Deriving efficient parallel programs for complex recurrences

Teo, Yong Meng; Chin, Wei-Ngan; Tan, Soon Huat

doi:10.1145/266670.266697

Cited by 7 publications

(2 citation statements)

References 19 publications

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“…This lay the foundation for semi-automatic programming [5,6,27]. Later, these concepts have been applied to divide-and-conquer in a disciplined way in [7,31]; these address divide-andconquer in the classical sense of [13] (Chapter 4), focusing on parallelism. In Bellmania, more focus is put on re-ordering of array reads and writes, following and mechanizing techniques related to DP from [8,9].…”

Section: Related Workmentioning

confidence: 99%

Deriving divide-and-conquer dynamic programming algorithms using solver-aided transformations

et al. 2016

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We introduce a framework allowing domain experts to manipulate computational terms in the interest of deriving better, more efficient implementations. It employs deductive reasoning to generate provably correct efficient implementations from a very high-level specification of an algorithm, and inductive constraint-based synthesis to improve automation. Semantic information is encoded into program terms through the use of refinement types.In this paper, we develop the technique in the context of a system called Bellmania that uses solver-aided tactics to derive parallel divide-and-conquer implementations of dynamic programming algorithms that have better locality and are significantly more efficient than traditional loop-based implementations. Bellmania includes a high-level language for specifying dynamic programming algorithms and a calculus that facilitates gradual transformation of these specifications into efficient implementations. These transformations formalize the divide-and-conquer technique; a visualization interface helps users to interactively guide the process, while an SMT-based back-end verifies each step and takes care of low-level reasoning required for parallelism.We have used the system to generate provably correct implementations of several algorithms, including some important algorithms from computational biology, and show that the performance is comparable to that of the best manually optimized code.

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Section: Related Workmentioning

confidence: 99%

Deriving divide-and-conquer dynamic programming algorithms using solver-aided transformations

et al. 2016

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“…They have been well researched in the context of optimizing compilers. The work in this area focused on a variety of issues (loosely categorized as follows) including detection of reductions [1,4,12,17], parallelization/scheduling strategies [9,18,22,27,28,34,35], speculative approaches [6,7,21,39], and architectural support [10]. The earlier techniques were often limited to loops in which the reduction variables and operators were fully analyzable by the compiler (even if the loop bounds were unknown).…”

Section: Related Workmentioning

confidence: 99%

Speculative parallelization of partial reduction variables

Han

Liu

Tuck

2010

Proceedings of the 8th Annual IEEE/ACM International Symposium on Code Generation and Optimization

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Reduction variables are an important class of cross-thread dependence that can be parallelized by exploiting the associativity and commutativity of their operation. In this paper, we define a class of shared variables called partial reduction variables (PRV). These variables either cannot be proven to be reductions or they violate the requirements of a reduction variable in some way. We describe an algorithm that allows the compiler to detect PRVs, and we also discuss the necessary requirements to parallelize detected PRVs. Based on these requirements, we propose an implementation in a TLS system to parallelize PRVs that works by a combination of techniques at compile time and in the hardware. The compiler transforms the variable under the assumption that the reduction-like behavior proven statically will hold true at runtime. However, if a thread reads or updates the shared variable as a result of an alias or unlikely control path, a lightweight hardware mechanism will detect the access and synchronize it to ensure correct execution. We implement our compiler analysis and transformation in GCC, and analyze its potential on the SPEC CPU 2000 benchmarks. We find that supporting PRVs provides up to 46% performance gain over a highly optimized TLS system and on average 10.7% performance improvement.

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Automatically Partitioning Data to Facilitate the Parallelization of Functional Programs

Dever

Hamilton

2015

Lecture Notes in Computer Science

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Deriving efficient parallel programs for complex recurrences

Cited by 7 publications

References 19 publications

Deriving divide-and-conquer dynamic programming algorithms using solver-aided transformations

Deriving divide-and-conquer dynamic programming algorithms using solver-aided transformations

Speculative parallelization of partial reduction variables

Automatically Partitioning Data to Facilitate the Parallelization of Functional Programs

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