a single storage device (such as a NAND flash chip), erasure codes that tolerate the failure of multiple storage nodes, and replication schemes that tolerate data center or regional failures. In some embodiments, low density parity check (LDPC) code is used within a single storage unit. Data is not further replicated within a storage cluster, as it is assumed a storage cluster may fail. Reed-Solomon encoding is used within a storage cluster, and mirroring is used within a storage grid in some embodiments. Metadata may be stored using an ordered log structured index (such as a Log Structured Merge Tree), and large data may be stored in an unordered log structured layout (similar to log structured file systems).



FIG. 4 is a block diagram showing a communication path 234 for redundant copies of metadata 230, with further details of flash storage nodes 150 (i.e., storage nodes 150 having flash memory) and non-volatile solid-state storages 152 in accordance with some embodiments. Metadata 230 includes information about the user data that is written to or read from the flash memory 206. Metadata 230 can include messages, or derivations from the messages, indicating actions to be taken or actions that have taken place involving the data that is written to or read from the flash memory 206. Distributing redundant copies of metadata 230 to the non-volatile solid-state storage units 152 through the communication interconnect 170 ensures that messages are persisted and can survive various types of failure the system may experience. Each non-volatile solid-state storage 152 dedicates a portion of the NVRAM 204 to storing metadata 230. In some embodiments, redundant copies of metadata 230 are stored in the additional non-volatile solid-state storage 152.


Flash storage nodes 150 are coupled via the communication interconnect 170. More specifically, the network interface controller 202 of each storage node 150 in the storage cluster is coupled to the communication interconnect 170, providing a communication path 234 among storage nodes 150 and non-volatile solid-state storage 152. Storage nodes 150 have one or more non-volatile solid-state storage units 152. Non-volatile solid-state storage units 152 internal to a storage node can communicate with each other, for example via a bus, a serial communication path, a network path or other communication path 234 as readily devised in accordance with the embodiments disclosed herein. Communication interconnect 170 can be included in or implemented with the switch fabric of FIG. 1 in some embodiments. Storage nodes 150 of FIG. 4 form a storage cluster that is enclosed within a single chassis that has an internal power distribution bus within the chassis as described with reference to FIG. 1.


Referring to FIGS. 3 and 4, in case of a power failure, whether local to non-volatile solid-state storage 152 or a storage node 150, data can be copied from the NVRAM 204 to the flash memory 206. For example, the DMA unit 214 of FIG. 3 can copy contents of the NVRAM 204, including the metadata, to the flash memory 206, using power supplied by the energy reserve 218. Energy reserve 218 is sized with sufficient capacity to support copy operation. That is, the energy reserve 218 should be sized so as to provide sufficient current at a sufficient voltage level for a time duration long enough to complete the copying so that messages that are in metadata 230 are persisted in the flash memory 206.


A further mechanism for persisting messages in a storage system involves the communication path 234 described above in FIG. 4. Redundant copies of the metadata 230 can be distributed via the communication path 234, in various ways. For example, a message coming from the filesystem could be distributed via the communication interconnect 170 as a broadcast over the communication path 234 to all of the non-volatile solid-state storages 152. A non-volatile solid-state storage 152 could send a copy of metadata 230 over the communication path 234 to other non-volatile solid-state storage 152 in a storage node 150. CPU 156 on a storage node 150, receiving a message from the communication interconnect 170 via the network interface controller 202 could send a copy of the message to each solid-state storage 152. The CPU 156 may rebroadcast the message to other flash storage nodes 150, and the flash storage nodes 150 could then distribute the message to the solid-state storages 152 in each of these flash storage nodes 150 in some embodiments. In these and other uses of the communication path 234, redundant copies of the metadata 230 can be distributed to the non-volatile solid-state storages 152. Then, if one non-volatile solid-state storage 152, or one storage node 150 experiences a failure, redundant copies of any message are available in metadata 230 of at least one other non-volatile solid-state storage 152. Each non-volatile solid-state storage 152 can apply decision logic 232 when evaluating various situations such as local power failure, an unreachable node, or instructions to consider or commence a data recovery or a data rebuild. The decision logic 232 includes witnessing logic, voting logic, consensus logic and/or other types of decision logic in various embodiments. Decision logic 232 could be implemented in hardware, software executing on the controller 212, firmware, or combinations thereof, and could be implemented as part of the controller 212 or coupled to the controller 212. The decision logic 232 is employed in consensus decisions among multiple solid-state storage units 152, in some embodiments. In further embodiments, the decision logic 232 could cooperate with the other non-volatile solid-state storage units 152 in order to gather copies of the redundant metadata 230, and make local decisions. The mechanisms for persisting messages in a storage system are useful in the event of a failure, and can be used in data recovery and reconstruction as described above.


Examples of messages include a request to write data, a request to read data, a request to lock or unlock a file, a change in permission of a file, an update to a file allocation table or other file or directory structure, a request to write a file that has executable instructions or to write a file name that is reserved and interpreted as an executable direction, updates to one or more authorities, updates to a fingerprint table, list or other data used in deduplication, updates to hash tables, updates to logs, and so on. When a message is received in non-volatile solid-state storage 152 of a storage node 150, indicating some action has taken place, the message or a derivation of the message is stored as metadata 230 in the NVRAM 204 of that solid-state storage 152. By applying the redundant copies of the metadata 230, actions are captured that are in progress, so that if a failure happens, these actions can be replayed and replacement actions can then be performed, for example upon restart. Actions span storage nodes and use cluster messaging, so the act of sending a message can be made persistent data via one or more of the mechanisms for persisting messages. These mechanisms address some of the known failure scenarios in order to ensure availability of data. In some embodiments, the messages don't require permanence beyond completion of the actions. In other embodiments the messages are further retained to facilitate rollback or other recovery operations.


For example, if a command is sent out to carry out a write operation, this message is recorded and redundant. If there is a failure, it can be determined whether or not that action has been carried out, and whether or not the action should be driven to completion. Such determination can be carried out using the decision logic 232 in each non-volatile solid-state storage 152. There is dedicated storage in NVRAM 204 for messages and other metadata 230, so that messages are recorded in the non-volatile solid-state storage 152 and replicated in some embodiments. The messages and other metadata 230 are written into flash memory 206 if one non-volatile solid-state storage 152 experiences a power failure, or if the entire system experiences a power failure or otherwise shuts down. The redundancy level of the messages matches the redundancy level of the metadata in some embodiments. When there are sufficient numbers of copies of messages, the message becomes irrevocable. If one node goes down, other nodes can vote, achieve consensus, or witness the various copies of the message and determine what action, if any, to carry to completion. If the entire system goes down, e.g., through a global power failure, then a sufficient number of these messages get written from NVRAM 204 to flash memory 206. Upon restoration of power, the nodes can again open copies of the message and determine what action, if any, to carry to completion to prevent any corruption.


