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Exploring Many-Core Design Templates for FPGAs and ASICs

Ilia Lebedev, Christopher Fletcher, Shaoyi Cheng, James Martin, Austin Doupnik, Daniel Burke, Mingjie Lin, John Wawrzynek

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Tags: ASIC, Bayesian, Computer science, FPGA, nVidia, nVidia GeForce GTX 580, OpenCL, Performance

October 30, 2011 by hgpu

Improving Energy Efficiency of GPU based General-Purpose Scientific Computing through Automated Selection of Near Optimal Configurations

Xiaohan Ma, Marion Rincon, Zhigang Deng

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 8800 GT

October 30, 2011 by hgpu

Leveraging Binary Translation for Heterogeneous Profiling

Dan Upton, Kim Hazelwood

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Tags: ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, nVidia, OpenCL, Performance, Tesla C2050

October 30, 2011 by hgpu

GPU Computations in Heterogeneous Grid Environments

Marcus Hinders

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Tags: ATI, ATI Radeon HD 5870, Biology, Computational biology, Computer science, Grid, Heterogeneous systems, nVidia, nVidia GeForce 8600 GT, nVidia GeForce GTX 280, OpenCL, Thesis

October 30, 2011 by hgpu

Dynamic Scheduling of Parallel Code for Heterogeneous Systems

Jeff Brantley, Chris Gregg

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Tags: ATI, ATI Radeon HD 4350, Computer science, Heterogeneous systems, OpenCL, Performance

October 30, 2011 by hgpu

CPU and GPU Co-processing for Sound

Aleksander Gjermundsen

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Source codes

Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Filtering, Linear Algebra, nVidia, nVidia GeForce GTX 280, OpenCL, Package, Signal processing, Tesla C2050, Thesis

October 30, 2011 by hgpu

Jit4OpenCL: a compiler from Python to OpenCL

Xunhao Li

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Tags: ATI, ATI Radeon HD 5850, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, OpenCL, Python, Thesis

October 29, 2011 by hgpu

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Muhammad Mustafa Rafique

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, Prefetch, Software Engineering, Tesla C2050, Thesis

October 28, 2011 by hgpu

Compiling Stream Applications for Heterogeneous Architectures

Amir H. Hormati

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Tags: Compilers, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Optimization, Tesla C2050, Thesis

October 28, 2011 by hgpu

Architectural Exploration and Scheduling Methods for Coarse Grained Reconfigurable Arrays

Giovanni Ansaloni

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Tags: Algorithms, Computer science, Design space exploration, Heterogeneous systems, Thesis

October 28, 2011 by hgpu

Architecture-based Performance Evaluation of Genetic Algorithms on Multi/Many-core Systems

Long Zheng, Yanchao Lu, Mengwei Ding, Yao Shen, Minyi Guo, Song Guo

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 580, Optimization

October 28, 2011 by hgpu

Matrix inversion speed up with CUDA

Jorge Soriano Pinedo

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, Matrix inversion, Matrix multiplication, nVidia, Tesla C1060, Thesis

October 28, 2011 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

Exploring Many-Core Design Templates for FPGAs and ASICs

Improving Energy Efficiency of GPU based General-Purpose Scientific Computing through Automated Selection of Near Optimal Configurations

Leveraging Binary Translation for Heterogeneous Profiling

GPU Computations in Heterogeneous Grid Environments

Dynamic Scheduling of Parallel Code for Heterogeneous Systems

CPU and GPU Co-processing for Sound

Jit4OpenCL: a compiler from Python to OpenCL

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Compiling Stream Applications for Heterogeneous Architectures

Architectural Exploration and Scheduling Methods for Coarse Grained Reconfigurable Arrays

Architecture-based Performance Evaluation of Genetic Algorithms on Multi/Many-core Systems

Matrix inversion speed up with CUDA

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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