Automatic Parallel Tiled Code Generation Based on Dependence Approximation

Bielecki, Wlodzimierz; Poliwoda, M.

doi:10.1007/978-3-030-86359-3_20

Cited by 7 publications

(13 citation statements)

References 12 publications

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“…To generate regular code and increase tile dimension, DAPT implements space-time tiling. First DAPT generates space tiles according to the technique presented in paper [15]. Then it splits each space tile into multiple time slices.…”

Section: Opitmizing Compilers Used For Experimentsmentioning

confidence: 99%

Automatic code optimization for computing the McCaskill partition functions

Bielecki¹,

Palkowski²,

Poliwoda³

2022

Annals of Computer Science and Information Systems

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In this paper, we present the application of three automatic source-to-source compilers to code implementing Mc-Caskill's bioinformatics algorithm. It computes probabilities of various substructures for RNA prediction. McCaskill's algorithm is compute and data intensive and it is within dynamic programming. A corresponding programming code exposes nonuniform dependences that complicate tiling of that code. The corresponding code is represented within the polyhedral model. Its optimization is still a challenging task for optimizing compilers employing multi-threaded loop tiling. To generate optimized code, we used the popular PLuTo compiler that finds and applies affine transformations, the TRACO compiler based on calculating the transitive closure of loop dependence graphs, and the newest polyhedral tool DAPT implementing space-time tiling. An experimental study fulfilled on two multi-core machines: an AMD Epyc with 64 threads and a 2x Intel Xeon Platinum 9242 with 192 threads demonstrates considerable speedup, high locality, and scalability for various problem sizes and the number of threads of generated codes by means of space-time tiling.

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Section: Opitmizing Compilers Used For Experimentsmentioning

confidence: 99%

Automatic code optimization for computing the McCaskill partition functions

Bielecki¹,

Palkowski²,

Poliwoda³

2022

Annals of Computer Science and Information Systems

Self Cite

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“…In this method, all iterations on the same Wavefronts are independent of each other and depend only on the previous Wavefronts' iterations. In [30], one of the latest research papers on the presentation of parallel compilers is presented. When dependencies are non-uniform, time tiling constraints are also nonlinear and usually increase in size and computational complexity after becoming linear.…”

Section: Introductionmentioning

confidence: 99%

A New Combination Method for Improving Parallelism in Two and Three Level Perfect Nested Loops

et al. 2022

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The growth of software techniques for implementing applications must go hand in hand with the growth of computer system hardware in the design of multi-core and multi-processor systems; otherwise, we cannot expect to be able to use maximum hardware capacities. One of the most important and challenging techniques for running applications is to run them in parallel with a focus on loop parallelism to reduce execution time. On the other hand, in recent years, many algorithms have been working on volumetric data, i.e., three-dimensional spaces; therefore, parallelization must be possible for all types of two-dimensional and three-dimensional loops. Uniformization is an important part of loop parallelism, and also the present paper's focus. The proposed algorithm in the present paper performed uniformization with a combination of the frog leaping algorithm and the fuzzy system for two-and three-dimensional loops on a wide range of input dependence vectors and achieved a considerable variety of results in the desired time. The results of this study can be used to facilitate the development of parallel codes.

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“…After they are linearised, constraint size and computation complexity of code generation are usually increased. � In recent years, uniformisation-based compilers have been developed [28] that can help reduce the complexity of these compilers by providing uniformisation methods. � In recent years, the lack of existing research in the field of uniformisation has led to the presentation of solutions based on a lack of optimal techniques for uniformisation [29].…”

Section: Introductionmentioning

confidence: 99%

“…When dependences are non‐uniform, time‐tiling constraints that need to be done in the next step are non‐linear as well, while they must be linear. After they are linearised, constraint size and computation complexity of code generation are usually increased. In recent years, uniformisation‐based compilers have been developed [28] that can help reduce the complexity of these compilers by providing uniformisation methods. In recent years, the lack of existing research in the field of uniformisation has led to the presentation of solutions based on a lack of optimal techniques for uniformisation [29]. So far, little work has been done on the uniformisation of three‐dimensional iteration spaces [18]; however, the processing, visualisation and analysis of 3D data spaces are important areas that have been considered in recent years.…”

Section: Introductionmentioning

confidence: 99%

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TLP: Towards three‐level loop parallelisation

Mahjoub

Golsorkhtabaramiri

Amiri

2022

IET Computers & Digital Tech

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Due to the design of computer systems in the multi‐core and/or multi‐processor form, it is possible to use the maximum capacity of processors to run an application with the least time consumed through parallelisation. This is the responsibility of parallel compilers, which perform parallelisation in several steps by distributing iterations between different processors and executing them simultaneously to achieve lower runtime. The present paper focuses on the uniformisation of three‐level perfect nested loops as an important step in parallelisation and proposes a method called Towards Three‐Level Loop Parallelisation (TLP) that uses a combination of a Frog Leaping Algorithm and Fuzzy to achieve optimal results because in recent years, many algorithms have worked on volumetric data, that is, three‐dimensional spaces. Results of the implementation of the TLP algorithm in comparison with existing methods lead to a wide variety of optimal results at desired times, with minimum cone size resulting from the vectors. Besides, the maximum number of input dependence vectors is decomposed by this algorithm. These results can accelerate the process of generating parallel codes and facilitate their development for High‐Performance Computing purposes.

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Automatic Parallel Tiled Code Generation Based on Dependence Approximation

Cited by 7 publications

References 12 publications

Automatic code optimization for computing the McCaskill partition functions

Automatic code optimization for computing the McCaskill partition functions

A New Combination Method for Improving Parallelism in Two and Three Level Perfect Nested Loops

TLP: Towards three‐level loop parallelisation

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