With continued reference to FIGS. 3 and 4, storage node 150 of a storage cluster 160 includes two levels of controllers. There is a host CPU 156 in the storage node 150, and there is a controller 212 in the non-volatile solid-state storage 152. The controller 212 can be considered a flash memory controller, which serves as a bridge between the host CPU 156 and the flash memory 206. Each of these controllers, namely the host CPU 156 and the flash controller 212, can be implemented as one or more processors or controllers of various types from various manufacturers. The host CPU 156 can access both the flash memory 206 and the NVRAM 204 as distinct resources, with each being independently (i.e., individually) addressable by the host CPU 156.


By separating the NVRAM 204 and the flash memory 206 into distinct resources, not all data placed in the NVRAM 204 must be written to the flash memory 206. The NVRAM 204 can also be employed for various functions and purposes. For example, updates to the NVRAM 204 can be made obsolete by newer updates to the NVRAM 204. A later transfer of user data from the NVRAM 204 to the flash memory 206 can transfer the updated user data, without transferring the obsolete user data to the flash memory 206. This reduces the number of erasure cycles of the flash memory 206, reduces wear on the flash memory 206, and moves data more efficiently. The CPU 156 can write to the NVRAM 204 at a smaller granularity than the granularity of the transfers from the NVRAM 204 to the flash memory 206. For example, the CPU 156 could perform 4 kB writes to the NVRAM 204, and the DMA unit 214 could perform a page write of 16 kB from the NVRAM 204 to the flash memory 206 under direction of the controller 212. The ability to collect multiple writes of user data to the NVRAM 204 prior to writing the user data from the NVRAM 204 to the flash memory 206 increases writing efficiency. In some embodiments, a client write of user data is acknowledged at the point at which the user data is written to the NVRAM 204. Since the energy reserve 218, described above with reference to FIG. 3, provides sufficient power for a transfer of contents of the NVRAM 204 to the flash memory 206, the acknowledgment of the client write does not need to wait until the user data is written to the flash memory 206.


As further examples of differences between present embodiments and previous solid-state drives, the metadata 230 in the NVRAM 204 is not written into the flash memory 206, except in cases of power loss. Here, a portion of the NVRAM 204 acts as a workspace for the CPU 156 of the storage node 150 to apply the metadata 230. The CPU 156 of the storage node 150 can write to the NVRAM 204 and read the NVRAM 204, in order to access the metadata 230. The CPU 156 is responsible for migrating data from the NVRAM 204 down to the flash memory 206 in one embodiment. Transfer from the NVRAM 204 to the flash memory 206 is not automatic and predetermined, in such embodiments. Transfer waits until there is sufficient user data in the NVRAM 204 for a page write to the flash memory 206, as determined by the CPU 156 and directed to the DMA unit 214. The DMA unit 214 can be further involved in the path of the user data. In some embodiments, the DMA unit 214 (also known as a DMA engine) is designed to detect and understand various data formats. The DMA unit 214 can perform a cyclic redundancy check (CRC) calculation to check the integrity of the user data. In some embodiments, the DMA unit 214 inserts the CRC calculation into the data and verifies that the data is consistent with a previously inserted CRC calculation.


Work may be offloaded to the controller 212 of the non-volatile solid-state storage 152. Processing that is offloaded to flash controller 212 can be co-designed with processing performed by the CPU 156 of the storage node 150. Various mapping tables that translate from one address space to another, e.g., index trees or address translation tables, can be managed within the non-volatile solid-state storage 152, in some embodiments. The controller 212 of the non-volatile solid-state storage 152 can perform various tasks such as looking through these mapping tables, finding metadata associated with the mapping tables, and determining physical addresses, e.g., for user data sought by the CPU 156 of the storage node 150. In order to find an authority associated with a segment number, a standard solid-state drive might bring back an entire 16 kB flash page, and the CPU 156 would search in this page. In some embodiments, the controller 212 of the non-volatile solid-state storage 152 can perform this search much more efficiently, and pass the results to the CPU 156 of the storage node 150, without sending back the entire flash page to the CPU 156.



FIG. 5 is a flow diagram of a method for accessing a non-volatile solid-state storage, which can be practiced on or by embodiments of storage clusters, storage nodes and/or non-volatile solid-state storages in accordance with some embodiments. Many of the actions described in the method can be performed by one or more processors, such as processors on storage nodes and non-volatile solid-state storages in some embodiments. In an action 502, user data is sent to a storage cluster. For example, a client could send the user data via a network, for storage in the storage cluster. The user data is forwarded to a storage node, in an action 504. For example, the storage cluster could route the user data to a storage node via a communication interconnect. In an action 506, the user data is written from the storage node into NVRAM of a non-volatile solid-state storage. For example, a CPU of the storage node could write the user data from the storage node into the NVRAM of a non-volatile solid-state storage. The client write is acknowledged, in an action 508. For example, the CPU of the storage node acknowledges the client write.


Metadata is written into the NVRAM of the non-volatile solid-state storage, in an action 510. For example, the CPU of the storage node could write metadata pertaining to user data into the NVRAM of the non-volatile solid-state storage. In a decision action 512, it is determined if there is sufficient user data in the NVRAM for a batch mode transfer from the NVRAM to flash memory of the non-volatile solid-state storage. If the answer is no, flow branches back to the action 502, for more user data. If the answer is yes, flow continues to the action 514.


The controller of the non-volatile solid-state storage is directed to perform the transfer, in an action 514. For example, the CPU of the storage node could direct the controller of the non-volatile solid-state storage to perform a page write or other batch mode transfer, since there is now sufficient user data in the NVRAM. The DMA unit is directed to perform the transfer, in an action 516. For example, upon receiving instructions from the CPU of the storage node, the controller may direct the DMA unit of the non-volatile solid-state storage to perform a DMA transfer of the user data from the NVRAM to the flash memory. The user data is transferred from the NVRAM of the non-volatile solid-state storage to the flash memory of the non-volatile solid-state storage, in an action 518. This transfer could be performed by the DMA unit, as directed by the controller.


Metadata is read from the NVRAM of the non-volatile solid-state storage, in an action 520. For example, the CPU of the storage node could read the metadata from the NVRAM, in order to obtain information pertaining to the user data. In an action 522, the controller of the non-volatile solid-state storage is requested to find information in the flash memory of the non-volatile solid-state storage. For example, the CPU of the storage node, after processing the metadata obtained from the NVRAM, could request the controller of the non-volatile solid-state storage find additional information.


