high performance computing on graphics processing units: hgpu.org

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Performance Improvement of TOUGH2 Simulation with Graphics Processing Unit

Yusuke Shimotoku, Toshiaki Tanaka, Ryuichi Itoi

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Tags: Computer science, CUDA, nVidia, Performance, Tesla C2070

September 10, 2012 by hgpu

Performance Evaluation of Concurrent Lock-free Data Structures on GPUs

Prabhakar Misra, Mainak Chaudhuri

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, Performance, Tesla C2070

September 8, 2012 by hgpu

Can GPGPU Programming Be Liberated from the Data-Parallel Bottleneck?

Benedict R. Gaster, Lee Howes

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, OpenCL, Performance

September 7, 2012 by hgpu

Architectural Analysis and Performance Characterization of NVIDIA GPUs using Microbenchmarking

Saktheesh Subramoniapillai Ajeetha

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, Performance, Tesla C2050, Thesis

September 6, 2012 by hgpu

Automated Enhanced Parallelization of Sequential C to Parallel OpenMP

Dheeraj D., Shruti Ramesh, Nitish B.

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Tags: Computer science, MPI, OpenMP, Performance

September 4, 2012 by hgpu

Parallel Data List Processing on Multicore-GPU Platforms

Carlos Alberto Martinez-Angeles, Jorge Buenabad-Chavez, Miguel Alfonso Castro-Garcia, Jose Luis Quiroz-Fabian

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 460, Performance

August 30, 2012 by hgpu

GPUVerify: A Verifier for GPU Kernels

Adam Betts, Nathan Chong, Alastair F. Donaldson, Shaz Qadeer, Paul Thomson

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Source codes

Tags: ARM, ATI, ATI Radeon HD 7970, Code generation, Computer science, CUDA, nVidia, OpenCL, Package, Performance, Tesla C2050

August 28, 2012 by hgpu

Performance Comparison Between Cg-based and CUDA-based Matrix Multiplications

Luke West, Jong Kwan Lee

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Tags: Cg, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance

August 28, 2012 by hgpu

Optimization Techniques for CUDA Application

Tushar Athawale, Xie Xu

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, Optimization, Performance

August 28, 2012 by hgpu

Efficient Dynamic Program Monitoring on Multi-Core Platforms

Guojin He

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro FX 5800, Performance, Security, Thesis

August 26, 2012 by hgpu

A Braille Conversion Service Using GPU and Human Interaction by Computer Vision

Roman Graf, Reinhold Huber-Mork

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 460, Pattern recognition, Performance

August 26, 2012 by hgpu

Supporting Preemptive Task Executions and Memory Copies in GPGPUs

Can Basaran, Kyoung-Don Kang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 460, Performance, Task scheduling

August 21, 2012 by hgpu

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

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high performance computing on graphics processing units: hgpu.org

Performance Improvement of TOUGH2 Simulation with Graphics Processing Unit

Performance Evaluation of Concurrent Lock-free Data Structures on GPUs

Can GPGPU Programming Be Liberated from the Data-Parallel Bottleneck?

Architectural Analysis and Performance Characterization of NVIDIA GPUs using Microbenchmarking

Automated Enhanced Parallelization of Sequential C to Parallel OpenMP

Parallel Data List Processing on Multicore-GPU Platforms

GPUVerify: A Verifier for GPU Kernels

Performance Comparison Between Cg-based and CUDA-based Matrix Multiplications

Optimization Techniques for CUDA Application

Efficient Dynamic Program Monitoring on Multi-Core Platforms

A Braille Conversion Service Using GPU and Human Interaction by Computer Vision

Supporting Preemptive Task Executions and Memory Copies in GPGPUs

Recent source codes

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

LC Framework

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