high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

Apple Silicon Performance in Scientific Computing

Connor Kenyon, Collin Capano

View

Download (PDF)

Tags: Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia A100, nVidia V100, OpenCL, Performance

November 6, 2022 by hgpu

Tausch: A halo exchange library for large heterogeneous computing systems using MPI, OpenCL, and CUDA

Lukas Spies, Amanda Bienz, David Moulton, Luke Olson, Andrew Reisner

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, OpenCL, Package, Tesla V100

October 23, 2022 by hgpu

Towards Performance Portable Programming for Distributed Heterogeneous Systems

Polykarpos Thomadakis, Nikos Chrisochoides

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Package, Performance, performance portability, Tesla V100

October 9, 2022 by hgpu

Decompiling x86 Deep Neural Network Executables

Zhibo Liu, Yuanyuan Yuan, Shuai Wang, Xiaofei Xie, Lei Ma

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce RTX 2080, OpenCL, Package, Security

October 9, 2022 by hgpu

Exploiting dynamic sparse matrices for performance portable linear algebra operations

Chris Stylianou, Michele Weiland

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, HPC, Linear Algebra, MPI, nVidia, OpenMP, Package, Sparse matrix, Tesla V100

October 2, 2022 by hgpu

EnergonAI: An Inference System for 10-100 Billion Parameter Transformer Models

Jiangsu Du, Ziming Liu, Jiarui Fang, Shenggui Li, Yongbin Li, Yutong Lu, Yang You

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, NLP, nVidia, nVidia A100, Package

September 11, 2022 by hgpu

Towards Understanding and Mitigating Memory-Access Challenges in Computing Systems

Mohammad K. Dashti

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Memory model, nVidia, nVidia GeForce RTX 2070, nVidia Jetson TK1, OpenCL, Package, Thesis

August 28, 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

Design and Implementation of ShenWei Universal C/C++

Huanqi Cao, Jiajie Chen

View

Download (PDF)

Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL

August 7, 2022 by hgpu

Demystifying Dependency Bugs in Deep Learning Stack

Kaifeng Huang, Bihuan Chen, Susheng Wu, Junmin Cao, Lei Ma, Xin Peng

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia

July 24, 2022 by hgpu

CPU-GPU Layer-Switched Low Latency CNN Inference

Ehsan Aghapour, Dolly Sapra, Andy Pimentel, and Anuj Pathania

View

Download (PDF)

Source codes

Tags: ARM, Computer science, Heterogeneous systems, Machine learning, Neural networks, OpenCL, Package, SoC

July 24, 2022 by hgpu

Heterogeneous Energy-aware Load Balancing for Industry 4.0 and IoT Environments

Usman Ahmed, Jerry Chun-Wei Lin, Gautam Srivastava

View

Download (PDF)

Tags: Computer science, Heterogeneous systems, IoT, Machine learning, nVidia, nVidia GeForce GTX 760, nVidia GeForce GTX 860, OpenCL

July 17, 2022 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Apple Silicon Performance in Scientific Computing

Tausch: A halo exchange library for large heterogeneous computing systems using MPI, OpenCL, and CUDA

Towards Performance Portable Programming for Distributed Heterogeneous Systems

Decompiling x86 Deep Neural Network Executables

Exploiting dynamic sparse matrices for performance portable linear algebra operations

EnergonAI: An Inference System for 10-100 Billion Parameter Transformer Models

Towards Understanding and Mitigating Memory-Access Challenges in Computing Systems

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

Design and Implementation of ShenWei Universal C/C++

Demystifying Dependency Bugs in Deep Learning Stack

CPU-GPU Layer-Switched Low Latency CNN Inference

Heterogeneous Energy-aware Load Balancing for Industry 4.0 and IoT Environments

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Most viewed papers (last 30 days)