In an action 524, the information within the flash memory is searched. For example, the controller of the non-volatile solid-state storage could read a page from the flash memory, and search for the information. The information is sent to the CPU of the storage node, in an action 526. For example, the controller of the non-volatile solid-state storage could find the information in a subset of the page of the flash memory, and send the information to the CPU of the storage node, without sending the entire page. The CPU of the storage node could then use this information, perhaps in combination with the metadata that the CPU read from the NVRAM to locate user data for reading. In other embodiments the information could be used to determine a location for writing user data or performing other operations as readily devised in accordance with the teachings herein.


It should be appreciated that the methods described herein may be performed with a digital processing system, such as a conventional, general-purpose computer system. Special purpose computers, which are designed or programmed to perform only one function may be used in the alternative. FIG. 6 is an illustration showing an exemplary computing device which may implement the embodiments described herein. The computing device of FIG. 6 may be used to perform embodiments of the functionality for a storage node or a non-volatile solid-state storage in accordance with some embodiments. The computing device includes a central processing unit (CPU) 601, which is coupled through a bus 605 to a memory 603, and mass storage device 607. Mass storage device 607 represents a persistent data storage device such as a disc drive, which may be local or remote in some embodiments. The mass storage device 607 could implement a backup storage, in some embodiments. Memory 603 may include read only memory, random access memory, etc. Applications resident on the computing device may be stored on or accessed via a computer readable medium such as memory 603 or mass storage device 607 in some embodiments. Applications may also be in the form of modulated electronic signals modulated accessed via a network modem or other network interface of the computing device. It should be appreciated that CPU 601 may be embodied in a general-purpose processor, a special purpose processor, or a specially programmed logic device in some embodiments.


Display 611 is in communication with CPU 601, memory 603, and mass storage device 607, through bus 605. Display 611 is configured to display any visualization tools or reports associated with the system described herein. Input/output device 609 is coupled to bus 605 in order to communicate information in command selections to CPU 601. It should be appreciated that data to and from external devices may be communicated through the input/output device 609. CPU 601 can be defined to execute the functionality described herein to enable the functionality described with reference to FIGS. 1-5. The code embodying this functionality may be stored within memory 603 or mass storage device 607 for execution by a processor such as CPU 601 in some embodiments. The operating system on the computing device may be MS-WINDOWS™, UNIX™, LINUX™, iOS™, CentOS™, Android, Redhat Linux™, z/OS™, or other known operating systems. It should be appreciated that the embodiments described herein may be integrated with virtualized computing system also.


Detailed illustrative embodiments are disclosed herein. However, specific functional details disclosed herein are merely representative for purposes of describing embodiments. Embodiments may, however, be embodied in many alternate forms and should not be construed as limited to only the embodiments set forth herein.


It should be understood that although the terms first, second, etc. may be used herein to describe various steps or calculations, these steps or calculations should not be limited by these terms. These terms are only used to distinguish one step or calculation from another. For example, a first calculation could be termed a second calculation, and, similarly, a second step could be termed a first step, without departing from the scope of this disclosure. As used herein, the term “and/or” and the “/” symbol includes any and all combinations of one or more of the associated listed items.


As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises”, “comprising”, “includes”, and/or “including”, when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Therefore, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.


It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may in fact be executed substantially concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.


With the above embodiments in mind, it should be understood that the embodiments might employ various computer-implemented operations involving data stored in computer systems. These operations are those requiring physical manipulation of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. Further, the manipulations performed are often referred to in terms, such as producing, identifying, determining, or comparing. Any of the operations described herein that form part of the embodiments are useful machine operations. The embodiments also relate to a device or an apparatus for performing these operations. The apparatus can be specially constructed for the required purpose, or the apparatus can be a general-purpose computer selectively activated or configured by a computer program stored in the computer. In particular, various general-purpose machines can be used with computer programs written in accordance with the teachings herein, or it may be more convenient to construct a more specialized apparatus to perform the required operations.


A module, an application, a layer, an agent or other method-operable entity could be implemented as hardware, firmware, or a processor executing software, or combinations thereof. It should be appreciated that, where a software-based embodiment is disclosed herein, the software can be embodied in a physical machine such as a controller. For example, a controller could include a first module and a second module. A controller could be configured to perform various actions, e.g., of a method, an application, a layer or an agent.


The embodiments can also be embodied as computer readable code on a non-transitory computer readable medium. The computer readable medium is any data storage device that can store data, which can be thereafter read by a computer system. Examples of the computer readable medium include hard drives, network attached storage (NAS), read-only memory, random-access memory, CD-ROMs, CD-Rs, CD-RWs, magnetic tapes, and other optical and non-optical data storage devices. The computer readable medium can also be distributed over a network coupled computer system so that the computer readable code is stored and executed in a distributed fashion. Embodiments described herein may be practiced with various computer system configurations including hand-held devices, tablets, microprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers and the like. The embodiments can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a wire-based or wireless network.


Although the method operations were described in a specific order, it should be understood that other operations may be performed in between described operations, described operations may be adjusted so that they occur at slightly different times or the described operations may be distributed in a system which allows the occurrence of the processing operations at various intervals associated with the processing.


In various embodiments, one or more portions of the methods and mechanisms described herein may form part of a cloud-computing environment. In such embodiments, resources may be provided over the Internet as services according to one or more various models. Such models may include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). In IaaS, computer infrastructure is delivered as a service. In such a case, the computing equipment is generally owned and operated by the service provider. In the PaaS model, software tools and underlying equipment used by developers to develop software solutions may be provided as a service and hosted by the service provider. SaaS typically includes a service provider licensing software as a service on demand. The service provider may host the software, or may deploy the software to a customer for a given period of time. Numerous combinations of the above models are possible and are contemplated.


Various units, circuits, or other components may be described or claimed as “configured to” perform a task or tasks. In such contexts, the phrase “configured to” is used to connote structure by indicating that the units/circuits/components include structure (e.g., circuitry) that performs the task or tasks during operation. As such, the unit/circuit/component can be said to be configured to perform the task even when the specified unit/circuit/component is not currently operational (e.g., is not on). The units/circuits/components used with the “configured to” language include hardware—for example, circuits, memory storing program instructions executable to implement the operation, etc. Reciting that a unit/circuit/component is “configured to” perform one or more tasks is expressly intended not to invoke 35 U.S.C. 112, sixth paragraph, for that unit/circuit/component. Additionally, “configured to” can include generic structure (e.g., generic circuitry) that is manipulated by software and/or firmware (e.g., an FPGA or a general-purpose processor executing software) to operate in manner that is capable of performing the task(s) at issue. “Configured to” may also include adapting a manufacturing process (e.g., a semiconductor fabrication facility) to fabricate devices (e.g., integrated circuits) that are adapted to implement or perform one or more tasks.


