Optimization Techniques for GPU Programming
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TL;DR: In this article , a survey discusses various optimization techniques found in 450 articles published in the last 14 years and analyzes the optimizations from different perspectives which shows that the various optimizations are highly interrelated, explaining the need for techniques such as auto-tuning.
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Abstract: In the past decade, Graphics Processing Units have played an important role in the field of high-performance computing and they still advance new fields such as IoT, autonomous vehicles, and exascale computing. It is therefore important to understand how to extract performance from these processors, something that is not trivial. This survey discusses various optimization techniques found in 450 articles published in the last 14 years. We analyze the optimizations from different perspectives which shows that the various optimizations are highly interrelated, explaining the need for techniques such as auto-tuning.
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References
•Journal Article
GPU-Based High Performance Password Recovery Technique for Hash Functions.
TL;DR: A new password recovery technique for the standardized hash functions, MD5 and SHA1, are proposed by combining the optimization methods on GPU, which makes it possible to recover password from hash values in a reasonable time.
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Compiling Generalized Histograms for GPU
Troels Henriksen,Sune Hellfritzsch,P. Sadayappan,Cosmin E. Oancea +3 more
- 01 Nov 2020
TL;DR: In this paper, the authors present a technique for histogram-like computations on GPUs that ensures both work-efficient asymptotic cost, support for arbitrary associative and commutative operators, and efficient use of hardwaresupported atomic operations when applicable.
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Optimization of Sparse Matrix-Vector Multiplication for CRS Format on NVIDIA Kepler Architecture GPUs
Daichi Mukunoki,Daisuke Takahashi +1 more
- 24 Jun 2013
TL;DR: This paper presents optimization techniques for SpMV for the Compressed Row Storage (CRS) format on NVIDIA Kepler architecture GPUs using CUDA, based on an existing method proposed for the Fermi architecture, and takes advantage of some of the new features of the Kepler architecture.
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Reducing divergence in GPGPU programs with loop merging
Tianyi David Han,Tarek S. Abdelrahman +1 more
- 16 Mar 2013
TL;DR: This work proposes a software optimization, called loop merging, that aims to reduce divergence due to varying trip-count of a loop across warp threads, and implements it in LLVM.
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Strassen’s Algorithm Reloaded on GPUs
TL;DR: A performance model for NVIDIA Volta GPUs is developed to select the appropriate blocking parameters and predict the performance for gemm and Strassen, and it is developed that can achieve up to 1.11× speedup with a crossover point as small as 1,536 compared to cublasSgemm on a NVIDIA Tesla V100 GPU.
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