Transactional memory for distributed shared memory multi-processor computer systems

Information

  • Patent Grant
  • 6360231
  • Patent Number
    6,360,231
  • Date Filed
    Friday, February 26, 1999
    25 years ago
  • Date Issued
    Tuesday, March 19, 2002
    22 years ago
Abstract
A cache coherent distributed shared memory multi-processor computer system is provided which supports transactional memory semantics. A cache flushing engine and temporary buffer allow selective forced write-backs of dirty cache lines to the home memory. A flush can be performed from the updated cache to the temporary buffer and then to the home memory after confirmation of receipt or from the updated cache to the home memory directly with the temporary buffer holding the old data until confirmation that the home memory contains the update.
Description




TECHNICAL FIELD




The present invention relates generally to multi-processor computer systems and more particularly to system control units.




BACKGROUND ART




High performance, multi-processor computer systems with a large number of microprocessors are built by interconnecting a number of node structures, each node containing a subset of the processors and memory in the system. While the memory in the system is distributed, several of these systems support a shared memory abstraction where all the memory in the system appears as a large memory common to all processors in the system. To support high-performance, these systems typically allow processors to maintain copies of memory data in their local caches. Since multiple processors can cache the same data, these systems must incorporate a cache coherence mechanism to keep the copies coherent.




In some cache-coherent systems, each memory block (typically a portion of memory tens of bytes in size) is assigned a “home node”, which maintains all necessary global information for that memory block, manages the sharing of that memory block, and guarantees its coherence. The home node maintains a directory, which identifies the nodes that possess a copy of the memory block. When a node requires a copy of the memory block, it requests the memory block from its local, private cache. If the data is found, the memory access is resolved locally. Otherwise, a remote memory access is performed to the home node. The home node supplies the data from memory if its memory has the latest data. If another node has the latest copy of the data, the home node directs this node to forward the data to the requesting node. The data is then stored in the local cache of the requesting node.




In cache-coherent systems, multiple copies of the same memory block can exist in different nodes. These copies must be read-only and identical to the home memory copy. They are called “clean” copies in a “shared” state.




When a processor updates its local cache copy, it must ensure that all other copies are invalidated. Consequently, the processor has an ‘exclusive” and “modified” data copy, which hold the most recent value of the data. The other copies of the memory block are “stale”. The updating processor then becomes the “owner” of the memory block.




The home node employs a coherence protocol to ensure that when a node writes a new value to the memory block, all other nodes see this latest value. Coherence controllers implement this coherence functionality. First, they implement a coherence controller for each memory unit, which maintains coherence of all memory blocks in that memory unit. Second, the functionality of the coherence controller is integrated with the functionality of the System Control Unit (SCU) of the associated memory unit.




The SCU provides the control and the path for data movement for the following sources and destinations within the node: the processors within the node; the local (node) portion of the memory system; the network connecting all of the nodes of the multi-processor computer system; and the input/output (I/O) system of the local node.




However, the state-of-art cache-coherent shared-memory multiprocessor system designs do not have good support for data integrity. Consider that a process executes the following code:




LOCK




update global data A;




update global data B;




update global data C;




UNLOCK




The above code can be simply considered as a “transaction”. Execution of the transaction causes that the local cache of the executing processor has the most recent data values of locations A, B, and C. the home memory of locations A, B, and C have stale data copies. Unfortunately, if the local node fails, it means that the most recent values of locations A, B, and C are lost. In the worst case, the new value of location A is reflected back to its home memory, and the new changes for B and C are lost. As a result, the global data structure is corrupted or partially updated with incomplete information.




Note that this problem of data integrity is not caused by the failure of resources, in this case the home memory which exports locations A, B, and C. Instead, the problem is due to the failure of nodes/processes which use the resources.




Under many situations, the software may demand the semantics of “transactional memory”. In brief, a transaction performed on global data structures consists of a “request” phase, an “execution” phase and finally a “commit” phase. The new changes are considered globally complete and visible only after the transaction is committed. If any failure occurs before the transaction commits, the system state is rolled back to the state right before the transaction begins.




For the exemplified transaction, it is clear that the LOCK operation defines where the original system state is and where the request phase begins. The UNLOCK operation indicates where the update operations must commit. Specifically, before the LOCK is released, the home memory of A, B, and C is either completely updated with the new values, or is unchanged. Given this “All-or-None” semantics, all processes will observe either the original state before the LOCK, or the new state defined by the execution of the transaction.




Thus, a system has been long sought and long eluded those skilled in the art, which would provide an efficient implementation of transactional memory.




DISCLOSURE OF THE INVENTION




The present invention provides a cache coherent distributed shared memory multi-processor computer system which supports transactional memory semantics.