The foregoing description, for the purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the embodiments and its practical applications, to thereby enable others skilled in the art to best utilize the embodiments and various modifications as may be suited to the particular use contemplated. Accordingly, the present embodiments are to be considered as illustrative and not restrictive, and the invention is not to be limited to the details given herein, but may be modified within the scope and equivalents of the appended claims.

Claims
  • 1. A storage system, comprising: a non-volatile random access memory (NVRAM) addressable by a first controller internal to non-volatile solid-state storage of the storage system, and by a second controller external to the non-volatile solid-state storage, the NVRAM configured to store user data and metadata relating to the user data, wherein the NVRAM is configured to store metadata corresponding to user data stored external to the non-volatile solid-state storage; andthe non-volatile solid state storage addressable by the first controller and by the second controller, the non-volatile solid state storage configured to store the user data responsive to the second controller directing transfer of the user data from the NVRAM to the non-volatile solid state storage.
  • 2. The system of claim 1, further comprising: a direct memory access (DMA) engine, configured to move the user data from the NVRAM to the non-volatile solid-state storage and to perform a cyclic redundancy check (CRC) to verify the user data.
  • 3. The system of claim 1, wherein: the NVRAM is configured as a workspace for the second processor to apply the metadata.
  • 4. The system of claim 1, further comprising: a direct memory access (DMA) engine, configured to transfer the user data from the NVRAM to the nonvolatile solid-state memory responsive to a plurality of writes of the user data to the NVRAM providing sufficient user data in the NVRAM for a page write to the nonvolatile solid-state memory.
  • 5. The system of claim 1, wherein: the NVRAM includes dynamic random access memory (DRAM) and an energy reserve.
  • 6. The system of claim 1, wherein the non-volatile solid state storage is contained within a storage node of a storage cluster, the storage cluster comprising a plurality of storage nodes wherein each of the plurality of storage nodes has one or more authorities, each of which directs sharding and reassembling of a range of the user data belonging to the respective authority.
  • 7. The system of claim 6, wherein the plurality of storage nodes is configured to distribute the user data and metadata associated with the user data throughout the plurality of storage nodes such that the plurality of storage nodes can access the user data, via erasure coding, with a failure of two of the plurality of storage nodes.
  • 8. A storage cluster, comprising: a plurality of storage nodes, each of the plurality of storage nodes having nonvolatile solid-state memory for storage of user data, the nonvolatile solid-state memory comprising:a non-volatile random access memory (NVRAM) configured to receive the user data and metadata from a processor of a storage node of the plurality of storage nodes, the NVRAM and the nonvolatile solid-state memory addressable by the processor, wherein the NVRAM is configured to include a portion dedicated to metadata corresponding to user data stored external to the non-volatile solid-state storage; anda controller configured to manage the user data in the nonvolatile solid-state memory, wherein the NVRAM and the nonvolatile solid-state memory are addressable by the controller.
  • 9. The storage cluster of claim 8, further comprising: an energy reserve coupled to the NVRAM and the nonvolatile solid-state memory, the energy reserve having sufficient capacity to support transfer of contents of the NVRAM to the nonvolatile solid-state memory; anda direct memory access (DMA) unit configured to transfer the contents of the NVRAM to the nonvolatile solid-state memory, responsive to the power loss.
  • 10. The storage cluster of claim 8, wherein: the metadata is not transferred from the NVRAM to the nonvolatile solid-state memory except in the event of the power loss; anda DMA unit configured to transfer the metadata from the NVRAM to the nonvolatile solid- state memory in the event of the power loss.
  • 11. The storage cluster of claim 8, further comprising: the controller configured to manage an address translation table that maps from a first address space to a second address space.
  • 12. The storage cluster of claim 8, wherein the metadata pertains to sharding and reassembling the user data as performed by the processor, and wherein each of the plurality of storage nodes has one or more authorities, each of which directs the sharding and the reassembling of a range of the user data belonging to the respective authority.
  • 13. The storage cluster of claim 8, wherein: the nonvolatile solid-state memory is configured to receive the user data from the NVRAM as a page write; andthe NVRAM is configured to receive the user data from the processor with each write to the NVRAM having a smaller amount of data than the page write to the nonvolatile solid-state memory.
