high performance computing on graphics processing units: hgpu.org

A. Gianelle, S. Amerio, D. Bastieri, M. Corvo, W. Ketchum, T. Liu, A. Lonardo, D. Lucchesi, S. Poprocki, R. Rivera, L. Tosoratto, P. Vicini, P. Wittich

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Tags: ATI, ATI Radeon HD 7970, CUDA, High Energy Physics - Experiment, Instrumentation and Detectors, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Physics, Tesla K20, Tesla M2050

December 6, 2013 by hgpu

Comparative Study of High Performance Computing Using Multi-core Parallel Systems

Hyo Jong Lee, Hyeon Kyu Kim

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 550 Ti, nVidia GeForce GTX 580, Performance

December 4, 2013 by hgpu

Divergence Analysis

Diogo Sampaio, Rafael Martins De Souza, Sylvain Collange, Fernando Magno Quintao Pereira

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 570, Performance

December 4, 2013 by hgpu

SESH framework: A Space Exploration Framework for GPU Application and Hardware Codesign

Joo Hwan Lee, Jiayuan Meng, Hyesoon Kim

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Tags: Benchmarking, Computer science, nVidia, nVidia GeForce GTX 580, Performance

December 3, 2013 by hgpu

Benchmarking Parallel Performance on Many-Core Processors

Bryant C. Lam, Ajay Barboza, Ravi Agrawal, Alan D. George, Herman Lam

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Tags: Benchmarking, Computer science, Heterogeneous systems, Intel Phi, Intel Xeon Phi, Performance

November 29, 2013 by hgpu

The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

Kamil Rocki, Martin Burtscher, Reiji Suda

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel Phi, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Programming techniques

November 28, 2013 by hgpu

Hybrid Programming using OpenSHMEM and OpenACC

Matthew Baker, Swaroop Pophale, Jean-Charles Vasnier, Haoqiang Jin, Oscar Hernandez

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Tags: Computer science, CUDA, MPI, nVidia, OpenACC, Performance, Tesla K20

November 28, 2013 by hgpu

Evaluating the Performance and Energy Efficiency of N-Body Codes on Multi-Core CPUs and GPUs

Ivan Zecena, Martin Burtscher, Tongdan Jin, Ziliang Zong

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Tags: Computer science, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 480, Performance

November 27, 2013 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

Lessons learned from contrasting a BLAS kernel implementations

Integrated GPUs: how useful are they in HPC?

The Comparisons of OpenCL and OpenMP Computing Paradigm

A Quantitative Comparison of Emulated Shared Memory Architectures to Current Multicore CPUs and GPUs

Applications of Many-Core Technologies to On-line Event Reconstruction in High Energy Physics Experiments

Comparative Study of High Performance Computing Using Multi-core Parallel Systems

Divergence Analysis

SESH framework: A Space Exploration Framework for GPU Application and Hardware Codesign

Benchmarking Parallel Performance on Many-Core Processors

The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

Hybrid Programming using OpenSHMEM and OpenACC

Evaluating the Performance and Energy Efficiency of N-Body Codes on Multi-Core CPUs and GPUs

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

Most viewed papers (last 30 days)