1. Field
The present disclosure relates to hash table data structures. More particularly, the disclosure concerns adaptive hash table resizing and modifying for hash tables that support concurrent access by readers and writers using the read-copy update synchronization mechanism.
2. Description of the Prior Art
By way of background, hash tables provide useful data structures for many applications, with various convenient properties such as constant average time for accesses and modifications. When a hash table is shared for reading and writing by concurrent applications, a suitable synchronization mechanism is required to maintain internal consistency. One technique for supporting concurrent hash table access comes in the form of Read-Copy Update (RCU). RCU is a synchronization mechanism with very low overhead for readers, and thus works particularly well for data structures with significantly more reads than writes, such as hash tables. These properties allow RCU-protected hash tables to scale well to many threads on many processors.
RCU-protected hash tables are implemented using open chaining, with RCU-protected linked lists being provided for the hash buckets. Readers traverse these linked lists without using locks, atomic operations or other forms of mutual exclusion. Writers performing updates to hash table elements protect the readers by waiting for a grace period to elapse before freeing any stale data that the readers may have been referencing.
A challenge respecting RCU-protected hash tables is the need to support efficient hash table resizing. The ability to dynamically resize a hash table stems from the fact that the performance and suitability of hash tables depend heavily on choosing the appropriate size for the table. Making a hash table too small will lead to excessively long hash chains and poor performance. Making a hash table too large will consume too much memory, reducing the memory available for other applications or performance-improving caches, and increasing hardware requirements. Many systems and applications cannot know the proper size of a hash table in advance. Software designed for use on a wide range of system configurations with varying needs may not have the option of choosing a single hash table size suitable for all supported system configurations. Furthermore, the needs of a system may change at run time due to numerous factors, and software must scale both up and down dynamically to meet these needs. For example, in a system that supports virtual computing environments, the ability to shrink a hash table can be particularly important so that memory can be reallocated from one virtual environment to another.
Resizing an RCU-protected hash table so as to either increase or decrease the hash table size results in hash buckets being respectively added to or removed from the hash table, with a corresponding change being made to the hash function. This usually entails one or more hash table elements having to be relocated to a different hash bucket, which can be disruptive to readers if care is not taken to protect their operations during the resizing operation. Existing RCU-protected hash tables support reader-friendly hash table resizing using several approaches. However, there are shortcomings that are variously associated with these approaches, such as (1) the need to maintain duplicate sets of per-element list links, thereby increasing the hash table memory foot print, (2) the need to incur large numbers of grace period delays and require readers to search two hash table versions during resizing, and (3) the need to copy data hash table elements, which makes it difficult or impossible for readers to maintain long-lived references to such elements. The present disclosure presents a new technique that enables optimized resizing of RCU-protected hash tables while permitting concurrent read access without any of the above deficiencies, and also while permitting insertion and deletion operations to proceed during resizing.
A method, system and computer program product are provided for concurrently resizing and modifying an RCU-protected hash table stored in a memory. According to the disclosed technique, a second RCU-protected hash table is allocated in the memory. The second hash table represents a resized version of said first hash table that has a different number of hash buckets than the first hash table, the second hash table buckets being defined but initially having no hash table elements. The second hash table is populated by linking each hash bucket of the second hash table to all hash buckets of the first hash table containing elements that hash to the second hash bucket. The second hash table is then published so that it is available for searching by hash table readers. If the modifying comprises inserting a new hash table element, the element is inserted at the head of a corresponding bucket in the second hash table. If the modifying comprises deleting an existing hash table element, an RCU read-side critical section is entered, all pointers in one or more hash buckets of the first hash table and the second hash table that reference the existing hash table element are removed or redirected, the RCU read-side critical section is exited, and the existing hash table element is freed from memory after waiting for a grace period which guarantees that no readers searching the first hash table or the second hash table will be referencing the existing hash table element. The first hash table is freed from memory after waiting for a grace period which guarantees that no readers searching the first hash table will be affected by the freeing.