  • 14. The storage cluster of claim 8, wherein the plurality of storage nodes is configured to distribute the user data and metadata associated with the user data throughout the plurality of storage nodes such that the plurality of storage nodes can access the user data, via erasure coding, with a failure of two of the plurality of storage nodes.
  • 15. A method, comprising: writing user data from a storage node of the storage cluster to a non-volatile random-access memory (NVRAM) of a non-volatile solid-state storage;writing metadata associated with user data from a differing storage node of the storage cluster to the NVRAM;writing the user data from the NVRAM to non-volatile solid-state storage, wherein each of the NVRAM and the nonvolatile solid-state memory is addressable as a distinct resource by a controller of the storage node, wherein each of the NVRAM and the nonvolatile solid-state memory is addressable as the distinct resource by a controller of the non-volatile solid-state storage, and wherein the writing the user data from the NVRAM to the non-volatile solid-state storage is directed by the controller of the storage node.
  • 16. The method of claim 15, further comprising: writing an update of the user data to the NVRAM, wherein the update obsoletes a portion of the user data in the NVRAM, and wherein the writing the user data from the NVRAM to the nonvolatile solid-state memory is performed in a batch mode transfer that includes the update of the user data.
  • 17. The method of claim 15, wherein the storage node has one or more authorities, each of which directs sharding and reassembling of a range of the user data belonging to the respective authority.
  • 18. The method of claim 15, further comprising: acknowledging a client write of the user data, responsive to the writing the user data to the NVRAM, the acknowledging occurring prior to the writing the user data from the NVRAM to the nonvolatile solid-state memory.
  • 19. The method of claim 15, further comprising: collecting a plurality of writes of the user data to the NVRAM, prior to the writing the user data from the NVRAM to the nonvolatile solid-state memory.
  • 20. The method of claim 15, further comprising: searching in the nonvolatile solid-state memory for information stored in a subset of a flash page, wherein the searching is performed by the controller of the non-volatile solid-state storage; andsending the information to the processor of the storage node without sending an entirety of the flash page to the controller of the storage node.
US Referenced Citations (464)
Number Name Date Kind
5390327 Lubbers et al. Feb 1995 A
5450581 Bergen et al. Sep 1995 A
5479653 Jones Dec 1995 A
5488731 Mendelsohn Jan 1996 A
5504858 Ellis et al. Apr 1996 A
5564113 Bergen et al. Oct 1996 A
5574882 Menon et al. Nov 1996 A
5649093 Hanko et al. Jul 1997 A
5883909 Dekoning et al. Mar 1999 A
6000010 Legg Dec 1999 A
6260156 Garvin et al. Jul 2001 B1
6269453 Krantz Jul 2001 B1
6275898 DeKoning Aug 2001 B1
6453428 Stephenson Sep 2002 B1
6523087 Busser Feb 2003 B2
6535417 Tsuda Mar 2003 B2
6643748 Wieland Nov 2003 B1
6725392 Frey et al. Apr 2004 B1
6763455 Hall Jul 2004 B2
6836816 Kendall Dec 2004 B2
6985995 Holland et al. Jan 2006 B2
7032125 Holt et al. Apr 2006 B2
7047358 Lee et al. May 2006 B2
7051155 Talagala et al. May 2006 B2
7055058 Lee et al. May 2006 B2
7065617 Wang Jun 2006 B2
7069383 Yamamoto et al. Jun 2006 B2
7076606 Orsley Jul 2006 B2
7107480 Moshayedi et al. Sep 2006 B1
7159150 Kenchammana-Hosekote et al. Jan 2007 B2
7162575 Dalai et al. Jan 2007 B2
7164608 Lee Jan 2007 B2
7188270 Nanda et al. Mar 2007 B1
7334156 Land et al. Feb 2008 B2
7370220 Nguyen et al. May 2008 B1
7386666 Beauchamp et al. Jun 2008 B1
7398285 Kisley Jul 2008 B2
7424498 Patterson Sep 2008 B1
7424592 Karr Sep 2008 B1
7444532 Masuyama et al. Oct 2008 B2
7480658 Heinla et al. Jan 2009 B2
7484056 Madnani et al. Jan 2009 B2
7484057 Madnani et al. Jan 2009 B1
7484059 Ofer et al. Jan 2009 B1
7536506 Ashmore et al. May 2009 B2
7558859 Kasiolas Jul 2009 B2
7565446 Talagala et al. Jul 2009 B2
7613947 Coatney Nov 2009 B1
7634617 Misra Dec 2009 B2
7634618 Misra Dec 2009 B2
7681104 Sim-Tang et al. Mar 2010 B1
7681105 Sim-Tang et al. Mar 2010 B1
7681109 Yang et al. Mar 2010 B2
7730257 Franklin Jun 2010 B2
7730258 Smith Jun 2010 B1
7730274 Usgaonkar Jun 2010 B1
7743276 Jacobsen et al. Jun 2010 B2
7752489 Deenadhayalan et al. Jul 2010 B2
7757038 Kitahara Jul 2010 B2
7757059 Ofer et al. Jul 2010 B1
7778960 Chatterjee et al. Aug 2010 B1
7783955 Haratsch et al. Aug 2010 B2
7814272 Barrall et al. Oct 2010 B2
7814273 Barrall Oct 2010 B2
7818531 Barrall Oct 2010 B2
7827351 Suetsugu et al. Nov 2010 B2
7827439 Matthew et al. Nov 2010 B2
7831768 Ananthamurthy et al. Nov 2010 B2
7856583 Smith Dec 2010 B1
7870105 Arakawa et al. Jan 2011 B2
7873878 Belluomini et al. Jan 2011 B2
7885938 Greene et al. Feb 2011 B1
7886111 Klemm et al. Feb 2011 B2
7908448 Chatterjee et al. Mar 2011 B1
7916538 Jeon et al. Mar 2011 B2
7921268 Jakob Apr 2011 B2
7930499 Duchesne Apr 2011 B2
7941697 Mathew et al. May 2011 B2
7958303 Shuster Jun 2011 B2
7971129 Watson Jun 2011 B2
7984016 Kisley Jul 2011 B2
7991822 Bish et al. Aug 2011 B2
8006126 Deenadhayalan et al. Aug 2011 B2
8010485 Chatterjee et al. Aug 2011 B1
8010829 Chatterjee et al. Aug 2011 B1