The present invention also provides a cache coherent distributed shared memory multi-processor computer system which supports transactional memory semantics with a cache flushing engine.




The present invention further provides a cache coherent distributed shared memory multi-processor computer system which allows programmers to selective force write-backs of dirty cache lines to the home memory.




The above and additional advantages of the present invention will become apparent to those skilled in the art from a reading of the following detailed description when taken in conjunction with the accompanying drawings.











BRIEF DESCRIPTION OF THE DRAWINGS





FIG. 1

is a cache coherent Distributed Shared Memory (DSM) multi-processor computer system according to the present invention;





FIG. 2

is a functional block diagram of the operational components of the transactional memory according to the present invention;





FIG. 3

is the functional block diagram of the operational components of the transactional memory in the backup operation in an alternate mode of the present invention; and





FIG. 4

is a functional block diagram of the operational components of the transactional memory in the flushing operation in the alternate mode of the present invention.











BEST MODES FOR CARRYING OUT THE INVENTION




Referring now to

FIG. 1

, therein is shown a cache coherent Distributed Shared Memory (ccDSM) multi-processor computer system


100


. It should be understood that the system shown is for illustrative purposes only since the present invention is applicable to all architecture designs with caches. The multi-processor computer system


100


has a plurality of nodes of which the nodes


200


,


300


, and


400


through


500


(with only the first and last nodes shown for nodes


400


through


500


). The nodes


200


, etc. are connected to an interconnect


600


, which is part of an interconnection network which includes crossbar switches and links as are well known to those skilled in the art.




Each node contains a plurality of processors and caches. For example, the node


200


contains processors


201


through


204


(with only the first and last processors shown) and respective caches


205


through


208


(with only the first and last processors shown). The caches are connected to a System Control Unit (SCU)


210


. The SCU


210


is connected to a memory


212


and a temporary buffer


214


. The SCU


210


provides the control and the path for data movement for various sources and destinations within the node


200


. The sources and destinations include: the processors


210


through


204


within the node; the local node memory


212


; the interconnect


600


; and the input/output (I/O) system of the local node (not shown). The SCU


210


further contains a cache flushing engine (CFE)


220


.




Similarly, the node


300


contains processors


301


through


304


(with only the first and last processors shown) and respective caches


305


through


308


(with only the first and last processors shown). The caches are connected to a System Control Unit (SCU)


310


. The SCU


310


is connected to a memory


312


and a temporary buffer


315


. The SCU


310


provides the control and the path for data movement for various sources and destinations within the node


300


. The SCU


310


further contains a cache flushing engine (CFE)


320


.




The other nodes


400


,


500


, etc. are the same as the nodes


200


and


300


.




Referring now to

FIG. 2

, therein is shown a functional block diagram of the operational components of the transactional memory according to the present invention. Herein, the node


200


is designated as a requesting node and the node


300


is designated as a home node. Initially, the requesting and home nodes have the same specified values in memory locations A, B, and C.




After an update, it is possible that the local cache of the requesting node, such as cache


205


, may have the most recent values of location A, B, and C inputted by the processor


201


. The home node then has stale data copies in its memory


302


. By issuing a “flush A, B, C” command as indicated by arrow


250


, the CFE


220


will force, or “flush”, the local cache


205


to write back the new values for locations A, B, and C to the temporary buffer


315


in the home node. The write back will be along “flush_req A, B, and C” arrow


252


from the SCU


210


to the SCU


310


through to the temporary buffer


315


.




After the new values are written into the temporary buffer


315


, the home node, or node


300


, acknowledges with an “ack” signal back to the requesting node, node


200


, as indicated by arrow


254


that all the new values have been successfully captured. Upon receiving the acknowledgement, the receiving node will issue a “request-to-commit” request as indicated by arrow


256


. This will cause the home node SCU


310


to copy the new values from the temporary buffer


315


to the actual memory locations for A, B, and C in the memory


312


.




Finally, the home node SCU


310


acknowledges with a “commit” message along arrow


260


to indicate that the transaction has been completed.




The software is developed with semantics of transactional memory so the code is:




LOCK




update A, B, and C;




flush A, B, C;




sync;




UNLOCK




Referring now to

FIG. 3

, therein is shown the functional block diagram of the operational components of the transactional memory in the backup operation in an alternate mode of the present invention. The architecture is the same as shown in FIG.


2


and the components have the same numbers.




