Towards a Benchmarking Suite for Kernel Tuners

Autor: Tørring, Jacob O., van Werkhoven, Ben, Petrovic, Filip, Willemsen, Floris-Jan, Filipovic, Jirí, Elster, Anne C.

As computing system become more complex, it is becoming harder for programmers to keep their codes optimized as the hardware gets updated. Autotuners try to alleviate this by hiding as many architecture-based optimization details as possible from the

Externí odkaz: http://arxiv.org/abs/2303.08976

Using hardware performance counters to speed up autotuning convergence on GPUs

Autor: Filipovič, Jiří, Hozzová, Jana, Nezarat, Amin, Oľha, Jaroslav, Petrovič, Filip

Nowadays, GPU accelerators are commonly used to speed up general-purpose computing tasks on a variety of hardware. However, due to the diversity of GPU architectures and processed data, optimization of codes for a particular type of hardware and spec

Externí odkaz: http://arxiv.org/abs/2102.05297

A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit

Autor: Petrovič, Filip, Střelák, David, Hozzová, Jana, Oľha, Jaroslav, Trembecký, Richard, Benkner, Siegfried, Filipovič, Jiří

Publikováno v: Petrovic et al., A benchmark set of highly-efficient CUDA and OpenCL kernels and its dynamic autotuning with Kernel Tuning Toolkit. In Future Generation Computer Systems, Vol. 108, pages 161-177. 2020

Autotuning of performance-relevant source-code parameters allows to automatically tune applications without hard coding optimizations and thus helps with keeping the performance portable. In this paper, we introduce a benchmark set of ten autotunable

Externí odkaz: http://arxiv.org/abs/1910.08498

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