In an embodiment, the modifying includes first determining whether resizing is underway, and if not, performing the modifying on the first hash table only. Determining whether resizing is underway may be performed after acquiring a lock on a hash bucket in the first hash table where the modifying is to be performed, and releasing the first lock if resizing is determined to be underway. If the modifying comprises inserting a new hash table element, a lock may be acquired on a hash bucket in the second hash table where the inserting is to be performed. If the modifying comprises deleting an existing hash table element, locks may be acquired on all hash buckets in the first hash table and the second hash table where the pointer removing or redirecting is to be performed. The modifying may further include performing an action to prevent starvation by successive resizing invocations.
The foregoing and other features and advantages will be apparent from the following more particular description of example embodiments, as illustrated in the accompanying Drawings, in which:
Introduction
Example embodiments will now be described for dynamically resizing RCU-protected hash tables in a manner that supports optimized deletion and insertion of hash table elements during a resizing operation. The RCU-protected hash table resizing technique disclosed herein offers the following advantages:
(1) Hash table elements need not be copied during a resize operation, thereby avoiding expansion of the read-side cache footprint while still allowing long-lived references to any given element;
(2) Readers need only search a single hash chain, even during a resize operation;
(3) An expanding resize operation can handle multiple items per RCU grace period in order to minimize the number of RCU grace periods required;
(4) Each hash table element need only maintain one set of list pointers; and
(5) Insertion and deletion operations may proceed during a resizing operation.
In order to achieve these benefits, an approach is taken wherein any resizing-induced changes to the hash function are restricted so that a given hash bucket in the hash table prior to resizing will map to a predictable bucket or set of buckets in the hash table subsequent to resizing. This restriction allows a hash table to be resized using cross-linking operations in which the hash table elements are neither copied nor moved around in memory. Instead, resizing occurs in an incremental fashion so that readers see consistent hash bucket lists with all applicable hash table elements at all times. The approach waits for grace periods between certain steps of the resizing operation in order to guarantee that readers see a sufficiently consistent view of the hash table. Using the disclosed technique, shrinking a hash table requires only a single grace period. Enlarging a hash table requires only a limited number of grace periods that does not exceed the number of hash table elements in the longest hash chain.
In both cases, a new resized hash table is created and co-exists with the original hash table during the resizing operation. The insertion of a hash table element during a resizing operation can be handled by adding the element at the head of the corresponding bucket that the element hashes to in the new hash table. The deletion of a hash table element can be handled by removing all links to the affected element in the corresponding buckets that the element hashes to in both the original and new hash tables. The deletion operation is performed within an RCU read-side critical section in order to guarantee the continued existence of the original hash table and also to avoid being starved by a closely-spaced sequence of resize operations. The insertion operation does not need to be performed within an RCU read-side critical section, but may benefit from doing so if starvation of the insertion operation due to closely-spaced resizing operations is a concern. Per-bucket locks are obtained when both inserting or deleting elements in a given hash bucket.
Resizing an RCU-Protected Hash Table by Shrinking
To shrink an RCU-protected hash table, an updater may perform the example operations 2-16 shown in
As shown in block 2 of
As shown in block 8 of
At this point, if a reader were to access the new hash table H2, it would find all of the elements of the original hash table H1. It is therefore safe to set the size of the new hash table H2 and publish it as a valid hash table that replaces the original hash table H1 (e.g., using the rcu_assign_pointer( ) primitive). These operations are shown in blocks 12 and 14 of
Resizing an RCU-Protected Hash Table by Expanding
To expand an RCU-protected hash table, an updater may perform the example operations 20-44 shown in
As shown in block 22 of
As shown in block 28 of
Blocks 34-44 of
Before reiterating blocks 38-42 with respect to the next bucket in the new hash table H2 (per block 36), block 44 waits for a grace period (e.g., by calling a primitive such as synchronize_rcu( ) or synchronize_rcu_expedited( )). The grace period is needed because the next iteration will link element n2 to element n4, thereby removing the existing link from element n2 to element n3. Without the grace period, a reader that is referencing element n2 but searching for odd-numbered hash table elements would be unable to continue its search when element n2 is relinked from element n3 to element n4.
