high performance computing on graphics processing units: hgpu.org

Jin-Hua Tao, Zi-Dong Du, Qi Guo, Hui-Ying Lan, Lei Zhang, Sheng-Yuan Zhou, Cong Liu, Hai-Feng Liu, Shan Tang, Allen Rush, Willian Chen, Shao-Li Liu, Yun-Ji Chen, Tian-Shi Chen

View

Download (PDF)

Tags: ASIC, Benchmarking, Computer science, Deep learning, nVidia, nVidia GeForce GTX 950, nVidia Tegra TX1, Tesla K40

October 24, 2017 by hgpu

Parallel Computing for the Inverse of SPD matrix

Yan Shen, Yuxing Dai, Zhiliang Zhu

Source codes

Tags: AMD Radeon R9 290, ATI, Computer science, Factorization, Linear Algebra, OpenCL, Package

October 24, 2017 by hgpu

A Fast and Generic GPU-Based Parallel Reduction Implementation

Walid Jradi, Hugo do Nascimento, Wellington Martins

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, OpenCL, Performance, Tesla C2075

October 24, 2017 by hgpu

GPU acceleration and performance of the particle-beam-dynamics code Elegant

J.R. King, I.V. Pogorelov, K.M. Amyx, M. Borland, R. Soliday

View

Download (PDF)

Tags: Computational Physics, CUDA, MPI, nVidia, Physics, Tesla K20

October 24, 2017 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

An efficient GPU algorithm for tetrahedron-based Brillouin-zone integration

Performance optimizations for scalable CFD applications on hybrid CPU+MIC heterogeneous computing system with millions of cores

A Study of Time and Energy Efficient Algorithms for Parallel and Heterogeneous Computing

Early Results of Deep Learning on the Stampede2 Supercomputer

GooFit 2.0

Strategy Preserving Compilation for Parallel Functional Code

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

Deep Voice 3: 2000-Speaker Neural Text-to-Speech

BENCHIP: Benchmarking Intelligence Processors

Parallel Computing for the Inverse of SPD matrix

A Fast and Generic GPU-Based Parallel Reduction Implementation

GPU acceleration and performance of the particle-beam-dynamics code Elegant

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Most viewed papers (last 30 days)