high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

OpenMP Kernel Language Extensions for Performance Portable GPU Codes

Shilei Tian, Tom Scogland, Barbara Chapman, Johannes Doerfert

View

Tags: AMD Radeon Instinct MI250, ATI, Benchmarking, Compilers, Computer science, CUDA, HIP, nVidia, nVidia A100, OpenMP, performance portability

October 1, 2023 by hgpu

Beehive SPIR-V Toolkit: A Composable and Functional API for Runtime SPIR-V Code Generation

Juan Fumero Alfonso, György Rethy, Athanasios Stratikopoulos, Nikolaos Foutris, Christos-Efthymios Kotselidis

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, Heterogeneous systems, Java, OpenCL, Package

October 1, 2023 by hgpu

Novel Parallelization Strategies for High-Performance DNN Training on HPC Systems

Arpan Jain

View

Download (PDF)

Tags: Artificial intelligence, Computer science, CUDA, Data parallelism, Deep learning, HPC, Machine learning, MPI, Neural networks, nVidia, Speech recognition, Tesla K80, Tesla V100, Thesis

October 1, 2023 by hgpu

Evaluating the performance portability of SYCL across CPUs and GPUs on bandwidth-bound applications

Istvan Z Reguly

View

Download (PDF)

Tags: AMD Radeon Instinct MI250X, ATI, Benchmarking, cfd, Computer science, CUDA, Fluid dynamics, HIP, Intel, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, OpenCL, performance portability, SYCL

September 24, 2023 by hgpu

Comparing Performance and Portability between CUDA and SYCL for Protein Database Search on NVIDIA, AMD, and Intel GPUs

Manuel Costanzo, Enzo Rucci, Carlos García Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

View

Download (PDF)

Tags: AMD Radeon RX 6700 XT, ATI, Bioinformatics, Biology, Computer science, CUDA, Intel, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3070, nVidia GeForce RTX 3090, oneAPI, Programming Languages, Smith-Waterman algorithm, SYCL, Tesla V100

September 24, 2023 by hgpu

Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation

Pedro Valero-Lara, Alexis Huante, Mustafa Al Lail, William F. Godoy, Keita Teranishi, Prasanna Balaprakash, Jeffrey S. Vetter

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, Deep learning, Fortran, HIP, HPC, nVidia, OpenACC, OpenMP, Package, Python

September 17, 2023 by hgpu

Improving the Efficiency of OpenCL Kernels through Pipes

Mostafa Eghbali Zarch, Michela Becchi

View

Download (PDF)

Tags: Computer science, FPGA, OpenCL, Performance, performance portability

September 17, 2023 by hgpu

Many Cores, Many Models: GPU Programming Model vs. Vendor Compatibility Overview

Andreas Herten

View

Download (PDF)

Tags: Computer science, CUDA, Fortran, HIP, HPC, nVidia, Overview, programming model, SYCL

September 17, 2023 by hgpu

host device — Generic programming in Cuda

Thomas Mejstrik

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Programming Languages

September 17, 2023 by hgpu

Unified Shared Memory: Friend or Foe?

Juan Fumero Alfonso, Florin-Gabriel Blanaru, Athanasios Stratikopoulos, Steve Dohrmann, Sandhya Viswanathan, Christos-Efthymios Kotselidis

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, FPGA, Heterogeneous systems, Java, Memory, nVidia, nVidia GeForce RTX 3070, OpenCL

September 17, 2023 by hgpu

PoCL-R: An Open Standard Based Offloading Layer for Heterogeneous Multi-Access Edge Computing with Server Side Scalability

Jan Solanti, Michal Babej, Julius Ikkala, Pekka Jääskeläinen

View

Download (PDF)

Source codes

Tags: Computer science, Distributed computing, Fluid dynamics, Heterogeneous systems, nVidia, nVidia GeForce RTX 2080 Ti, nVidia RTX A6000, OpenCL, Package, Rendering

September 6, 2023 by hgpu

Leveraging Memory Copy Overlap for Efficient Sparse Matrix-Vector Multiplication on GPUs

Guangsen Zeng, Yi Zou

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, nVidia, nVidia A40, Sparse matrix

September 6, 2023 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Programming

OpenMP Kernel Language Extensions for Performance Portable GPU Codes

Beehive SPIR-V Toolkit: A Composable and Functional API for Runtime SPIR-V Code Generation

Novel Parallelization Strategies for High-Performance DNN Training on HPC Systems

Evaluating the performance portability of SYCL across CPUs and GPUs on bandwidth-bound applications

Comparing Performance and Portability between CUDA and SYCL for Protein Database Search on NVIDIA, AMD, and Intel GPUs

Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation

Improving the Efficiency of OpenCL Kernels through Pipes

Many Cores, Many Models: GPU Programming Model vs. Vendor Compatibility Overview

host device — Generic programming in Cuda

Unified Shared Memory: Friend or Foe?

PoCL-R: An Open Standard Based Offloading Layer for Heterogeneous Multi-Access Edge Computing with Server Side Scalability

Leveraging Memory Copy Overlap for Efficient Sparse Matrix-Vector Multiplication on GPUs

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Most viewed papers (last 30 days)