Insertion while Resizing an RCU-Protected Hash Table
Inserting a hash table element while resizing a hash table using the above resizing techniques can be handled by inserting at the head of the corresponding bucket that the element hashes to in the new hash table. This presumes that the new hash table has reached the stage of being published. When shrinking a hash table, publication of the new hash table occurs in block 14 of
One approach is to have the insertion operation check a per-bucket flag that indicates whether or not resizing is underway. This flag would be set on the hash buckets of the original hash table by the resizing operation. The resizing operation may use per-bucket resizing locks to synchronize with other resizing operations, with each bucket involved in a resizing operation being locked prior to that bucket being processed. In that case, the per-bucket flags could be set as each bucket's resizing lock is acquired. A global flag on the hash table itself could also be used in lieu of per-bucket flags. A second approach that may also be combined with per-bucket locking during resizing operations is to have a global integer that indicates the largest-index bucket of the original hash table whose resizing locked has been acquired by a resizing operation. This index can be incremented to reference a given bucket only if the bucket's resizing lock is held. The insertion operation would first obtain an insertion lock on a bucket in the original hash table and check the global integer. If the global integer is less than the bucket's index, the resizing operation has not yet processed the bucket and the new hash table element is therefore inserted at the head of the corresponding bucket of the original hash table. Otherwise, the new hash table element is inserted at the head of the corresponding bucket of the new hash table. A third approach checks the pointers that have been assigned to the original and new hash tables. If both pointers are non-NULL, then resizing is in progress. Note that only one of these pointers need be used by readers searching the hash table.
In all of the foregoing approaches, if a hash table element is to be inserted in the new hash table, the insertion lock for the old hash table's corresponding bucket is dropped and that of the new hash table's bucket is acquired. It may then be desirable to recheck to see if a new resize operation has started in the meantime. If a given insertion operation collides with too many different resize operations, the insertion operation can avoid starvation by acquiring the per-bucket resizing lock used by resizing operations. Alternatively, starvation of the insertion operation can be avoided by performing the insertion operation within an RCU read-side critical section. Because each resizing operation contains at least one wait for a grace period, no more than one resizing operation can complete concurrently with such an insertion. Nevertheless, it still may be desirable to recheck after acquiring a new hash table's bucket lock. For example, if the final grace period of the resizing operation is performed after dropping the resizing lock, it is possible that the next resizing operation has proceeded far enough to require switching again to the next new hash table version. Although the resizing of a hash table multiple times in quick succession may be somewhat unlikely, such operations could result from repeated insertion and deletion operations being performed in a short time span.
Deletion while Resizing an RCU-Protected Hash Table
Deletion while a hash table is being resized using the above-described resizing techniques requires the removal or redirection of all pointers to the hash table element being deleted in both the original and new hash tables (including reverse pointers if the hash bucket containing the element is implemented as a doubly-linked list). This operation is performed within an RCU read-side critical section to prevent the concurrent resizing operation from freeing the original hash table while it is being referenced by the deletion operation. After exiting the RCU read-side critical section and waiting for a grace period, the deleted element may be freed. The foregoing processing presumes that the new hash table has reached the stage of being published. As discussed above, when shrinking a hash table, publication of the new hash table occurs in block 14 of
Readers
Advantageously, the foregoing resizing techniques allow readers to perform concurrent read operations during hash table resizing without incurring any significant overhead. To access an RCU-protected hash table for reading, the reader initiates an RCU read-side critical section, for example, using the rcu_read_lock( ) primitive. The only additional step required of the reader is to snapshot the original hash table pointer in case an updater replaces the pointer during the reader's lookup operation. This represents a simple fetch and store sequence to create a local copy of the pointer. Once the reader has done this, it may search the hash table in conventional fashion, as by (1) hashing the desired key, modulo the number of buckets, (2) searching for the corresponding hash bucket, (3) traversing the hash bucket's linked list, comparing each element's key to the desired key, and (4) carrying out the desired read operation on the hash table element whose key matches the desired key. Thereafter, the reader may exit the RCU read-side critical section, for example, using the rcu_read_unlock( ) primitive. In this way, readers search only one hash bucket, as required.
