Using memory mapping to support cactus stacks in work-stealing runtime systems

Many multithreaded concurrency platforms that use a work-stealing runtime system incorporate a "cactus stack," wherein a function's accesses to stack variables properly respect the function's calling ancestry, even when many of the functions operate in parallel. Unfortunately, su...

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Published in:PACT '10 : proceedings of the Nineteenth International Conference on Parallel Architectures and Compilation Techniques : September 11-15, 2010, Vienna, Austria pp. 411 - 420
Main Authors: I-Ting Angelina Lee, Boyd-Wickizer, Silas, Zhiyi Huang, Leiserson, Charles E.
Format: Conference Proceeding
Language:English
Published: ACM 01.09.2010
Subjects:
cactus stack
Cilk
Concurrent computing
Instruction sets
interoperability
memory mapping
Parallel processing
Prototypes
Runtime
serial-parallel reciprocity
Synchronization
Work stealing
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Abstract Many multithreaded concurrency platforms that use a work-stealing runtime system incorporate a "cactus stack," wherein a function's accesses to stack variables properly respect the function's calling ancestry, even when many of the functions operate in parallel. Unfortunately, such existing concurrency platforms fail to satisfy at least one of the following three desirable criteria: † full interoperability with legacy or third-party serial binaries that have been compiled to use an ordinary linear stack, † a scheduler that provides near-perfect linear speedup on applications with sufficient parallelism, and † bounded and efficient use of memory for the cactus stack. We have addressed this cactus-stack problem by modifying the Linux operating system kernel to provide support for thread-local memory mapping (TLMM). We have used TLMM to reimplement the cactus stack in the open-source Cilk-5 runtime system. The Cilk-M runtime system removes the linguistic distinction imposed by Cilk-5 between serial code and parallel code, erases Cilk-5's limitation that serial code cannot call parallel code, and provides full compatibility with existing serial calling conventions. The Cilk-M runtime system provides strong guarantees on scheduler performance and stack space. Benchmark results indicate that the performance of the prototype Cilk-M 1.0 is comparable to the Cilk 5.4.6 system, and the consumption of stack space is modest.
AbstractList Many multithreaded concurrency platforms that use a work-stealing runtime system incorporate a "cactus stack," wherein a function's accesses to stack variables properly respect the function's calling ancestry, even when many of the functions operate in parallel. Unfortunately, such existing concurrency platforms fail to satisfy at least one of the following three desirable criteria: † full interoperability with legacy or third-party serial binaries that have been compiled to use an ordinary linear stack, † a scheduler that provides near-perfect linear speedup on applications with sufficient parallelism, and † bounded and efficient use of memory for the cactus stack. We have addressed this cactus-stack problem by modifying the Linux operating system kernel to provide support for thread-local memory mapping (TLMM). We have used TLMM to reimplement the cactus stack in the open-source Cilk-5 runtime system. The Cilk-M runtime system removes the linguistic distinction imposed by Cilk-5 between serial code and parallel code, erases Cilk-5's limitation that serial code cannot call parallel code, and provides full compatibility with existing serial calling conventions. The Cilk-M runtime system provides strong guarantees on scheduler performance and stack space. Benchmark results indicate that the performance of the prototype Cilk-M 1.0 is comparable to the Cilk 5.4.6 system, and the consumption of stack space is modest.
Author I-Ting Angelina Lee
Leiserson, Charles E.
Zhiyi Huang
Boyd-Wickizer, Silas
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  givenname: Charles E.
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  fullname: Leiserson, Charles E.
  organization: MIT CSAIL, Cambridge, MA, USA
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Snippet Many multithreaded concurrency platforms that use a work-stealing runtime system incorporate a "cactus stack," wherein a function's accesses to stack variables...
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StartPage 411
SubjectTerms cactus stack
Cilk
Concurrent computing
Instruction sets
interoperability
memory mapping
Parallel processing
Prototypes
Runtime
serial-parallel reciprocity
Synchronization
Work stealing
Title Using memory mapping to support cactus stacks in work-stealing runtime systems
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