high performance computing on graphics processing units: hgpu.org

hgpu.org » Computer science

Exposing Errors Related to Weak Memory in GPU Applications

Tyler Sorensen, Alastair F. Donaldson

View

Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, nVidia Quadro K5200, Tesla C2050, Tesla C2075, Tesla K20

May 3, 2016 by hgpu

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

Andreas Klockner, Lucas C. Wilcox, T. Warburton

View

Download (PDF)

Source codes

Tags: Algorithms, AMD Radeon R9 Fury, ATI, Code generation, Computer science, Fortran, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, Prefetch, Programming Languages, Python, Tesla K40

April 29, 2016 by hgpu

On the design of sparse hybrid linear solvers for modern parallel architectures

Stojce Nakov

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, MPI, nVidia, Sparse linear iterative solvers, Sparse matrix, Tesla K40, Tesla M2070, Thesis

April 29, 2016 by hgpu

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

Alcides Fonseca, Bruno Cabral, Joao Rafael, Ivo Correia

View

Download (PDF)

Source codes

Tags: Computer science, Java, OpenCL, Package, Programming Languages

April 29, 2016 by hgpu

Adaptive GPU Array Layout Auto-Tuning

Nicolas Weber, Michael Goesele

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Linear Algbera, nVidia, nVidia GeForce GTX Titan X, Package, Performance, Tesla K20

April 29, 2016 by hgpu

Parallel Subgraph Mining on Hybrid Platforms: HPC Systems, Multi-Cores and GPUs

Nilothpal Talukder

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Data mining, Databases, MPI, nVidia, Tesla C2075, Thesis

April 29, 2016 by hgpu

GPU-Aware Non-contiguous Data Movement In Open MPI

Wei Wu, George Bosilca, Rolf vandeVaart, Sylvain Jeaugey, Jack Dongarra

View

Download (PDF)

Tags: Computer science, CUDA, MPI, nVidia, Tesla K40

April 26, 2016 by hgpu

Investigating performance portability of a highly scalable particle-in-cell simulation code on various multi-core architectures

Benjamin Worpitz

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Intel Xeon Phi, OpenMP, Package, Particle-in-cell methods, Performance, performance portability, Tesla K20, Tesla K80, Thesis

April 26, 2016 by hgpu

To Co-Run, or Not To Co-Run: A Performance Study on Integrated Architectures

Feng Zhang, Jidong Zhai, Wenguang Chen, Bingsheng He, Shuhao Zhang

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, OpenCL, Package

April 26, 2016 by hgpu

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

Ilya Loshchilov, Frank Hutter

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Package, Python

April 26, 2016 by hgpu

GPL: A GPU-based Pipelined Query Processing Engine

Johns Paul, Jiong He, Bingsheng He

View

Download (PDF)

Tags: Analytical model, Computer science, Databases, nVidia, OpenCL

April 24, 2016 by hgpu

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

M. Abalenkovs, A. Abdelfattah, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, I. Yamazaki, A. YarKhan

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, OpenCL, Programming techniques, Review, Tesla K40

April 19, 2016 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

* * *

high performance computing on graphics processing units: hgpu.org

Exposing Errors Related to Weak Memory in GPU Applications

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

On the design of sparse hybrid linear solvers for modern parallel architectures

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

Adaptive GPU Array Layout Auto-Tuning

Parallel Subgraph Mining on Hybrid Platforms: HPC Systems, Multi-Cores and GPUs

GPU-Aware Non-contiguous Data Movement In Open MPI

Investigating performance portability of a highly scalable particle-in-cell simulation code on various multi-core architectures

To Co-Run, or Not To Co-Run: A Performance Study on Integrated Architectures

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

GPL: A GPU-based Pipelined Query Processing Engine

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

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

Most viewed papers (last 30 days)