Example Computing Environment
Turning now to the
The computer system 102 may represent any of several different types of computing apparatus. Examples of such apparatus include, but are not limited to, general purpose computers, special purpose computers, portable computing devices, communication and/or media player devices, set-top devices, embedded systems, and other types of information handling machines. The term “processor” as used with reference to the processors 1041, 1042 . . . 104n encompasses any logical execution unit capable of executing program instructions, including but not limited to a packaged integrated circuit device (such as a microprocessor), a processing core within a packaged integrated circuit device (such as a microprocessor core), or a hardware thread comprising one or more functional units within a processing core (such as an SMT thread). The processors 1041, 1042 . . . 104n may be situated within a single computing device or node (e.g., as part of a single-node SMP system) or they may be distributed over plural nodes (e.g., as part of a NUMA system, a cluster, or a cloud). The memory 8 may comprise any type of tangible storage medium capable of storing data in computer readable form for use in program execution, including but not limited to, any of various types of random access memory (RAM), various flavors of programmable read-only memory (PROM) (such as flash memory), and other types of primary storage (i.e., program memory). The cache memories 1101, 1102 . . . 110n may be implemented in several levels (e.g., as level 1, level 2 and level 3 caches) and the cache controllers 1121, 1122 . . . 112n may collectively represent the cache controller logic that supports each cache level. As illustrated, the memory controller 114 may reside separately from processors 1041, 1042 . . . 104n, for example, as part of a discrete chipset. Alternatively, the memory controller 114 could be provided by plural memory controller instances that are respectively integrated with the processors 1041, 1042 . . . 104n.
Each of the processors 1041, 1042 . . . 104n is operable to execute program instruction logic under the control of a software program stored in the memory 108 (or elsewhere). As part of this program execution logic, update operations (updaters) 118 will periodically execute within a process, thread, or other execution context (hereinafter “task”) on the processors 1041, 1042 . . . 104n to perform hash table resizing and modification (e.g., insertions and deletions) on the hash table 116. Reference numerals 1181, 1182 . . . 118n illustrate individual updaters that may execute from time to time on the various processors 1041, 1042 . . . 104n. Each of the processors 1041, 1042 . . . 104n also periodically executes read operations (readers) 120 on the hash table 116. Reference numerals 1201, 1202 . . . 120n illustrate individual readers that may execute from time to time on the various processors 1041, 1042 . . . 104n. Each search operation is assumed to entail an element-by-element traversal of a bucket (implemented as a linked list) until one or more items representing the target of the search are found. In order to support concurrent hash table operations, such search operations may be performed using a lock-free synchronization mechanism, such as read-copy update. Each search operation is assumed to entail an element-by-element traversal of a bucket (implemented as an RCU-protected linked list) until one or more items representing the target of the search are found.
To facilitate synchronized updater-reader access to the hash table 116, the several processors 1041, 1042 . . . 104n are programmed to implement an RCU subsystem 122 by periodically executing respective RCU instances 1221, 1222 . . . 122n as part of their operating system functions or user-mode operations. As shown in
Accordingly, a technique for optimized resizing of RCU-protected hash tables has been disclosed. It will be appreciated that the foregoing concepts may be variously embodied in any of a data processing system, a machine implemented method, and a computer program product in which programming logic is provided by one or more machine-usable storage media for use in controlling a data processing system to perform the required functions. Example embodiments of a data processing system and machine implemented method were previously described in connection with
Example data storage media for storing such program instructions are shown by reference numerals 108 (memory) and 110 (cache) of the computer system 102 of
Although various example embodiments have been shown and described, it should be apparent that many variations and alternative embodiments could be implemented in accordance with the disclosure. It is understood, therefore, that the invention is not to be in any way limited except in accordance with the spirit of the appended claims and their equivalents.
This application is a continuation under 35 U.S.C. 120 of application Ser. No. 13/314,240, filed Dec. 8, 2011, entitled “Optimized Deletion And Insertion For High-Performance Resizable RCU-Protected Hash Tables.”
