high performance computing on graphics processing units: hgpu.org

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Aspects of GPU for general purpose high performance computing

Takayuki Aoki, Shoichi Hirasawa, Akira Nukada, Hiroki Honda, Satoshi Matsuoka

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques, Task scheduling

March 23, 2011 by hgpu

Improving accuracy for matrix multiplications on GPUs

Matthew Badin, Lubomir Bic, Michael Dillencourt, Alexandru Nicolau

Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Performance

March 22, 2011 by hgpu

Performance comparison of FPGA, GPU and CPU in image processing

Shuichi Asano, Tsutomu Maruyama, Yoshiki Yamaguchi

Tags: Filtering, FPGA, Image processing, Performance

March 21, 2011 by hgpu

An approach for the effective utilization of GP-GPUs in parallel combined simulation

David W. Bauer, Matthew McMahon, Ernest H. Page

Tags: Computer science, Heterogeneous systems, Partial differential equations, PDEs, Performance

March 21, 2011 by hgpu

Joint Forces: From Multithreaded Programming to GPU Computing

Frank Feinbube, Peter Troger, Andreas Polze

Tags: Computer science, Optimization, Performance

March 20, 2011 by hgpu

Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters

J. Myre, S. D. C. Walsh, D. Lilja, M. O. Saar

Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, OpenMP, Performance

March 17, 2011 by hgpu

Implementing the Himeno benchmark with CUDA on GPU clusters

Everett H. Phillips, Massimiliano Fatica

Tags: Benchmarking, Computer science, CUDA, GPU cluster, nVidia, Performance, Tesla C1060

March 16, 2011 by hgpu

Patterns of Inefficient Performance Behavior in GPU Applications

Dominic Eschweiler, Daniel Becker, Felix Wolf

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla T10

March 16, 2011 by hgpu

General-purpose molecular dynamics simulations on GPU-based clusters

Christian R. Trott, Lars Winterfeld, Paul S. Crozier

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Tags: Computational Physics, Condensed matter, CUDA, GPU cluster, Materials Science, Molecular dynamics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Performance, Physics, Tesla C1060, Tesla S1070

March 8, 2011 by hgpu

Non-blocking programming on multi-core graphics processors: (extended asbtract)

Phuong Hoai Ha, Philippas Tsigas, Otto J. Anshus

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques

March 7, 2011 by hgpu

Performance study of mapping irregular computations on GPUs

Steven Solomon, Parimala Thulasiraman

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Performance, Presentation

March 6, 2011 by hgpu

Tuned and asynchronous stencil kernels for CPU/GPU systems (thesis)

Sundaresan Venkatasubramanian

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 570, Performance, Tesla C1060, Tesla C870, Thesis

March 6, 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

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high performance computing on graphics processing units: hgpu.org

Aspects of GPU for general purpose high performance computing

Improving accuracy for matrix multiplications on GPUs

Performance comparison of FPGA, GPU and CPU in image processing

An approach for the effective utilization of GP-GPUs in parallel combined simulation

Joint Forces: From Multithreaded Programming to GPU Computing

Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters

Implementing the Himeno benchmark with CUDA on GPU clusters

Patterns of Inefficient Performance Behavior in GPU Applications

General-purpose molecular dynamics simulations on GPU-based clusters

Non-blocking programming on multi-core graphics processors: (extended asbtract)

Performance study of mapping irregular computations on GPUs

Tuned and asynchronous stencil kernels for CPU/GPU systems (thesis)

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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