high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Padding Free Bank Conflict Resolution for CUDA-Based Matrix Transpose Algorithm

Ayaz ul Hassan Khan, Mayez Al-Mouhamed, Allam Fatayer, Anas Almousa, Abdulrahman Baqais, Mohammed Assayony

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro FX 7000, Performance

October 29, 2015 by hgpu

CLOP: A Multi-stage Compiler to Seamlessly Embed Heterogeneous Code

Dmitri Makarov, Matthias Hauswirth

View

Download (PDF)

Source codes

Tags: Compilers, Computer science, OpenCL, Package

October 29, 2015 by hgpu

Approximation of BEM matrices using GPGPUs

Steffen Borm, Sven Christophersen

View

Download (PDF)

Tags: Computer science, Fast multipole method, Mathematical Software, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL

October 29, 2015 by hgpu

GPU Ray-Traced Collision Detection for Cloth Simulation

Francois Lehericey, Valerie Gouranton, Bruno Arnaldi

View

Download (PDF)

Tags: 3D Graphics and Realism, Algorithms, AMD FirePro W9100, ATI, Collision detection, Computer science, OpenCL, Raytracing

October 29, 2015 by hgpu

Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Recurrent Neural Network

Peilu Wang, Yao Qian, Frank K. Soong, Lei He, Hai Zhao

View

Download (PDF)

Tags: Computer science, CUDA, Neural networks, NLP, nVidia

October 29, 2015 by hgpu

Evaluation of the Stability and Performance of a Multi-Stage Riemann Solver in Relativistic Hydrodynamic Simulations

J. Sikorski, J. Porter-Sobieraj, D. Kikola, M. Slodkowski, P. Aszklar

View

Download (PDF)

Tags: CUDA, Fluid dynamics, Nuclear Theory, nVidia

October 27, 2015 by hgpu

Pairwise Sequence Alignment with Gaps with GPU

Thomas C. Carroll, Jude-Thaddeus Ojiaku, Prudence W.H. Wong

View

Download (PDF)

Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 650, OpenCL, Sequence alignment

October 27, 2015 by hgpu

Compiling and Optimizing Java 8 Programs for GPU Execution

Kazuaki Ishizaki, Akihiro Hayashi, Gita Koblents, Vivek Sarkar

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, Java, nVidia, OpenCL, Tesla K40

October 27, 2015 by ahayashi

Overlap fermions on GPUs

Nigel Cundy, Weonjong Lee

View

Download (PDF)

Tags: CUDA, High Energy Physics - Lattice, nVidia, nVidia GeForce GTX Titan, Physics

October 27, 2015 by hgpu

Machine-Learning-based Performance Heuristics for Runtime CPU/GPU Selection

Akihiro Hayashi, Kazuaki Ishizaki, Vivek Sarkar, Gita Koblents

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, Java, Machine learning, nVidia, OpenCL, Tesla K40

October 27, 2015 by ahayashi

ZNN – A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-Core and Many-Core Shared Memory Machines

Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung

View

Download (PDF)

Source codes

Tags: CNN, Computer science, Computer vision, Deep learning, FFT, Intel Xeon Phi, Machine learning, Package

October 25, 2015 by hgpu

Modern Gyrokinetic Particle-In-Cell Simulation of Fusion Plasmas on Top Supercomputers

Bei Wang, Stephane Ethier, William Tang, Khaled Ibrahim, Kamesh Madduri, Samuel Williams, Leonid Oliker

View

Download (PDF)

Tags: CUDA, Heterogeneous systems, Intel Xeon Phi, Laplace and Poisson equation, nVidia, Particle-in-cell methods, Physics, Plasma physics, Poisson equation, Tesla K20

October 25, 2015 by hgpu

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Padding Free Bank Conflict Resolution for CUDA-Based Matrix Transpose Algorithm

CLOP: A Multi-stage Compiler to Seamlessly Embed Heterogeneous Code

Approximation of BEM matrices using GPGPUs

GPU Ray-Traced Collision Detection for Cloth Simulation

Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Recurrent Neural Network

Evaluation of the Stability and Performance of a Multi-Stage Riemann Solver in Relativistic Hydrodynamic Simulations

Pairwise Sequence Alignment with Gaps with GPU

Compiling and Optimizing Java 8 Programs for GPU Execution

Overlap fermions on GPUs

Machine-Learning-based Performance Heuristics for Runtime CPU/GPU Selection

ZNN – A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-Core and Many-Core Shared Memory Machines

Modern Gyrokinetic Particle-In-Cell Simulation of Fusion Plasmas on Top Supercomputers

Recent source codes

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

Most viewed papers (last 30 days)