Number | Name | Date | Kind |
---|---|---|---|
5442758 | Slingwine et al. | Aug 1995 | A |
5608893 | Slingwine et al. | Mar 1997 | A |
5727209 | Slingwine et al. | Mar 1998 | A |
5960434 | Schimmel | Sep 1999 | A |
6219690 | Slingwine et al. | Apr 2001 | B1 |
6662184 | Friedberg | Dec 2003 | B1 |
6886162 | McKenney | Apr 2005 | B1 |
6996812 | McKenney | Feb 2006 | B2 |
7085911 | Sachedina et al. | Aug 2006 | B2 |
7191272 | McKenney | Mar 2007 | B2 |
7287131 | Martin et al. | Oct 2007 | B1 |
7287135 | McKenney et al. | Oct 2007 | B2 |
7313555 | Klier | Dec 2007 | B2 |
7349926 | McKenney et al. | Mar 2008 | B2 |
7353346 | McKenney et al. | Apr 2008 | B2 |
7395263 | McKenney | Jul 2008 | B2 |
7395383 | McKenney | Jul 2008 | B2 |
7426511 | McKenney | Sep 2008 | B2 |
7454581 | McKenney et al. | Nov 2008 | B2 |
7472228 | McKenney et al. | Dec 2008 | B2 |
7533377 | Appavoo et al. | May 2009 | B2 |
7653791 | McKenney | Jan 2010 | B2 |
7668851 | Triplett | Feb 2010 | B2 |
7689789 | McKenney et al. | Mar 2010 | B2 |
7734879 | McKenney et al. | Jun 2010 | B2 |
7734881 | McKenney et al. | Jun 2010 | B2 |
7747805 | McKenney | Jun 2010 | B2 |
7809916 | Shavit et al. | Oct 2010 | B1 |
7814082 | McKenney | Oct 2010 | B2 |
7818306 | McKenney et al. | Oct 2010 | B2 |
7873612 | McKenney et al. | Jan 2011 | B2 |
7904436 | McKenney | Mar 2011 | B2 |
7934062 | McKenney et al. | Apr 2011 | B2 |
7953708 | McKenney et al. | May 2011 | B2 |
7953778 | McKenney et al. | May 2011 | B2 |
7987166 | McKenney et al. | Jul 2011 | B2 |
8020160 | McKenney | Sep 2011 | B2 |
8055860 | McKenney et al. | Nov 2011 | B2 |
8055918 | McKenney et al. | Nov 2011 | B2 |
20040083347 | Parson | Apr 2004 | A1 |
20060112121 | McKenney et al. | May 2006 | A1 |
20060117072 | McKenney | Jun 2006 | A1 |
20060130061 | Bauer et al. | Jun 2006 | A1 |
20060265373 | McKenney et al. | Nov 2006 | A1 |
20070061372 | Appavoo et al. | Mar 2007 | A1 |
20080021908 | Trask et al. | Jan 2008 | A1 |
20080082532 | McKenney | Apr 2008 | A1 |
20080228691 | Shavit et al. | Sep 2008 | A1 |
20080313238 | McKenney et al. | Dec 2008 | A1 |
20090006403 | McKenney | Jan 2009 | A1 |
20090077080 | McKenney | Mar 2009 | A1 |
20100115235 | Triplett | May 2010 | A1 |
20110055183 | McKenney | Mar 2011 | A1 |
20110283082 | McKenney et al. | Nov 2011 | A1 |
Entry |
---|
P. Zijlstra, “[PATCH] slab: document SLAB—DESTROY—BY—RCU”, LKML.org, Nov. 13, 2008, 1 page. |
A. Arcangeli et al., “Using Read-Copy-Update Techniques for System V IPC in the Linux 2.5 Kernel,” 2003 FREENIX, Jun. 14, 2003, 13 pages. |
P. McKenney, “The RCU API, 2010 Edition”, LWN.net, Dec. 8, 2010, 11 pages. |
O. Shalev et al., “Split-Ordered Lists: Lock-Free Extensible Hash Tables”, Journal of the ACM, vol. 53, No. 3, 2006, pp. 379-405. |
Anonymous, “A Method for Implementing a Lock-Free Hash Table”, ip.com/priorartdatabase.com/IPCOM000205877D, Apr. 6, 2011, pages. |
M. Jensen et al. “Optimality in external memory hashing”, Algorithmica, vol. 52, No. 3, 403-311, Nov. 2008, 1 page abstract. |
J. Appavoo, “Clustered Objects”, University of Toronto Ph.D Thesis, 2005, 176 pages. |
