high performance computing on graphics processing units: hgpu.org

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Run-time Reconfigurable Multiprocessors

Madhura Purnaprajna

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Tags: ATI, Computer science, FPGA, Hardware Architecture, nVidia, Performance, Thesis

October 7, 2011 by hgpu

Architecture-Aware Optimization on a 1600-core Graphics Processor

Mayank Daga, Thomas R.W. Scogland, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, Cluster computing, Computer science, CUDA, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Tesla C2050

October 4, 2011 by hgpu

Finite element assembly strategies on multi-and many-core architectures

G. R. Markall, A. Slemmer, D. A .Ham, P. H. J. Kelly, C. D. Cantwell, S. J. Sherwin

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Tags: Algorithms, ATI, ATI Radeon HD 5870, CUDA, FEM, Finite element method, Fluid dynamics, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Spectral elements

October 4, 2011 by hgpu

GPU-Accelerated DNA Distance Matrix Computation

Zhi Ying, Xinhua Lin, Simon Chong-Wee See, Minglu Li

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Tags: ATI, ATI Radeon HD 5850, Bioinformatics, Biology, Genetics, nVidia, OpenCL, Performance, Tesla C2050

October 3, 2011 by hgpu

An Auto-tuning Solution to Data Streams Clustering in OpenCL

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips

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Tags: ATI, ATI Radeon HD 5870, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Optimization, Performance

October 3, 2011 by hgpu

A Complete Descritpion of the UnPython and Jit4GPU Framework

Rahul Garg, Jose Nelson Amaral

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Tags: ATI, ATI CAL, ATI IL, ATI Radeon HD 5850, ATI Stream, Compilers, Computer science, OpenMP, Optimization, Performance, Python

October 2, 2011 by hgpu

CheCL: Transparent Checkpointing and Process Migration of OpenCL Applications

Hiroyuki Takizawa, Kentaro Koyama, Katuto Sato, Kazuhiko Komatsu, Hiroaki Kobayashi

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Tags: ATI, ATI Radeon HD 5870, Code generation, Compilers, Computer science, MPI, nVidia, OpenCL, Tesla C1060

October 1, 2011 by hgpu

A Comprehensive Performance Comparison of CUDA and OpenCL

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Cell processor, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Optimization, Performance

October 1, 2011 by hgpu

Large Scale DNA Sequence Alignment and Kernel Method Implemented with GPUs

Songwen Pei, Wenhao Wang, Gang Wei, Baifeng Wu

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Tags: Algorithms, ATI, ATI Radeon HD 4870, Bioinformatics, Biology, Brook, Sequence alignment

October 1, 2011 by hgpu

Image registration on GPU

Jeremy Coatelen, Yu Qi

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Tags: Algorithms, ATI, ATI Mobility Radeon HD 5850, Cloud, Image processing, Image registration, nVidia, OpenCL

October 1, 2011 by hgpu

Architecture-Aware Mapping and Optimization on Heterogeneous Computing Systems

Mayank Daga

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Heterogeneous systems, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Tesla C2050, Thesis

September 30, 2011 by hgpu

Stack-less SIMT reconvergence at low cost

Sylvain Collange

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Tags: ATI, Computer science, Hardware Architecture, Memory, nVidia, Performance

September 30, 2011 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

Run-time Reconfigurable Multiprocessors

Architecture-Aware Optimization on a 1600-core Graphics Processor

Finite element assembly strategies on multi-and many-core architectures

GPU-Accelerated DNA Distance Matrix Computation

An Auto-tuning Solution to Data Streams Clustering in OpenCL

A Complete Descritpion of the UnPython and Jit4GPU Framework

CheCL: Transparent Checkpointing and Process Migration of OpenCL Applications

A Comprehensive Performance Comparison of CUDA and OpenCL

Large Scale DNA Sequence Alignment and Kernel Method Implemented with GPUs

Architecture-Aware Mapping and Optimization on Heterogeneous Computing Systems

Stack-less SIMT reconvergence at low cost

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

Most viewed papers (last 30 days)