8020047 Courtney Sep 2011 B2
8046548 Chatterjee et al. Oct 2011 B1
8051361 Sim-Tang et al. Nov 2011 B2
8051362 Li et al. Nov 2011 B2
8074038 Lionetti et al. Dec 2011 B2
8082393 Galloway et al. Dec 2011 B2
8086603 Nasre et al. Dec 2011 B2
8086634 Mimatsu Dec 2011 B2
8086911 Taylor Dec 2011 B1
8090837 Shin et al. Jan 2012 B2
8108502 Tabbara et al. Jan 2012 B2
8117388 Jernigan, IV Feb 2012 B2
8117521 Yang et al. Feb 2012 B2
8140821 Raizen et al. Mar 2012 B1
8145838 Miller et al. Mar 2012 B1
8145840 Koul et al. Mar 2012 B2
8175012 Haratsch et al. May 2012 B2
8176360 Frost et al. May 2012 B2
8176405 Hafner et al. May 2012 B2
8180855 Aiello et al. May 2012 B2
8200922 McKean et al. Jun 2012 B2
8209469 Carpenter et al. Jun 2012 B2
8225006 Karamchetl Jul 2012 B1
8239618 Kotzur et al. Aug 2012 B2
8244999 Chatterjee et al. Aug 2012 B1
8261016 Goel Sep 2012 B1
8271455 Kesselman Sep 2012 B2
8285686 Kesselman Oct 2012 B2
8305811 Jeon Nov 2012 B2
8315999 Chatley et al. Nov 2012 B2
8327080 Der Dec 2012 B1
8335769 Kesselman Dec 2012 B2
8341118 Drobychev et al. Dec 2012 B2
8351290 Huang et al. Jan 2013 B1
8364920 Parkison et al. Jan 2013 B1
8365041 Chu et al. Jan 2013 B2
8375146 Sinclair Feb 2013 B2
8397016 Talagala et al. Mar 2013 B2
8402152 Duran Mar 2013 B2
8412880 Leibowitz et al. Apr 2013 B2
8423739 Ash et al. Apr 2013 B2
8429436 Filinglm et al. Apr 2013 B2
8452928 Ofer et al. May 2013 B1
8473698 Lionetti et al. Jun 2013 B2
8473778 Simitci Jun 2013 B2
8473815 Yu et al. Jun 2013 B2
8479037 Chatterjee et al. Jul 2013 B1
8484414 Sugimoto et al. Jul 2013 B2
8498967 Chatterjee et al. Jul 2013 B1
8522073 Cohen Aug 2013 B2
8533408 Madnani et al. Sep 2013 B1
8533527 Daikokuya et al. Sep 2013 B2
8539177 Ofer et al. Sep 2013 B1
8544029 Bakke et al. Sep 2013 B2
8549224 Zeryck et al. Oct 2013 B1
8583861 Ofer et al. Nov 2013 B1
8589625 Colgrove et al. Nov 2013 B2
8595455 Chatterjee et al. Nov 2013 B2
8615599 Takefman et al. Dec 2013 B1
8627136 Shankar et al. Jan 2014 B2
8627138 Clark Jan 2014 B1
8639669 Douglis et al. Jan 2014 B1
8639863 Kanapathippillai et al. Jan 2014 B1
8640000 Cypher Jan 2014 B1
8650343 Kanapathippillai et al. Feb 2014 B1
8660131 Vermunt et al. Feb 2014 B2
8661218 Piszczek et al. Feb 2014 B1
8671072 Shah et al. Mar 2014 B1
8689042 Kanapathippillai et al. Apr 2014 B1
8700875 Barron et al. Apr 2014 B1
8706694 Chatterjee et al. Apr 2014 B2
8706914 Duchesneau Apr 2014 B2
8706932 Kanapathippillai et al. Apr 2014 B1
8712963 Douglis et al. Apr 2014 B1
8713405 Healey et al. Apr 2014 B2
8719621 Karmarkar May 2014 B1
8725730 Keeton et al. May 2014 B2
8751859 Becker-szendy et al. Jun 2014 B2
8756387 Frost et al. Jun 2014 B2
8762793 Grube et al. Jun 2014 B2
8838541 Gamble et al. Jun 2014 B2
8769232 Suryabudl et al. Jul 2014 B2
8775858 Gower et al. Jul 2014 B2
8775868 Colgrove et al. Jul 2014 B2
8788913 Xin et al. Jul 2014 B1
8793447 Usgaonkar et al. Jul 2014 B2
8799746 Baker et al. Aug 2014 B2
8819311 Liao Aug 2014 B2
8819383 Jobanputra et al. Aug 2014 B1
8824261 Miller et al. Sep 2014 B1
8832528 Thatcher et al. Sep 2014 B2
8838892 Li Sep 2014 B2
8843700 Salessi et al. Sep 2014 B1
8850108 Hayes et al. Sep 2014 B1
8850288 Lazier et al. Sep 2014 B1
8856593 Eckhardt et al. Oct 2014 B2
8856619 Cypher Oct 2014 B1
8862617 Kesselman Oct 2014 B2
8862847 Feng et al. Oct 2014 B2
8862928 Xavier et al. Oct 2014 B2
8868825 Hayes Oct 2014 B1
8874836 Hayes Oct 2014 B1
8880793 Nagineni Nov 2014 B2
8880825 Lionetti et al. Nov 2014 B2
8886778 Nedved et al. Nov 2014 B2
8898383 Yamamoto et al. Nov 2014 B2
8898388 Kimmel Nov 2014 B1
8904231 Coatney et al. Dec 2014 B2
8918478 Ozzie et al. Dec 2014 B2
8930307 Colgrove et al. Jan 2015 B2
8930633 Amit et al. Jan 2015 B2
8930648 Storer Jan 2015 B1
8943357 Atzmony Jan 2015 B2
8949502 McKnight et al. Feb 2015 B2
8959110 Smith et al. Feb 2015 B2
8959388 Kuang et al. Feb 2015 B1
8972478 Storer et al. Mar 2015 B1
8972779 Lee et al. Mar 2015 B2
8977597 Ganesh et al. Mar 2015 B2
8996828 Kalos et al. Mar 2015 B2
9003144 Hayes Apr 2015 B1
9009724 Gold et al. Apr 2015 B2
9021053 Bembo et al. Apr 2015 B2
9021215 Meir et al. Apr 2015 B2
9025393 Wu May 2015 B2
9043372 Makkar et al. May 2015 B2
9047214 Sharon et al. Jun 2015 B1
9053808 Sprouse Jun 2015 B2
9058155 Cepulis et al. Jun 2015 B2
9063895 Madnani et al. Jun 2015 B1
9063896 Madnani et al. Jun 2015 B1
9098211 Madnani et al. Aug 2015 B1
9110898 Chamness et al. Aug 2015 B1
9110964 Shilane et al. Aug 2015 B1
9116819 Cope et al. Aug 2015 B2
9117536 Yoon Aug 2015 B2
9122401 Zaltsman et al. Sep 2015 B2
9123422 Sharon et al. Sep 2015 B2
9124300 Olbrich et al. Sep 2015 B2
9134908 Horn et al. Sep 2015 B2
9153337 Sutardja Oct 2015 B2
9158472 Kesselman et al. Oct 2015 B2
9159422 Lee et al. Oct 2015 B1
9164891 Karamcheti et al. Oct 2015 B2
9183136 Kawamura et al. Nov 2015 B2
9189650 Jaye et al. Nov 2015 B2
9201733 Verma Dec 2015 B2
9207876 Shu et al. Dec 2015 B2
9229656 Contreras et al. Jan 2016 B1
9229810 He et al. Jan 2016 B2
9235475 Shilane et al. Jan 2016 B1
9244626 Shah et al. Jan 2016 B2
9250999 Barroso Feb 2016 B1
9251066 Colgrove et al. Feb 2016 B2
9268648 Barash et al. Feb 2016 B1
9268806 Kesselman et al. Feb 2016 B1
9286002 Karamcheti et al. Mar 2016 B1
9292214 Kalos et al. Mar 2016 B2
9298760 Li et al. Mar 2016 B1
9304908 Karamcheti et al. Apr 2016 B1