After an update, the local cache of the requesting node, such as cache


205


, has the most recent values of location A, B, and C. The CFE


220


receives a “backup A, B, C” instruction


262


and records the caches that are potentially to be updated and flushed. The CFE


220


then sends a backup required instruction as indicated by “backup_req A, B, C” arrow


264


to the home memory


302


in the home node SCU


310


. The old values of the affected memory locations of the home memory


302


are then copied into the temporary buffer


315


as indicated by arrow


266


to prevent their loss in case of a failure before the transaction is completed. The SRU


310


then sends an acknowledgement that the backup is complete as indicated by “ack” arrow


268


.




Referring now to

FIG. 4

, therein is shown the functional block diagram of the operational components of the transactional memory in the flushing operation of an alternate mode of the present invention.




After the backup operations of

FIG. 3

, the local cache


205


in the requesting node, node


500


, will have the most recent values of locations A, B, and C. By issuing a “flush and synchronize” command as indicated by arrow


270


, the CFE


220


forces the local cache


205


to write back the new value of A, B, and C as indicated by “flush_req A, B, and C” arrow


272


to the home node memory


312


.




After the new values are written into the home node memory


312


, the home node


300


, acknowledges with an “ack” signal as indicated by arrow


274


that all the new values have been successfully captured. Upon receiving the acknowledgement, the receiving node will issue a “request-to-commit” request as indicated by arrow


276


. Finally, the home node SCU


310


acknowledges with a “commit” message along arrow


278


to indicate that the transaction has been completed.




If the transaction fails, the SRU


310


will retrieve the original values from the temporary buffer


315


and place them back in the memory


312


.




The software is developed with semantics of transactional memory so the code is:




LOCK




Backup A, B, and C;




update A, B, and C;




flush&sync;




UNLOCK




While the invention has been described in conjunction with a specific best mode, it is to be understood that many alternatives, modifications, and variations will be apparent to those skilled in the art in light of the aforegoing description. Accordingly, it is intended to embrace all such alternatives, modifications, and variations which fall within the spirit and scope of the included claims. All matters set forth herein or shown in the accompanying drawings are to be interpreted in an illustrative and non-limiting sense.



Claims
  • 1. A transactional memory control method for multi-processor computer system having requesting and home nodes comprising the steps of:loading a new value for a location in memory into local cache in the requesting node; forcing said local cache in the requesting node to write back said new value for said location to the home node; acknowledging the capture of the new value from the home node to the requesting node; requesting a commit instruction from the requesting node to the home node in response to said acknowledging of the capture of the new value; copying the new value for said location into memory in the home node in response to said step of requesting a commit instruction; sending a commit instruction from the home node to the requesting node to complete the transaction.
  • 2. The transactional memory control method as claimed in claim 1 wherein the step of:said forcing said local cache in the requesting node to write back said new value for said location to the home node writes back through a system control unit to a temporary buffer.
  • 3. The transactional memory control method as claimed in claim 1 wherein the step of:said requesting a commit instruction from the requesting node to the home node in response to said acknowledging of the capture of the new value causes said new value to be transferred from a temporary buffer of said home node to the memory thereof.
  • 4. A transactional memory control method for multi-processor computer system having requesting and home nodes comprising the steps of:loading a new value for a location in memory into local cache in the requesting node; forcing said local cache in the requesting node to write back said new value for said location to the home node; copying an old value in memory in the home node into a temporary buffer therein; copying the new value for said location into memory in the home node; acknowledging the capture of the new value from the home node to the requesting node; requesting a commit instruction from the receiving node to the home node in response to said acknowledging of the capture of the new value; and sending a commit instruction from the home node to the requesting node to complete the transaction.
  • 5. The transactional memory control method as claimed in claim 4 wherein the step of:said forcing said local cache in the requesting node to write back said new value for said location to the home node writes back through a system control unit to the memory of the home node.
  • 6. The transactional memory control method as claimed in claim 4 wherein the step of:said forcing said local cache in the requesting node to write back said new value for said location to the home node causes an old value in the memory to be transferred from the memory of said home node to a temporary buffer thereof.
CROSS-REFERENCE TO RELATED APPLICATIONS

The present application contains subject matter related to a pending U.S. patent application Ser. No. 09/258,549, entitled “Cache Flushing Engine for Distributed Shared Memory Multi-processor Computer Systems” by F. Pong, L. Russell, and T. Nguyen. This application was filed contemporaneously herewith, is hereby incorporated by reference.

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5329626 Klein et al. Jul 1994 A
5335343 Lampson et al. Aug 1994 A
6049889 Steely, Jr. et al. Apr 2000 A
6055605 Sharma et al. Apr 2000 A
Non-Patent Literature Citations (1)
Entry
Data Concurrency Control in Distributed Data Networks. Dec. 1981, IBM Technical Disclosure Bul letin, vol. 24 No. 7A, pp. 3137-3139.