high performance computing on graphics processing units: hgpu.org

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GPU Computing Gems: Emerald Edition

edited by: W. W. Hwu

Tags: Algorithms, Book, Computer science, CUDA, nVidia, Programming techniques

March 9, 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

Object-oriented stream programming using aspects

Mingliang Wang, M. Parashar

Tags: Computer science, CUDA, Hybrid computing, nVidia, nVidia GeForce GTX 280, Programming techniques

March 7, 2011 by hgpu

Object-oriented stream programming using Aspects: a high-productivity programming paradigm for hybrid platforms

Mingliang Wang

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Tags: Computer science, CUDA, Hybrid computing, nVidia, nVidia GeForce GTX 280, Programming techniques, Thesis

March 7, 2011 by hgpu

A Stream Processor Cluster Architecture Model with the Hybrid Technology of MPI and CUDA

Qing-kui Chen, Jia-kang Zhang

Tags: Computer science, CUDA, GPU cluster, MPI, nVidia, Programming techniques

March 4, 2011 by hgpu

Formal Description and Optimization Based High – Performance Computing on CUDA

Bo Li, Huacheng Zhao, Jingjing Liang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8600 GT, Optimization, Programming techniques

March 4, 2011 by hgpu

Towards a Software Transactional Memory for Graphics Processors

Daniel Cederman, Philippas Tsigas and Muhammad Tayyab Chaudhry

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, Programming techniques

March 4, 2011 by hgpu

Architecture-Aware Optimization Targeting Multithreaded Stream Computing

Byunghyun Jang, Synho Do, Homer Pien, David Kaeli

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Tags: ATI, ATI Radeon HD 3870, Brook, Computer science, Optimization, Programming techniques

March 4, 2011 by hgpu

Unified – A Sharp Turn in the Latest Era of Graphic Processors

Asma Kausar, Aziz Khan, Zulfiqar Ali

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Programming techniques, Review

March 3, 2011 by hgpu

Bothnia: a dual-personality extension to the Intel integrated graphics driver

Gautham N. Chinya, Jamison D. Collins, Perry H. Wang, Hong Jiang, Guei Y. Lueh, Thomas A. Piazza, Hong Wang

Tags: Computer science, Intel, Intel GMA X3000, Programming techniques

February 28, 2011 by hgpu

Data Buffering Optimization Methods toward a Uniform Programming Interface for GPU-based Applications

Shinichi Yamagiwa, Leonel Sousa, Diogo Antao

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Tags: Computer science, DirectX, nVidia, nVidia GeForce 7400 GO, OpenGL, Programming techniques

February 27, 2011 by hgpu

Accelerating CUDA Graph Algorithms at Maximum Warp

Sungpack Hong, Sang Kyun Kim, Tayo Oguntebi, Kunle Olukotun

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Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 275, Package, Performance, Programming techniques

February 27, 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

GPU Computing Gems: Emerald Edition

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

Object-oriented stream programming using aspects

Object-oriented stream programming using Aspects: a high-productivity programming paradigm for hybrid platforms

A Stream Processor Cluster Architecture Model with the Hybrid Technology of MPI and CUDA

Formal Description and Optimization Based High – Performance Computing on CUDA

Towards a Software Transactional Memory for Graphics Processors

Architecture-Aware Optimization Targeting Multithreaded Stream Computing

Unified – A Sharp Turn in the Latest Era of Graphic Processors

Bothnia: a dual-personality extension to the Intel integrated graphics driver

Data Buffering Optimization Methods toward a Uniform Programming Interface for GPU-based Applications

Accelerating CUDA Graph Algorithms at Maximum Warp

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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