high performance computing on graphics processing units: hgpu.org

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Exploring GPGPU workloads: Characterization methodology, analysis and microarchitecture evaluation implications

Nilanjan Goswami, Ramkumar Shankar, Madhura Joshi, Tao Li

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Tags: Benchmarking, Computer science, CUDA, nVidia, Performance, PTX

April 4, 2011 by hgpu

Throughput-Effective On-Chip Networks for Manycore Accelerators

Ali Bakhoda, John Kim, Tor M. Aamodt

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance

April 2, 2011 by hgpu

MARC: A Many-Core Approach to Reconfigurable Computing

Ilia Lebedev, Shaoyi Cheng, Austin Doupnik, James Martin, Christopher Fletcher, Daniel Burke, Mingjie Lin, John Wawrzynek

Tags: Compilers, Computer science, FPGA, OpenCL, Performance

April 2, 2011 by hgpu

Parallel discrete wavelet transform using the Open Computing Language: a performance and portability study

B. Sharma, N. Vydyanathan

Tags: ATI, Image processing, nVidia, OpenCL, Performance, Wavelet

April 2, 2011 by hgpu

Parallel implementation of the Finite-Difference Time-Domain method in Open Computing Language

T.P. Stefanski, S. Benkler, N. Chavannes, N. Kuster

Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, OpenCL, Performance

April 2, 2011 by hgpu

A characterization and analysis of PTX kernels

Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, PTX

April 2, 2011 by hgpu

Non-intrusive Performance Analysis of Parallel Hardware Accelerated Applications on Hybrid Architectures

Robert Dietrich, Thomas Ilsche, Guido Juckeland

Tags: Computer science, CUDA, nVidia, OpenCL, Performance

April 1, 2011 by hgpu

Application of the OpenCL API for Implementation of the NIPALS Algorithm for Principal Component Analysis of Large Data Sets

Joshua C. Bowden

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Tags: BLAS, Computer science, GPU cluster, MPI, nVidia, nVidia Quadro FX 580, OpenCL, Performance, Tesla C1060, Tesla S2050, Tesla T10

March 31, 2011 by hgpu

Evaluation Framework for GPU Performance Based on OpenCL Standard

M. Jurecko, J. Kocisova, J. Busa, T. Kasanicky, M. Domiter, M. Zvada

Tags: ATI, Computer science, GPU cluster, nVidia, OpenCL, Performance

March 31, 2011 by hgpu

An Empirically Optimized Radix Sort for GPU

B. Huang, Jinlan Gao, Xiaoming Li

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Tags: Algorithms, Computer science, MPI, nVidia, Performance, Sorting

March 28, 2011 by hgpu

A parallelization cost model for GPU

Zhang Dan, Zhao Rongcai, Han Lin, Wang Tao, Qu Jin

Tags: Computer science, Optimization, Performance

March 27, 2011 by hgpu

Modeling GPU-CPU Workloads and Systems

Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce 8600 GS, nVidia GeForce GTX 280, Performance, Task scheduling, Tesla C1060

March 23, 2011 by hgpu

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Exploring GPGPU workloads: Characterization methodology, analysis and microarchitecture evaluation implications

Throughput-Effective On-Chip Networks for Manycore Accelerators

MARC: A Many-Core Approach to Reconfigurable Computing

Parallel discrete wavelet transform using the Open Computing Language: a performance and portability study

Parallel implementation of the Finite-Difference Time-Domain method in Open Computing Language

A characterization and analysis of PTX kernels

Non-intrusive Performance Analysis of Parallel Hardware Accelerated Applications on Hybrid Architectures

Application of the OpenCL API for Implementation of the NIPALS Algorithm for Principal Component Analysis of Large Data Sets

Evaluation Framework for GPU Performance Based on OpenCL Standard

An Empirically Optimized Radix Sort for GPU

A parallelization cost model for GPU

Modeling GPU-CPU Workloads and Systems

Recent source codes

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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