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Using hardware performance counters to speed up autotuning convergence on GPUs

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

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Tags: Auto-Tuning, Computer science, CUDA, HPC, Machine learning, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2080, OpenCL, Package, Performance, Vulkan

February 23, 2021 by hgpu

Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures

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

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Tags: Auto-Tuning, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 680, nVidia GeForce GTX 750, nVidia GeForce RTX 2080, Package

February 14, 2021 by hgpu

Fast CUDA-Aware MPI Datatypes without Platform Support

Carl Pearson, Kun Wu, I-Hsin Chung, Jinjun Xiong, Wen-Mei Hwu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1070, Tesla V100

January 3, 2021 by hgpu

Hybrid MPI and CUDA Parallelization for CFD Applications on Multi-GPU HPC Clusters

Jianqi Lai, Hang Yu, Zhengyu Tian, Hua Li

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Tags: cfd, CUDA, Fluid dynamics, GPU cluster, HPC, MPI, nVidia, nVidia GeForce GTX 1070, OpenMP, Tesla V100

September 27, 2020 by hgpu

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

Aditya Agarwal, Yupeng Han, Maxim Likhachev

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 1070, Package, Robotics, Tesla P100, Tesla V100

August 9, 2020 by hgpu

Studies on CUDA Offloading for Real-Time Simulation and Visualization

Edgar Josafat Martinez-Noriega

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 970 M, nVidia GeForce RTX 2080, nVidia Jetson K1, Rendering, Thesis, Virtualization, Visualization

July 5, 2020 by hgpu

Framework for Parallel Kernels Auto-tuning

Filip Petrovič

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Tags: Auto-Tuning, Computer science, CUDA, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 750, nVidia GeForce GTX 970, OpenCL, Package, Performance, Thesis

November 10, 2019 by hgpu

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

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

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Tags: AMD Radeon RX Vega 56, Auto-Tuning, Benchmarking, Computer science, CUDA, Electron microscopy, Intel Xeon Phi, Microscopy, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 750, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Performance, performance portability, Tesla K20

October 27, 2019 by hgpu

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

Philippe Tillet, H. T. Kung, David Cox

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Tags: Compilers, Computer science, CUDA, Deep learning, High-level Languages, LLVM, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 1070, Package

June 30, 2019 by hgpu

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Grigory Glukhov, Aleksandra Soltan

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Tags: 3D Graphics and Realism, AMD RX Vega 64, ATI, Neural networks, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2070, Thesis, Voxelization, Vulkan

June 23, 2019 by hgpu

Improving OpenCL Performance by Specializing Compiler Phase Selection and Ordering

Ricardo Nobre, Luis Reis, Joao M. P. Cardoso

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Tags: Computer science, nVidia, nVidia GeForce GTX 1070, OpenCL, Performance, PTX

October 28, 2018 by hgpu

pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment

Sven Warris, N. Roshan N. Timal, Marcel Kempenaar, Arne M. Poortinga, Henri van de Geest, Ana L. Varbanescu, Jan-Peter Nap

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 1070, OpenCL, Package, Python, Sequence alignment, Smith-Waterman algorithm

January 13, 2018 by hgpu

pharos: performance monitoring instrumentation for multi-FPGA systems

Performance Monitoring of Multi-FPGA Systems

Efficient Video Compression via Content-Adaptive Super-Resolution

CUDA Modular Polynomial (CUMODP) Library

Parallel Arbitrary-precision Integer Arithmetic

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

CUDA Tutorial - Cryptanalysis of Classical Ciphers Using Modern GPUs and CUDA

CUDA Tutorial – Cryptanalysis of Classical Ciphers Using Modern GPUs and CUDA

Ginkgo: a high-performance linear algebra library for manycore systems, with a focus on sparse solution of linear systems

Porting a sparse linear algebra math library to Intel GPUs

Exa.TrkX: Machine Learning for Particle Track Reconstruction

Physics and Computing Performance of the Exa.TrkX TrackML Pipeline

A Compiler Infrastructure for Accelerator Generators

LIKWID: A Lightweight Performance-Oriented Tool Suite

ECM modeling and performance tuning of SpMV and Lattice QCD on A64FX

hls4ml: A package for machine learning inference in FPGAs

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices

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2021

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Munich, Germany

9th International Workshop on OpenCL and SYCL, 2021

2020

December

10-14

Virtually in Barcelona, Spain

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

2020

November

24-27

Naha, Okinawa, Japan

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2021

January

13-15

Shenzhen, China

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

2020

December

14-16

Bangkok, Thailand

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020

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high performance computing on graphics processing units: hgpu.org

Using hardware performance counters to speed up autotuning convergence on GPUs

Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures

Fast CUDA-Aware MPI Datatypes without Platform Support

Hybrid MPI and CUDA Parallelization for CFD Applications on Multi-GPU HPC Clusters

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

Studies on CUDA Offloading for Real-Time Simulation and Visualization

Framework for Parallel Kernels Auto-tuning

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

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Improving OpenCL Performance by Specializing Compiler Phase Selection and Ordering

pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment

Recent source codes

pharos: performance monitoring instrumentation for multi-FPGA systems

Efficient Video Compression via Content-Adaptive Super-Resolution

CUDA Modular Polynomial (CUMODP) Library

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

CUDA Tutorial - Cryptanalysis of Classical Ciphers Using Modern GPUs and CUDA

Ginkgo: a high-performance linear algebra library for manycore systems, with a focus on sparse solution of linear systems

Exa.TrkX: Machine Learning for Particle Track Reconstruction

A Compiler Infrastructure for Accelerator Generators

LIKWID: A Lightweight Performance-Oriented Tool Suite

hls4ml: A package for machine learning inference in FPGAs

Most viewed papers (last 30 days)

Featured events

9th International Workshop on OpenCL and SYCL, 2021

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020