high performance computing on graphics processing units: hgpu.org

hgpu.org » ATI

OpenMP Advisor

Alok Mishra, Abid M. Malik, Meifeng Lin, Barbara Chapman

View

Tags: AMD Radeon Instinct Mi50, ATI, Benchmarking, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, OpenMP, Tesla A100, Tesla K80, Tesla V100

January 15, 2023 by hgpu

Providing performance portable numerics for Intel GPUs

Yu-Hsiang M. Tsai, Terry Cojean, Hartwig Anzt

View

Download (PDF)

Source codes

Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, Linear Algebra, nVidia, nVidia A100, OpenCL, Package, performance portability, Sparse, SYCL

October 30, 2022 by hgpu

From Task-Based GPU Work Aggregation to Stellar Mergers: Turning Fine-Grained CPU Tasks into Portable GPU Kernels

Gregor Daiß, Patrick Diehl, Dominic Marcello, Alireza Kheirkhahan, Hartmut Kaiser, Dirk Pflüger

View

Download (PDF)

Source codes

Tags: AMD Radeon Instinct MI100, Astrophysics, ATI, CUDA, HIP, nVidia, nVidia A100, Package, performance portability, Physics

October 23, 2022 by hgpu

PMT: Power Measurement Toolkit

Stefano Corda, Bram Veenboer, Emma Tolley

View

Download (PDF)

Source codes

Tags: AMD Radeon Pro W6600, ATI, Computer science, Energy-efficient computing, HPC, nVidia, nVidia Titan RTX, Package, Performance

October 16, 2022 by hgpu

Benchmarking optimization algorithms for auto-tuning GPU kernels

Richard Schoonhoven, Ben van Werkhoven, Kees Joost Batenburg

View

Download (PDF)

Tags: AMD Radeon Instinct Mi50, ATI, Auto-Tuning, Benchmarking, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX Titan X, nVidia Titan RTX, OpenCL, Performance, pyCUDA, PyOpenCL, Tesla K20, Tesla P100, Tesla V100

October 9, 2022 by hgpu

Enhancing the Performance Portability of Heterogeneous Circuit Analysis Programs

Tsung-Wei Huang

View

Download (PDF)

Tags: AMD Radeon RX 6900 XT, ATI, Computer science, Deep learning, nVidia, nVidia GeForce RTX 3090, OpenCL, performance portability, PyTorch, SYCL

September 11, 2022 by hgpu

Towards making the most of NLP-based device mapping optimization for OpenCL kernels

Petros Vavaroutsos, Ioannis Oroutzoglou, Dimosthenis Masouros, Dimitrios Soudris

View

Download (PDF)

Tags: AMD Radeon HD 7970, ATI, Computer science, Deep learning, Machine learning, NLP, nVidia, nVidia GeForce GTX 970, OpenCL

September 4, 2022 by hgpu

Optimization of GPU workloads using natural language processing based on deep learning techniques

Petros Vavaroutsos

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 970, OpenCL, Thesis

August 21, 2022 by hgpu

Deep Learning Approaches to Source Code Analysis for Optimization of Heterogeneous Systems: Recent Results, Challenges and Opportunities

Francesco Barchi, Emanuele Parisi, Andrea Bartolini, Andrea Acquaviva

View

Download (PDF)

Tags: AMD Radeon HD 7970, ATI, Computer science, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 970, OpenCL, Optimization, Overview, Security

August 7, 2022 by hgpu

Reducing Synchronous GPU Memory Transfers: Design and implementation of a Futhark compiler optimisation

Philip Jon Børgesen

View

Download (PDF)

Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, nVidia, nVidia A100, OpenCL, Performance, Thesis

July 17, 2022 by hgpu

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

Shilei Tian, Joseph Huber, Barbara Chapman, Johannes Doerfert

View

Download (PDF)

Tags: AMD Radeon Instinct MI100, ATI, Compilers, Computer science, CUDA, nVidia, nVidia A100, OpenCL, OpenMP

July 17, 2022 by hgpu

Fast GPU bounding boxes on tree-structured scenes

Raph Levien

View

Download (PDF)

Source codes

Tags: 3D Graphics and Realism, AMD Radeon RX 5700 XT, ATI, GLSL, HLSL, nVidia, nVidia GeForce GTX 1080, Package, Rendering, Vulkan

May 29, 2022 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

OpenMP Advisor

Providing performance portable numerics for Intel GPUs

From Task-Based GPU Work Aggregation to Stellar Mergers: Turning Fine-Grained CPU Tasks into Portable GPU Kernels

PMT: Power Measurement Toolkit

Benchmarking optimization algorithms for auto-tuning GPU kernels

Enhancing the Performance Portability of Heterogeneous Circuit Analysis Programs

Towards making the most of NLP-based device mapping optimization for OpenCL kernels

Optimization of GPU workloads using natural language processing based on deep learning techniques

Deep Learning Approaches to Source Code Analysis for Optimization of Heterogeneous Systems: Recent Results, Challenges and Opportunities

Reducing Synchronous GPU Memory Transfers: Design and implementation of a Futhark compiler optimisation

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

Fast GPU bounding boxes on tree-structured scenes

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)