9311969 Murin Apr 2016 B2
9311970 Sharon et al. Apr 2016 B2
9323663 Karamcheti et al. Apr 2016 B2
9323667 Bennett Apr 2016 B2
9323681 Apostolides et al. Apr 2016 B2
9335942 Kumar et al. May 2016 B2
9348538 Mallaiah et al. May 2016 B2
9355022 Ravimohan et al. May 2016 B2
9384082 Lee et al. Jul 2016 B1
9384252 Akirav et al. Jul 2016 B2
9389958 Sundaram et al. Jul 2016 B2
9390019 Patterson et al. Jul 2016 B2
9396202 Drobychev et al. Jul 2016 B1
9400828 Kesselman et al. Jul 2016 B2
9405478 Koseki et al. Aug 2016 B2
9411685 Lee Aug 2016 B2
9417960 Klein Aug 2016 B2
9417963 He et al. Aug 2016 B2
9430250 Hamid et al. Aug 2016 B2
9430542 Aklrav et al. Aug 2016 B2
9432541 Ishida Aug 2016 B2
9454434 Sundaram et al. Sep 2016 B2
9471579 Natanzon Oct 2016 B1
9477554 Chamness et al. Oct 2016 B2
9477632 Du Oct 2016 B2
9495255 Davis Nov 2016 B2
9501398 George et al. Nov 2016 B2
9525737 Friedman Dec 2016 B2
9529542 Friedman et al. Dec 2016 B2
9535631 Fu et al. Jan 2017 B2
9552248 Miller et al. Jan 2017 B2
9552291 Munetoh et al. Jan 2017 B2
9552299 Stalzer Jan 2017 B2
9563517 Natanzon et al. Feb 2017 B1
9588698 Karamcheti et al. Mar 2017 B1
9588712 Kalos et al. Mar 2017 B2
9594652 Sathiamoorthy et al. Mar 2017 B1
9600193 Ahrens et al. Mar 2017 B2
9612952 Hayes Apr 2017 B2
9619321 Sharon et al. Apr 2017 B1
9619430 Kannan et al. Apr 2017 B2
9645754 Li et al. May 2017 B2
9667720 Bent et al. May 2017 B1
9710535 Aizman et al. Jul 2017 B2
9733840 Karamcheti et al. Aug 2017 B2
9734225 Akirav et al. Aug 2017 B2
9740403 Storer et al. Aug 2017 B2
9740700 Chopra et al. Aug 2017 B1
9740762 Horowitz et al. Aug 2017 B2
9747319 Bestler et al. Aug 2017 B2
9747320 Kesselman Aug 2017 B2
9767130 Bestler et al. Sep 2017 B2
9781227 Friedman et al. Oct 2017 B2
9785498 Misra et al. Oct 2017 B2
9798486 Singh Oct 2017 B1
9804925 Carmi et al. Oct 2017 B1
9811285 Karamcheti et al. Nov 2017 B1
9811546 Bent et al. Nov 2017 B1
9818478 Chung Nov 2017 B2
9829066 Herman Nov 2017 B2
9836245 Hayes et al. Dec 2017 B2
9891854 Munetoh et al. Feb 2018 B2
9891860 Delgado et al. Feb 2018 B1
9892005 Kedem et al. Feb 2018 B2
9892186 Akirav et al. Feb 2018 B2
9904589 Donlan et al. Feb 2018 B1
9904717 Anglin et al. Feb 2018 B2
9952809 Shah Feb 2018 B2
9910748 Pan Mar 2018 B2
9910904 Anglin et al. Mar 2018 B2
9934237 Shilane et al. Apr 2018 B1
9940065 Kalos et al. Apr 2018 B2
9946604 Glass Apr 2018 B1
9959167 Donlan et al. May 2018 B1
9965539 D'halluin et al. May 2018 B2
9998539 Brock et al. Jun 2018 B1
10007457 Hayes et al. Jun 2018 B2
10013177 Liu et al. Jul 2018 B2
10013311 Sundaram et al. Jul 2018 B2
10019314 Yang et al. Jul 2018 B2
10019317 Usvyatsky et al. Jul 2018 B2
10031703 Natanzon et al. Jul 2018 B1
10061512 Lin Aug 2018 B2
10073626 Karamcheti et al. Sep 2018 B2
10082985 Hayes et al. Sep 2018 B2
10089012 Chen et al. Oct 2018 B1
10089174 Yang Oct 2018 B2
10089176 Donlan et al. Oct 2018 B1
10108819 Donlan et al. Oct 2018 B1
10146787 Bashyam et al. Dec 2018 B2
10152268 Chakraborty et al. Dec 2018 B1
10157098 Yang et al. Dec 2018 B2
10162704 Kirschner et al. Dec 2018 B1
10180875 Klein Jan 2019 B2
10185730 Bestler et al. Jan 2019 B2
10235065 Miller et al. Mar 2019 B1
10572176 Davis Feb 2020 B2
20020144059 Kendall Oct 2002 A1
20030105984 Masuyama et al. Jun 2003 A1
20030110205 Johnson Jun 2003 A1
20040161086 Buntin et al. Aug 2004 A1
20050001652 Malik et al. Jan 2005 A1
20050076228 Davis et al. Apr 2005 A1
20050235132 Karr et al. Oct 2005 A1
20050278460 Shin et al. Dec 2005 A1
20050283649 Turner et al. Dec 2005 A1
20060015683 Ashmore et al. Jan 2006 A1
20060114930 Lucas et al. Jun 2006 A1
20060174157 Barrall et al. Aug 2006 A1
20060248294 Nedved et al. Nov 2006 A1
20070079068 Draggon Apr 2007 A1
20070214194 Reuter Sep 2007 A1
20070214314 Reuter Sep 2007 A1
20070234016 Davis et al. Oct 2007 A1
20070268905 Baker et al. Nov 2007 A1
20080046538 Susarla Feb 2008 A1
20080049542 Lee Feb 2008 A1
20080080709 Michtchenko et al. Apr 2008 A1
20080107274 Worthy May 2008 A1
20080155191 Anderson et al. Jun 2008 A1
20080295118 Liao Nov 2008 A1
20090077208 Nguyen et al. Mar 2009 A1
20090138654 Sutardja May 2009 A1
20090216910 Duchesneau Aug 2009 A1
20090216920 Lauterbach et al. Aug 2009 A1
20100017444 Chatterjee et al. Jan 2010 A1
20100042636 Lu Feb 2010 A1
20100094806 Apostolides et al. Apr 2010 A1
20100115070 Missimilly May 2010 A1
20100125695 Wu et al. May 2010 A1
20100162076 Sim-Tang et al. Jun 2010 A1
20100169707 Mathew et al. Jul 2010 A1
20100174576 Naylor Jul 2010 A1
20100268908 Ouyang et al. Oct 2010 A1
20110040925 Frost et al. Feb 2011 A1
20110060927 Fillingim et al. Mar 2011 A1
20110119462 Leach et al. May 2011 A1
20110219170 Frost et al. Sep 2011 A1
20110238625 Hamaguchi et al. Sep 2011 A1
20110264843 Haines et al. Oct 2011 A1
20110302369 Goto et al. Dec 2011 A1
20120011398 Eckhardt Jan 2012 A1
20120079318 Colgrove et al. Mar 2012 A1
20120089567 Takahashi et al. Apr 2012 A1
20120110249 Jeong et al. May 2012 A1
20120131253 McKnight May 2012 A1
20120158923 Mohamed et al. Jun 2012 A1
20120191900 Kunimatsu et al. Jul 2012 A1
20120198152 Terry et al. Aug 2012 A1
20120198261 Brown et al. Aug 2012 A1
20120209943 Jung Aug 2012 A1
20120226934 Rao Sep 2012 A1
20120246435 Meir et al. Sep 2012 A1
20120260055 Murase Oct 2012 A1
20120311557 Resch Dec 2012 A1
20130022201 Glew et al. Jan 2013 A1
