high performance computing on graphics processing units: hgpu.org

Niels Drost, Jason Maassen, Maarten A.J. van Meersbergen, Henri E. Bal, F. Inti Pelupessy, Simon Portegies Zwart, Michael Kliphuis, Henk A. Dijkstra, Frank J. Seinstra

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Tags: Astrophysics, Cloud, Computer science, CUDA, Earth and Space Sciences, Heterogeneous systems, nVidia, Physics, Solar and Stellar Astrophysics, Tesla C2050

March 6, 2012 by hgpu

Ray Tracing Visualization Toolkit

Christiaan Gribble, Jeremy Fisher, Daniel Eby, Ed Quigley, Gideon Ludwig

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Tags: 3D Graphics and Realism, Algorithms, Computer science, OpenCL, OpenGL, Raytracing, Rendering, Visualization

March 2, 2012 by hgpu

Efficient Performance Evaluation of Memory Hierarchy for Highly Multithreaded Graphics Processors

Sara S. Baghsorkhi, Isaac Gelado, Matthieu Delahaye, Wen-mei W. Hwu

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Tags: Computer science, CUDA, nVidia, Performance, Sparse matrix, Tesla C2050

March 2, 2012 by hgpu

Parallel Hashing, Compression and Encryption with OpenCL under OS X

Vasileios Xouris

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Tags: Algorithms, Compression, Computer science, Hashing, nVidia, nVidia GeForce 9400 M, nVidia GeForce 9600 M GT, OpenCL, Security, Thesis

March 2, 2012 by hgpu

Chestnut: A GPU Programming Language for Non-Experts

Andrew Stromme, Ryan Carlson, Tia Newhall

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Programming Languages

March 1, 2012 by hgpu

Black-Box Side-Channel Attacks Highlight the Importance of Countermeasures: An Analysis of the Xilinx Virtex-4 and Virtex-5 Bitstream Encryption Mechanism

Amir Moradi, Markus Kasper, Christof Paar

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Tags: AES, Computer science, CUDA, FPGA, nVidia, Security, Tesla C2070

March 1, 2012 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

Paragon: Collaborative Speculative Loop Execution on GPU and CPU

PISTON: A Portable Cross-Platform Framework for Data-Parallel Visualization Operators

Efficient Relational Algebra Algorithms and Data Structures for GPU

PartialRC: A Partial Recomputing Method for Efficient Fault Recovery on GPGPUs

KUDA: GPU Accelerated Split Race Checker

Synthesizing Software from a ForSyDe Model Targeting GPGPUs

Ray Tracing Visualization Toolkit

Efficient Performance Evaluation of Memory Hierarchy for Highly Multithreaded Graphics Processors

Parallel Hashing, Compression and Encryption with OpenCL under OS X

Chestnut: A GPU Programming Language for Non-Experts

Black-Box Side-Channel Attacks Highlight the Importance of Countermeasures: An Analysis of the Xilinx Virtex-4 and Virtex-5 Bitstream Encryption Mechanism

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

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