J. Seigh, “RCU + SMR for preemptive kernel/user threads,” Linux Kernel Mailing List, May 9, 2005, 2 pages. |
M. Michael, “Hazard Pointers: Safe Memory Reclamation for Lock-Free Objects,” IEEE Transactions on Parallel and Distributed Jun. 2004, vol. 15, No. 6, pp. 491-504. |
D. Sarma et al., “Making RCU Safe for Deep Sub-Millisecond Response Realtime Applications,” 2004 USENIX (UseLinux track) Jun. 2004, 9 pages. |
P. McKenney, “RCU vs. Locking Performance on Different CPUs,” 2004 Linux.conf.au, 2004, 18 pages. |
P. McKenney et al., “Scaling dcache with RCU,” Linux Journal, Jan. 1, 2004, 12 pages. |
P. McKenney et al., “Using RCU in the Linux 2.5 Kernel,” Llnux Journal, Oct. 1, 2003, 11 pages. |
P. McKenney et al.,“Read-Copy Update,” 2002 Ottawa Linux Symposium, Jul. 8, 2002, 28 pages. |
H. Lindar et al., “Scalability of the Directory Entry Cache,” 2002 Ottawa Linux Symposium, Jun. 26, 2002, pp. 289-300. |
P. McKenney et al., “Read-Copy Update,” 2001 Ottawa Linux symposium, Jul. 2001, 22 pages. |
P. McKenney et al., “Read-Copy Update: Using Execution History to Solve Concurrency Problems,” PDCS, Oct. 1998, 11 pages. |
S. Dietrich et al., “Evolution of Real-Time Linux,” 7th RTL Workshop, Nov. 17, 2005, 18 pages. |
B. Gamsa, “Tornado: Maximizing Locality and Concurrency in a Shared Memory Multiprocessor Operating System,” 1999, 14 pages. |
Molnar et al., “Realtime and Linux,” 2005 Linux Kernel Summit, 8 pages. |
H. Boehm, “The Space Cost of Lazy Reference Counting,” ACM SIGPLAN Notices, Proceedings of the 31st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, POPL '04, vol. 39, Issue 1, Jan. 2004, p. 210-219. |
M. Michael, “Scalable Lock-Free Dynamic Memory Allocation,” ACM SIGPLAN Notices, Proceedings of the ACM SIGPLAN 2004 Conference on Programming Language Design and Implementation; PLDI '04, vol. 39, Issue 6, Jun. 2004, p. 35-46. |
D. Dice et al., “Mostly Lock-Free Malloc,” ACM SIGPLAN Notices, Proceedings of the 3rd International Symposium on Memory Management, ISMM '02, vol. 38, Issue 2 Supplement, Jun. 2002, p. 163-174. |
J. Corbet, “Read-copy-update for realtime,” LWN.net, Sep. 26, 2006, 3 pages. |
McKenney, “Seven real-time Linux approaches (Part C)”, LinuxDevices.com, Jun. 7, 2005, 13 pages. |
P. McKenney, “RCU and CONFIG—l PREEMPT—RT progress,” Linux Kernel Mailing List, May 9, 2005, 2 pages. |
O. Nesterov, QRCU: ‘Quick’ SRCU Implementation, Linux Kernel Mailing List, Dec. 1, 2005, 3 pages. |
P. McKenney, “Sleepable RCU”, LWN.net, Sep. 6, 2010, 10 pages. |
P. McKenney, “Read-Copy Update Implementations”, 2001, 3 pages. |
M. Herlihy, “A Methodology for Implementing Highly Concurrent Data Objects,” ACM Transactions on Programming Languages and Systems, vol. 15, Issue 5, Nov. 1993, pp. 745-770. |
M. Michael, “Safe Memory Reclamation for Dynamic Lock-Free Objects Using Atomic Reads and Writes,” Proceedings of the 21st Annual ACM Symposium on Principles of Distributed Computing, Jul. 2002, 10 pages. |
N. Barghouti et al., “Concurrency Control in Advanced Database Operations,” Jan. 1994, 83 pages. |