20130036314 Glew et al. Feb 2013 A1
20130042056 Shats Feb 2013 A1
20130060884 Bernbo et al. Mar 2013 A1
20130067188 Mehra et al. Mar 2013 A1
20130073894 Xavier et al. Mar 2013 A1
20130124776 Hallak et al. May 2013 A1
20130132800 Healey et al. May 2013 A1
20130151653 Sawicki Jun 2013 A1
20130151771 Tsukahara et al. Jun 2013 A1
20130173853 Ungureanu et al. Jul 2013 A1
20130238554 Yucel et al. Sep 2013 A1
20130339314 Carpenter et al. Dec 2013 A1
20130339635 Amit et al. Dec 2013 A1
20130339818 Baker et al. Dec 2013 A1
20140032992 Hara Jan 2014 A1
20140040535 Lee Feb 2014 A1
20140040702 He et al. Feb 2014 A1
20140047263 Coatney et al. Feb 2014 A1
20140047269 Kim Feb 2014 A1
20140063721 Herman et al. Mar 2014 A1
20140064048 Cohen et al. Mar 2014 A1
20140068224 Fan et al. Mar 2014 A1
20140075252 Luo et al. Mar 2014 A1
20140122510 Namkoong et al. May 2014 A1
20140136880 Shankar et al. May 2014 A1
20140181402 White Jun 2014 A1
20140237164 Le et al. Aug 2014 A1
20140237168 Prins Aug 2014 A1
20140279936 Bernbo et al. Sep 2014 A1
20140280025 Eidson et al. Sep 2014 A1
20140289588 Nagadomi et al. Sep 2014 A1
20140330785 Isherwood et al. Nov 2014 A1
20140372838 Lou et al. Dec 2014 A1
20140380125 Calder et al. Dec 2014 A1
20140380126 Yekhanin et al. Dec 2014 A1
20150032720 James Jan 2015 A1
20150039645 Lewis Feb 2015 A1
20150039849 Lewis Feb 2015 A1
20150089283 Kermarrec et al. Mar 2015 A1
20150100746 Rychlik Apr 2015 A1
20150134824 Mickens May 2015 A1
20150153800 Lucas et al. Jun 2015 A1
20150180714 Chunn Jun 2015 A1
20150280959 Vincent Oct 2015 A1
20150310921 Melik-Martirosian Oct 2015 A1
20160191508 Bestler et al. Jun 2016 A1
20160246537 Kim Aug 2016 A1
20160378612 Hipsh et al. Dec 2016 A1
20170091236 Hayes et al. Mar 2017 A1
20170103092 Hu et al. Apr 2017 A1
20170103094 Hu et al. Apr 2017 A1
20170103098 Hu et al. Apr 2017 A1
20170103116 Hu et al. Apr 2017 A1
20170177236 Cai et al. Jun 2017 A1
20180039442 Shadrin et al. Feb 2018 A1
20180081958 Akirav et al. Mar 2018 A1
20180101441 Hyun et al. Apr 2018 A1
20180101587 Anglin et al. Apr 2018 A1
20180101588 Anglin et al. Apr 2018 A1
20180217756 Liu et al. Aug 2018 A1
20180307560 Vishnumolakala et al. Oct 2018 A1
20180321874 Li et al. Nov 2018 A1
20190036703 Bestler Jan 2019 A1
Foreign Referenced Citations (6)
Number Date Country
2164006 Mar 2010 EP
2256621 Dec 2010 EP
WO 02-13033 Feb 2002 WO
WO 2008103569 Aug 2008 WO
WO 2008157081 Dec 2008 WO
WO 2013032825 Jul 2013 WO
Non-Patent Literature Citations (25)
Entry
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/023485, dated Jul. 21, 2016.
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/033306, dated Aug. 19, 2016.
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/047808, dated Nov. 25, 2016.
Stalzer, Mark A., “FlashBlades: System Architecture and Applications,” Proceedings of the 2nd Workshop on Architectures and Systems for Big Data, Association for Computing Machinery, New York, NY, 2012, pp. 10-14.
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/042147, dated Nov. 30, 2016.
Hwang, Kai, et al. “RAID-x: A New Distributed Disk Array for I/O-Centric Cluster Computing,” HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing, IEEE, 2000, pp. 279-286.
Schmid, Patrick: “RAID Scaling Charts, Part 3:4-128 kB Stripes Compared”, Tom's Hardware, Nov. 27, 2007 (http://www.tomshardware.com/reviews/RAID-SCALING-CHARTS.1735-4.html), See pp. 1-2.
Storer, Mark W. et al., “Pergamum: Replacing Tape with Energy Efficient, Reliable, Disk-Based Archival Storage,” Fast '08: 6th USENIX Conference on File and Storage Technologies, San Jose, CA, Feb. 26-29, 2008 pp. 1-16.
Ju-Kyeong Kim et al., “Data Access Frequency based Data Replication Method using Erasure Codes in Cloud Storage System”, Journal of the Institute of Electronics and Information Engineers, Feb. 2014, vol. 51, No. 2, pp. 85-91.
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/018169, dated May 15, 2015.
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/034302, dated Sep. 11, 2015.
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/039135, dated Sep. 18, 2015.
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/039136, dated Sep. 23, 2015.
International Search Report, PCT/US2015/039142, dated Sep. 24, 2015.
International Search Report, PCT/US2015/034291, dated Sep. 30, 2015.
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/039137, dated Oct. 1, 2015.
International Search Report, PCT/US2015/044370, dated Dec. 15, 2015.
International Search Report amd the Written Opinion of the International Searching Authority, PCT/US2016/031039, dated May 5, 2016.
International Search Report, PCT/US2016/014604, dated May 19, 2016.
International Search Report, PCT/US2016/014361, dated May 30, 2016.
International Search Report, PCT/US2016/014356, dated Jun. 28, 2016.
International Search Report, PCT/US2016/014357, dated Jun. 29, 2016.
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/016504, dated Jul. 6, 2016.
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/024391, dated Jul. 12, 2016.
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/026529, dated Jul. 19, 2016.
Related Publications (1)
Number Date Country
20200192577 A1 Jun 2020 US
Continuations (2)
Number Date Country
Parent 15830984 Dec 2017 US
Child 16797443 US
Parent 14322891 Jul 2014 US
Child 15830984 US