66 citations · 163 across the 4 of their papers we have counts for
5 papers
Towards a Benchmarking Suite for Kernel Tuners
Jacob O. Tørring, Ben van Werkhoven, Filip Petrovic +3
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 hidin…
Using hardware performance counters to speed up autotuning convergence on GPUs
Jiří Filipovič, Jana Hozzová, Amin Nezarat +2
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…
A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit
Filip Petrovič, David Střelák, Jana Hozzová +4
Autotuning of performance-relevant source-code parameters allows to automatically tune applications without hard coding optimizations and thus helps with keeping the performance po…
CaverDock: A Novel Method for the Fast Analysis of Ligand Transport
Jiří Filipovič, Ondřej Vávra, Jan Plhák +5
Here we present a novel method for the analysis of transport processes in proteins and its implementation called CaverDock. Our method is based on a modified molecular docking algo…
Optimizing CUDA Code By Kernel Fusion---Application on BLAS
J. Filipovič, M. Madzin, J. Fousek +1
Modern GPUs are able to perform significantly more arithmetic operations than transfers of a single word to or from global memory. Hence, many GPU kernels are limited by memory ban…