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
Kernel Fusion: An Effective Method for Better Power Efficiency on Multithreaded GPU
Guibin Wang,YiSong Lin,Wei Yi +2 more
- 18 Dec 2010
TL;DR: Experimental evaluation validates that the proposed kernel fusion method could reduce energy consumption without performance loss for several typical kernels and effective method to reduce the usage of shared memory and coordinate the thread space of the kernels to be fused is proposed.
Inter-block GPU communication via fast barrier synchronization
Shucai Xiao,Wu-chun Feng +1 more
- 19 Apr 2010
TL;DR: This work proposes two approaches for inter-block GPU communication via barrier synchronization: GPU lock-based synchronization andGPU lock-free synchronization and evaluates the efficacy of each approach via a micro-benchmark as well as three well-known algorithms — Fast Fourier Transform, dynamic programming, and bitonic sort.
Optimizing Dynamic Programming on Graphics Processing Units Via Data Reuse and Data Prefetch with Inter-Block Barrier Synchronization
Chao-Chin Wu,Kai-Cheng Wei,Ting-Hong Lin +2 more
- 17 Dec 2012
TL;DR: This work proposed a methodology that can adaptively adjust the thread-level parallelism in mapping a NPDP problem onto the GPU, thus providing sufficient and steady degrees of parallelism across different compute stages, and realizes the optimal matrix parenthesization problem.
Bulk execution of the dynamic programming for the optimal polygon triangulation problem on the GPU
TL;DR: This paper proposes a parallel processing technique for the bulk execution of the dynamic programming using the GPU (Graphics Processing Unit) and focuses on the optimal polygon triangulation problem for a lot of polygons.
Systematic approach in optimizing numerical memory-bound kernels on GPU
Ahmad Abdelfattah,David E. Keyes,Hatem Ltaief +2 more
- 27 Aug 2012
TL;DR: A systematic approach for efficiently implementing memory-bound DLA kernels on GPUs, by taking advantage of the underlying device's architecture, to outperform existing state-of-the-art GPU implementations for the symmetric matrix-vector multiplication (SYMV).