1053
hgpu.org » Review

How GPUs Work

David Luebke, Greg Humphreys
View View   Download Download (PDF)   

Tags: ,

October 30, 2010 by hgpu

GPUs: A Closer Look

Kayvon Fatahalian, Mike Houston
View View   Download Download (PDF)   

Tags: ,

October 30, 2010 by hgpu

Mapping computational concepts to GPUs

Mark Harris
View View   Download Download (PDF)   

Tags: ,

October 30, 2010 by hgpu

Rise of the Graphics Processor

D. Blythe
View View   Download Download (PDF)   

Tags: ,

October 30, 2010 by hgpu

The GPU Computing Era

John Nickolls,William J. Dally

Tags: ,

October 27, 2010 by hgpu

GPU Computing

John D. Owens,Mike Houston,David Luebke,Simon Green,John E. Stone,James C. Phillips
View View   Download Download (PDF)   

Tags: , , ,

October 27, 2010 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
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
BoltzGen:Toward Universal Binder Design

BoltzGen:Toward Universal Binder Design

BoltzGen:Toward Universal Binder Design
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

* * *

* * *

HGPU group © 2010-2026 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: