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hgpu.org » AMD

APUNet: Revitalizing GPU as Packet Processing Accelerator

Younghwan Go, Muhammad Jamshed, YoungGyoun Moon, Changho Hwang, KyoungSoo Park
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March 28, 2017 by hgpu

TREES: A CPU/GPU Task-Parallel Runtime with Explicit Epoch Synchronization

Blake A. Hechtman, Andrew D. Hilton, Daniel J. Sorin
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August 4, 2016 by hgpu

Fast reconstruction of 3D volumes from 2D CT projection data with GPUs

M. Leeser, S. Mukherjee, J. Brock
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September 1, 2014 by hgpu

Implementation of Just In Time Value Specialization for the Optimization of Data Parallel Kernels

N. Tuck
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March 28, 2014 by hgpu

Multi-tier Dynamic Vectorization for Translating GPU Optimizations into CPU Performance

Hee-Seok Kim, Izzat El Hajj, John A. Stratton, Wen-Mei W. Hwu
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February 12, 2014 by hgpu

Hybrid strategy for stencil computations on the APU

Pacome Eberhart, Issam Said, Pierre Fortin
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January 26, 2014 by hgpu

OmniDB: Towards Portable and Efficient Query Processing on Parallel CPU/GPU Architectures

Shuhao Zhang, Jiong He, Bingsheng He, Mian Lu
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July 12, 2013 by hgpu

Recent source codes

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

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

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation
SeedFold: Scaling Biomolecular Structure Prediction

SeedFold: Scaling Biomolecular Structure Prediction

SeedFold: Scaling Biomolecular Structure Prediction
Tilus: A Tile-Level GPU Kernel Programming Language

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

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

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs
BoltzGen:Toward Universal Binder Design

BoltzGen:Toward Universal Binder Design

BoltzGen:Toward Universal Binder Design
CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

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

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning
cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

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

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution
MATLAB Tensor Core models

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores
TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

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

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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