high performance computing on graphics processing units: hgpu.org

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Expanding the boundaries of GPU computing

Dell Power Solutions

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, Review, Tesla M1060, Tesla M2050, Tesla M2070

March 14, 2011 by hgpu

A Quantitative Performance Analysis Model for GPU Architectures

Yao Zhang, John D. Owens

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Tags: Computer science, CUDA, Hardware Architecture, Linear Algebra, nVidia, nVidia GeForce GTX 285, Optimization

March 13, 2011 by hgpu

A Predictive Shutdown Technique for GPU Shader Processors

Po-Han Wang, Yen-Ming Chen, Chia-Lin Yang, Yu-Jung Cheng

Tags: Computer science, Energy-efficient computing, Hardware Architecture

March 10, 2011 by hgpu

Architecting graphics processors for non-graphics compute acceleration

Tor M. Aamodt

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Tags: Computer science, Hardware Architecture, nVidia, Review

February 20, 2011 by hgpu

Design Space Exploration for GPU-Based Architecture

Zhenyu Ye

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Tags: Computer science, CUDA, Factorization, Hardware Architecture, Memory model, nVidia, nVidia GeForce 8800 GTX, Review, Thesis

February 20, 2011 by hgpu

Increasing Memory Miss Tolerance for SIMD Cores

David Tarjan, Jiayuan Meng and Kevin Skadron

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Tags: Computer science, Hardware Architecture, Performance

February 12, 2011 by hgpu

On testing GPU memory for hard and soft errors

Guochun Shi, Jeremy Enos, Michael Showerman, Volodymyr Kindratenko

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Source codes

Tags: Computer science, CUDA, Hardware Architecture, Memory, nVidia, Package, Tesla C1060, Tesla S1070

February 3, 2011 by hgpu

3D GPU Architecture using Cache Stacking: Performance, Cost, Power and Thermal analysis

Ahmed Al Maashri, Guangyu Sun, Xiangyu Dong, Vijay Narayanan and Yuan Xie

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Tags: Computer science, CUDA, Hardware Architecture, Memory, Memory model, nVidia, nVidia GeForce 6400 GT

February 3, 2011 by hgpu

Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in GPGPU

Imran S. Haque, Vijay S. Pande

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9500 GT, Package, Tesla C870

November 9, 2010 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Expanding the boundaries of GPU computing

A Quantitative Performance Analysis Model for GPU Architectures

A Predictive Shutdown Technique for GPU Shader Processors

Architecting graphics processors for non-graphics compute acceleration

Design Space Exploration for GPU-Based Architecture

Increasing Memory Miss Tolerance for SIMD Cores

On testing GPU memory for hard and soft errors

3D GPU Architecture using Cache Stacking: Performance, Cost, Power and Thermal analysis

Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in GPGPU

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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