high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia

Optimization of Heterogeneous Parallel Computing Systems using Machine Learning

Devi Abhiseshu Adurti, Mohit Battu

View

Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, Matrix multiplication, nVidia, nVidia GeForce GTX 1050 Ti, Thesis

July 4, 2021 by hgpu

Object Detection Based Handwriting Localization

Yuli Wu, Yucheng Hu, Suting Miao

View

Download (PDF)

Tags: Deep learning, Image processing, Neural networks, nVidia, nVidia GeForce RTX 2080 Ti

July 4, 2021 by hgpu

Improving Performance and Energy Efficiency of Heterogeneous Systems with rCUDA

Javier Prades Gasulla

View

Download (PDF)

Tags: Cloud, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Tesla K40, Tesla P100, Thesis, Virtualization

June 27, 2021 by hgpu

Sigmoid: An auto-tuned load balancing algorithm for heterogeneous systems

Borja Pérez, E. Stafford, J.L. Bosque, R. Beivide

View

Download (PDF)

Tags: Algorithms, Computer science, Heterogeneous systems, load balancing, nVidia, nVidia GeForce GTX Titan Black, OpenCL, Tesla K20

June 27, 2021 by hgpu

APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores

Boyuan Feng, Yuke Wang, Tong Geng, Ang Li, Yufei Ding

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce RTX 3090, Package, Precision, Python, Tesla A100

June 27, 2021 by hgpu

Lettuce: PyTorch-based Lattice Boltzmann Framework

Mario Christopher Bedrunka, Dominik Wilde, Martin Kliemank, Dirk Reith, Holger Foysi, Andreas Krämer

View

Download (PDF)

Source codes

Tags: Algorithms, Computational Physics, CUDA, Deep learning, Fluid dynamics, Lattice Boltzmann model, Machine learning, nVidia, nVidia GeForce RTX 2070, Package, Physics, Tesla V100

June 27, 2021 by hgpu

GPUAPI: Multi-level Chapel Runtime API for GPUs

Akihiro Hayashi, Sri Raj Paul, Vivek Sarkar

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, Heterogeneous systems, HIP, nVidia, OpenCL, Package, SYCL, Tesla V100

June 20, 2021 by hgpu

Study and evaluation of improved automatic GPU offloading method

Yoji Yamato

View

Download (PDF)

Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia Quadro P 4000, OpenACC, OpenCL

June 20, 2021 by hgpu

Benchmarking the Nvidia GPU Lineage: From Early K80 to Modern A100 with Asynchronous Memory Transfers

Martin Svedin, Steven W. D. Chien, Gibson Chikafa, Niclas Jansson, Artur Podobas

View

Download (PDF)

Tags: Benchmarking, Computer science, MPI, nVidia, nVidia GeForce GTX 1050 Ti, nVidia Quadro K 2200, Tesla A100, Tesla K80, Tesla P100, Tesla V100

June 20, 2021 by hgpu

StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs

Artur Podobas, Martin Svedin, Steven W. D. Chien, Ivy B. Peng, Naresh Balaji Ravichandran, Pawel Herman, Anders Lansner, Stefano Markidis

View

Download (PDF)

Source codes

Tags: Bayesian, Computer science, CUDA, Deep learning, FPGA, HPC, Machine learning, MPI, nVidia, OpenMPI, Package, Tesla A100, Tesla V100

June 20, 2021 by hgpu

Experience Report: Writing A Portable GPU Runtime with OpenMP 5.1

Shilei Tian, Jon Chesterfield, Johannes Doerfert, Barbara Chapman

View

Download (PDF)

Tags: Computer science, CUDA, HIP, LLVM, MPI, nVidia, OpenMP, Portability, Tesla V100

June 20, 2021 by hgpu

Data-Driven Analysis and Design of Vulkan Ray-Tracing Applications using Automatic Instrumentation

David Pankratz

View

Download (PDF)

Tags: Computer science, nVidia, nVidia GeForce GTX 1660 Ti, nVidia GeForce RTX 3080, Rasterization, Raytracing, Rendering, Thesis, Visualization, Vulkan

June 6, 2021 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

Optimization of Heterogeneous Parallel Computing Systems using Machine Learning

Object Detection Based Handwriting Localization

Sigmoid: An auto-tuned load balancing algorithm for heterogeneous systems

APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores

Lettuce: PyTorch-based Lattice Boltzmann Framework

GPUAPI: Multi-level Chapel Runtime API for GPUs

Study and evaluation of improved automatic GPU offloading method

Benchmarking the Nvidia GPU Lineage: From Early K80 to Modern A100 with Asynchronous Memory Transfers

StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs

Experience Report: Writing A Portable GPU Runtime with OpenMP 5.1

Data-Driven Analysis and Design of Vulkan Ray-Tracing Applications using Automatic Instrumentation

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)