high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Many-Core Compiler Fuzzing

Christopher Lidbury, Andrei Lascu, Nathan Chong, Alastair F. Donaldson

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Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Compilers, Computer science, FPGA, Intel HD 4600, Intel Xeon Phi, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX Titan, OpenCL, Tesla K40, Tesla M2050

July 10, 2015 by hgpu

Towards Good Practices for Very Deep Two-Stream ConvNets

Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao

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Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, MPI, nVidia, OpenMPI, Package

July 10, 2015 by hgpu

Multiple String Matching on a GPU using CUDAs

Charalampos S. Kouzinopoulos, Panagiotis D. Michailidis, Konstantinos G. Margaritis

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Tags: Algorithms, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, String matching

July 10, 2015 by hgpu

Learning Better Encoding for Approximate Nearest Neighbor Search with Dictionary Annealing

Shicong Liu, Hongtao Lu

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Tags: Computer science, Databases, Nearest neighbour, nVidia, nVidia GeForce GTX 980, Optimization, Vector quantization

July 8, 2015 by hgpu

Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing

Alexey Lastovetsky, Lukasz Szustak, Roman Wyrzykowski

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Tags: Computer science, Intel Xeon Phi, Performance

July 8, 2015 by hgpu

Autotuning OpenACC Work Distribution via Direct Search

Calvin Montgomery, Jeffrey L. Overbey, Xuechao Li

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Tags: Computer science, MPI, nVidia, OpenACC, Package, Performance, Python, Tesla K20

July 8, 2015 by hgpu

Experiments on Parallel Training of Deep Neural Network using Model Averaging

Hang Su, Haoyu Chen

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Tags: Computer science, CUDA, Deep learning, MPI, Neural networks, nVidia, Tesla K20

July 8, 2015 by hgpu

Sorting and Permuting without Bank Conflicts on GPUs

Peyman Afshani, Nodari Sitchinava

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Tags: Algorithms, Computer science, Performance, Sorting

July 8, 2015 by hgpu

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Anton Akusok, Kaj-Mikael Bjork, Yoan Miche, Amaury Lendasse

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, OpenCL, Package, Python

July 6, 2015 by hgpu

LTTng CLUST: A system-wide unified CPU and GPU tracing tool for OpenCL applications

David Couturier, Michel R. Dagenais

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Tags: Computer science, Intel HD 4600, OpenCL, Performance

July 6, 2015 by hgpu

Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources

Kai Zhang, Feng Chen, Xiaoning Ding, Yin Huai, Rubao Lee, Tian Luo, Kaibo Wang, Yuan Yuan, Xiaodong Zhang

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Tags: Computer science, CUDA, Data parallelism, Databases, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL

July 6, 2015 by hgpu

Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores

Kai Zhang, Kaibo Wang, Yuan Yuan, Lei Guo, Rubao Lee, Xiaodong Zhang

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Tags: Computer science, CUDA, Data parallelism, Databases, nVidia, nVidia GeForce GTX 780, Package

July 6, 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

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high performance computing on graphics processing units: hgpu.org

Applications

Many-Core Compiler Fuzzing

Towards Good Practices for Very Deep Two-Stream ConvNets

Multiple String Matching on a GPU using CUDAs

Learning Better Encoding for Approximate Nearest Neighbor Search with Dictionary Annealing

Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing

Autotuning OpenACC Work Distribution via Direct Search

Experiments on Parallel Training of Deep Neural Network using Model Averaging

Sorting and Permuting without Bank Conflicts on GPUs

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

LTTng CLUST: A system-wide unified CPU and GPU tracing tool for OpenCL applications

Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources

Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores

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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