P. McKenney, “Exploiting Deferred Destruction: An Analysis of Read-Copy-Update Techniques in Operating System Kernels,” OGI School of School of Science & Engineering at Oregon Health & Science University, Jul. 2004, pp. 1-380. |
P. McKenney et al., “Extending RCU for Realtime and Embedded Workloads,” 2006 Ottawa Linux Symposium, Aug. 11, 2006, 15 pages. |
P. McKenney, “The design of preemptible read-copy-update,” LWN.net, Oct. 8, 2007, 27 pages. |
P. McKenney, “Integrating and Validating dynticks and Preemptible RCU,” LWN.net, Apr. 22, 2008, 19 pages. |
P. McKenney, “Hierarchical RCU,” LWN.net, Nov. 4, 2008, 19 pages. |
P. McKenney, “Is Parallel Programming Hard, and, If So, What Can You Do About It”, Mar. 8, 2009, 146 pages. |
P. McKenney, “Priority-Boosting RCU Read-Side Critical Sections,” LWN.net, Feb. 5, 2007, 15 pages. |
P. McKenney et al., “Towards hard realtime response from the Linux kernel on SMP hardware,” linux.conf.au, Canberra, Australia, Apr. 2005, 16 pages. |
P. McKenney et al., “Exploiting Deferred Destruction: An Analysis of Read-Copy-Update Techniques in Operating System Kernels”, Jan. 3, 2005, pp. 1-41. |
D. Guniguntala et al., “The read-copy-update mechanism for supporting real-time applications on shared-memory multiprocessor systems with Linux”, IBM Systems Journal vol. 47 No. 2, 2008, pp. 221-236. |
P. McKenney, “Introducing Technology Into Linux”, 2008 Linux Developer Symposium, China, 2008, 47 pages. |
P. McKenney, “Simplicity Through Optimization”, linux.conf.au, Jan. 2010, 109 pages. |
P. McKenney, “Deterministic Synchronization in Multicore Systems: the Role of RCU”, Aug. 18, 2009, pp. 1-9. |
P. McKenney, “RCU cleanups and simplified preemptable RCU”, LKML.org, Jul. 23, 2009, 1 page. |
P. McKenney, “Expedited “big hammer” RCU grace periods”, LKML.org, Jun. 25, 2009, 2 pages. |
P. McKenney, “RCU: The Bloatwatch Edition”, LWN.net, Mar. 17, 2009, 9 pages. |
M. Desnoyers, “Low-Impact Operating System Tracing”, University of Montreal, PhD Thesis, Dec. 2009, 233 pages. |
P. McKenney, “Using a Malicious User-Level RCU to Torture RCU-Based Algorithms”, linux.conf.au, Jan. 2009, 51 pages. |
P. McKenney et al., “Introducing Technology Into the Linux Kernel: A Case Study”, Operating Systems Review, Jul. 2008, 16 pages. |
P. McKenney “What is RCU, Fundamentally”, LWN.net, Dec. 17, 2007, 15 pages. |
P. McKenney, What is RCU? Part 2: Usage, LWN.net,Dec. 24, 2007, 15 pages. |
P. McKenney, RCU part 3: the RCU API, LWN.net, Jan. 7, 2008, 7 pages. |
T. Hart et al., “Performance of memory reclamation for lockless synchronization”, Journal of Parallel and Distributed Computing, Dec. 2007, pp. 1270-1285. |
McKenney, “Using Promela and Spin to verify parallel algorithms”, LWN.net, Aug. 1, 2007, 11 pages. |
McKenney, “RCU and Unloadable Modules”, LWN.net, Jan. 14, 2007, 4 pages. |
Number | Date | Country | |
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20130151811 A1 | Jun 2013 | US |
Number | Date | Country | |
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Parent | 13314240 | Dec 2011 | US |
Child | 13455220 | US |