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Genetically Improved CUDA kernels for StereoCamera

W. B. Langdon, M. Harman

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Tags: Computer science, CUDA, Evolutionary Computations, Genetic programming, nVidia, nVidia GeForce GTX 580, Package, Tesla C2050, Tesla K20, Tesla T10

March 12, 2014 by hgpu

GPU-EvR: Run-time Event Based Real-time Scheduling Framework on GPGPU Platform

Haeseung Lee, Mohammad Abdullah Al Faruque

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Tags: Computer science, nVidia, Task scheduling, Tesla K20

March 10, 2014 by hgpu

Massively parallel read mapping on GPUs with PEANUT

Johannes Koster, Sven Rahmann

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Tags: Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 780, OpenCL, Package, Python

March 10, 2014 by hgpu

RASR/NN: The RWTH Neural Network Toolkit for Speech Recognition

Simon Wiesler, Alexander Richard, Pavel Golik, Ralf Schluter, Hermann Ney

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Tags: Algorithms, Computer science, CUDA, Neural networks, nVidia, Speech recognition, Tesla K20

March 9, 2014 by hgpu

A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing

H.I. Alzeini, Sh.A. Hameed, M.H. Habaebi

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Tags: Algorithms, Computer science, Heterogeneous systems

March 9, 2014 by hgpu

Designing Efficient MPI and UPC Runtime for Multicore Clusters with InfiniBand, Accelerators and Co-Processors

Miao Luo

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Tesla C2050

March 9, 2014 by hgpu

Converting Data to Task-Parallelism by Rewrites

Ryan R. Newton, Eric Holk, Trevor L. McDonell

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Tags: Computer science, CUDA, Haskell, nVidia, Package, Task scheduling, Tesla C2075

March 7, 2014 by hgpu

Exploring High Performance SQL Databases with Graphics Processing Units

Glen Hordemann

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GTX 680, Text mining, Thesis

March 7, 2014 by hgpu

Interactive Program Debugging and Optimization for Directive-Based, Efficient GPU Computing

Seyong Lee, Dong Li, Jeffrey S. Vetter

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Tags: Benchmarking, Computer science, CUDA, nVidia, OpenACC, Performance, Tesla M2090

March 7, 2014 by hgpu

Dynamic Workload Division in GPU-CPU Heterogeneous Systems

Wei Chen

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2070, Thesis

March 7, 2014 by hgpu

OCCA: A unified approach to multi-threading languages

David S Medina, Amik St-Cyr, T. Warburton

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Tags: ATI, ATI Radeon HD 7970, ATI Radeon HD 7990, Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX Titan, OpenCL, Spectral elements

March 6, 2014 by hgpu

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

M.G.B. Johnson, D. P. Playne, K.A. Hawick

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 660 M, nVidia GeForce GTX 680, Performance, Tesla M2050, Tesla M2070, Tesla M2075, Tesla M2090

March 6, 2014 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

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high performance computing on graphics processing units: hgpu.org

Genetically Improved CUDA kernels for StereoCamera

GPU-EvR: Run-time Event Based Real-time Scheduling Framework on GPGPU Platform

Massively parallel read mapping on GPUs with PEANUT

RASR/NN: The RWTH Neural Network Toolkit for Speech Recognition

A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing

Designing Efficient MPI and UPC Runtime for Multicore Clusters with InfiniBand, Accelerators and Co-Processors

Converting Data to Task-Parallelism by Rewrites

Exploring High Performance SQL Databases with Graphics Processing Units

Interactive Program Debugging and Optimization for Directive-Based, Efficient GPU Computing

Dynamic Workload Division in GPU-CPU Heterogeneous Systems

OCCA: A unified approach to multi-threading languages

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

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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