high performance computing on graphics processing units: hgpu.org

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Extending the Gotran framework: LATEX and GPU acceleration

George Bahijevitch Bahij

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Tags: Computational modelling, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX Titan, ODEs, Ordinary differential equations, Python, Thesis

February 6, 2015 by hgpu

Unlocking Bandwidth for GPUs in CC-NUMA Systems

Neha Agarwal, David Nellans, Mike O'Connor, Stephen W. Keckler, Thomas F. Wenisch

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Prefetch

February 6, 2015 by hgpu

Nucleation Studies on Graphics Processing Units

Benjamin J. Block

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Tags: Anisotropy, ATI, ATI Radeon HD 6970, Biology, Chemistry, Differential equations, Ising model, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, OpenCL, Physics, Tesla K20, Thesis

February 6, 2015 by hgpu

Cryptography on Graphics Processing Unit: A Survey

Alpha Sarita Barik, Srinivas Mishra, Manoranjan Pradhan

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Tags: ATI, Computer science, CUDA, nVidia, OpenCL, Security, survey

February 6, 2015 by hgpu

Comparison of OpenCL performance on different platforms using VexCL and Blaze

Hammad Mazhar, Dan Negrut

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Tags: AMD Radeon R7 260, ATI, Benchmarking, Computer science, Intel Xeon Phi, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 770, OpenCL, Performance, Sparse matrix, Tesla K20

February 6, 2015 by hgpu

Register-leaning kernels in CUDA

Y. Lutsyshyn

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Tags: CUDA, nVidia, nVidia Kepler

February 6, 2015 by ylts

A Survey of Power Management Techniques for Phase Change Memory

Sparsh Mittal

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Tags: cpu, Energy-efficient computing, GPU, Memory, non-volatile memory, Power-efficient computing

February 3, 2015 by sparsh0mittal

Pointer Analysis for Semi-Automatic Code Parallelizers

Ketan Sudhakar Vyavahare

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Tags: Code generation, Computer science, CUDA, OpenCL, Thesis

February 3, 2015 by hgpu

Exploiting Concurrency Patterns with Heterogeneous Task and Data Parallelism

A Geetha Venkatesh

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Tags: Computer science, Data parallelism, Heterogeneous systems, Matrix multiplication, nVidia, OpenCL, Tesla C2070, Thesis

February 3, 2015 by hgpu

GPGPU and MIC in Accelerated Cluster for Remote Sensed Image Processing Software

Olivier MELET, Toon Huysmans, Michel Hummel, Pierre-Marie Brunet

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Tags: CUDA, Image processing, Intel Xeon Phi, nVidia, nVidia GeForce GTX 480, OpenCL, Tesla K20

February 3, 2015 by hgpu

On the Accelerating of Two-dimensional Smart Laplacian Smoothing on the GPU

Kunyang Zhao, Gang Mei, Nengxiong Xu, Jiayin Zhang

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 640, Triangular meshes

February 3, 2015 by hgpu

Scaling Recurrent Neural Network Language Models

Will Williams, Niranjani Prasad, David Mrva, Tom Ash, Tony Robinson

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan

February 3, 2015 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

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

NVIDIA Nemotron Parse 1.1

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Extending the Gotran framework: LATEX and GPU acceleration

Unlocking Bandwidth for GPUs in CC-NUMA Systems

Nucleation Studies on Graphics Processing Units

Cryptography on Graphics Processing Unit: A Survey

Comparison of OpenCL performance on different platforms using VexCL and Blaze

Register-leaning kernels in CUDA

A Survey of Power Management Techniques for Phase Change Memory

Pointer Analysis for Semi-Automatic Code Parallelizers

Exploiting Concurrency Patterns with Heterogeneous Task and Data Parallelism

GPGPU and MIC in Accelerated Cluster for Remote Sensed Image Processing Software

On the Accelerating of Two-dimensional Smart Laplacian Smoothing on the GPU

Scaling Recurrent Neural Network Language Models

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

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

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