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Single Server Multi-GPU Training of ConvNets

Omry Yadan, Keith Adams, Yaniv Taigman, Marc'Aurelio Ranzato

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Tags: Computer science, Computer vision, Machine learning, Neural networks

December 23, 2013 by hgpu

Fast Training of Convolutional Networks through FFTs

Michael Mathieu, Mikael Henaff, Yann LeCun

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Tags: Algorithms, Computer science, Computer vision, CUDA, FFT, Machine learning, nVidia

December 23, 2013 by hgpu

Resource Centered Computing delivering high parallel performance

Jens Gustedt, Stephane Vialle, Patrick Mercier

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Tags: Computer science, CUBLAS, CUDA, GPU cluster, Hierarchical clustering, MPI, nVidia, nVidia GeForce GTX 580

December 22, 2013 by hgpu

Energy Auto-tuning using the Polyhedral Approach

Wei Wang, John Cavazos, Allan Porterfield

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Tags: Computer science, Intel Xeon Phi, Performance

December 22, 2013 by hgpu

Architecting an LTE Base Station with Graphics Processing Units

Q. Zheng, Y. Chen, R. Dreslinski, C. Chakrabarti, A. Anastasopoulos, S. Mahlke, T. Mudge

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Wireless baseband architecture

December 21, 2013 by hgpu

GPU Accelerated Graph SLAM and Occupancy Voxel Based ICP For Encoder-Free Mobile Robots

Adrian Ratter, Claude Sammut, Matthew McGill

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 570

December 21, 2013 by hgpu

Parallel Compact Genetic Algorithm on CUDA-C Platform

Vuppuluri Sumati

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Genetic programming, nVidia

December 21, 2013 by hgpu

Videogame Graphics, BigData & Analytics

Eamonn Killian

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Tags: Book, Computer science, CUDA, Games, OpenCL, OpenGL

December 21, 2013 by hgpu

Warps and Atomics: Beyond Barrier Synchronization in the Verification of GPU Kernels

Ethel Bardsley, Alastair F. Donaldson

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Source codes

Tags: Benchmarking, Computer science, CUDA, nVidia, OpenCL, Package, Python

December 20, 2013 by hgpu

Pannotia: Understanding Irregular GPGPU Graph Applications

Shuai Che, Bradford M. Beckmann, Steven K. Reinhardt, Kevin Skadron

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Tags: Algorithms, ATI, ATI Radeon HD 7950, Computer science, OpenCL

December 20, 2013 by hgpu

Adapting the GA Approach to Solve Traveling Salesman Problems on CUDA Architecture

Ugur Cekmez, Mustafa Ozsiginan, Ozgur Koray Sahingoz

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 740 M, Path problems, Vehicular traffic

December 20, 2013 by hgpu

XSD: Accelerating MapReduce by Harnessing the GPU inside an SSD

Benjamin Y. Cho, Won Seob Jeong, Doohwan Oh, Won Woo Ro

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Tags: Computer science, GPGPU-sim, MapReduce, nVidia, nVidia GeForce GTX 580, nVidia Tegra

December 20, 2013 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

See all packages

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high performance computing on graphics processing units: hgpu.org

Single Server Multi-GPU Training of ConvNets

Fast Training of Convolutional Networks through FFTs

Resource Centered Computing delivering high parallel performance

Energy Auto-tuning using the Polyhedral Approach

Architecting an LTE Base Station with Graphics Processing Units

GPU Accelerated Graph SLAM and Occupancy Voxel Based ICP For Encoder-Free Mobile Robots

Parallel Compact Genetic Algorithm on CUDA-C Platform

Videogame Graphics, BigData & Analytics

Warps and Atomics: Beyond Barrier Synchronization in the Verification of GPU Kernels

Pannotia: Understanding Irregular GPGPU Graph Applications

Adapting the GA Approach to Solve Traveling Salesman Problems on CUDA Architecture

XSD: Accelerating MapReduce by Harnessing the GPU inside an SSD

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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