high performance computing on graphics processing units: hgpu.org

Packages

hgpu.org » Applications » Computer science

TensorNetwork for Machine Learning

Stavros Efthymiou, Jack Hidary, Stefan Leichenauer

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, Machine learning, nVidia, Package, Tesla P100

June 20, 2019 by hgpu

SYCL Code Generation for Multigrid Methods

Stefan Groth, Christian Schmitt, Jürgen Teich, and Frank Hannig

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, Differential equations, OpenCL, Package, Partial differential equations, PDEs

June 16, 2019 by hgpu

Parallel scalable simulations of biological neural networks using TensorFlow: A beginner’s guide

Saptarshi Soham Mohanta, Collins Assisi

View

Download (PDF)

Source codes

Tags: Biology, Computer science, CUDA, Deep learning, Differential equations, Machine learning, Neural networks, nVidia, ODEs, Ordinary differential equations, Package, Partial differential equations, PDEs, Python, TensorFlow, Tutorial

June 12, 2019 by hgpu

Diagnosing Performance Bottlenecks in HPC Applications

Kenneth Czechowski

View

Download (PDF)

Source codes

Tags: Computer science, HPC, Package, Performance, Thesis

June 9, 2019 by hgpu

Dynamic Distribution Pruning for Efficient Network Architecture Search

Xiawu Zheng, Rongrong Ji, Lang Tang, Yan Wan, Baochang Zhang, Yongjian Wu, Yunsheng Wu, Ling Shao

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, Package, Tesla V100

June 5, 2019 by hgpu

Raising the Performance of the Tinker-HP Molecular Modeling Package on Intel’s HPC Architectures: a Living Review [Article v1.0]

Luc-Henri Jolly, Alejandro Duran, Louis Lagardere, Jay W. Ponder, Pengyu Ren, Jean-Philip Piquemal

View

Download (PDF)

Source codes

Tags: Chemical Physics, Computational Physics, Computer science, Intel Xeon Phi, Mathematical Software, Molecular dynamics, Molecular modeling, OpenMP, Package

June 5, 2019 by hgpu

A Development Platform for Embedded Domain-Specific Languages

Shigeru Chiba, YungYu Zhuang, Thanh-Chung Dao

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, DSL, High-level Languages, Java, nVidia, Package

June 2, 2019 by hgpu

Breadth-First Search using Dynamic Parallelism on the GPU

Dominik Todling

View

Download (PDF)

Source codes

Tags: Algorithms, Breadth-First Search, Computer science, CUDA, nVidia, Package

May 30, 2019 by hgpu

Multi-GPU Rendering with Vulkan API

Lars Olav Tolo

View

Download (PDF)

Source codes

Tags: AMD Radeon RX 460, ATI, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 970, Package, Thesis, Vulkan

May 26, 2019 by hgpu

Comparing Energy Efficiency of CPU, GPU and FPGA Implementations for Vision Kernels

Murad Qasaimeh, Kristof Denolf, Jack Lo, Kees Vissers, Joseph Zambreno, Phillip H. Jones

View

Download (PDF)

Source codes

Tags: ARM, Benchmarking, Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia Jetson TX2, OpenCV, Package

May 26, 2019 by hgpu

Neural Query Language: A Knowledge Base Query Language for Tensorflow

William W. Cohen, Matthew Siegler, Alex Hofer

View

Download (PDF)

Source codes

Tags: Computer science, Databases, Deep learning, Package, Performance

May 19, 2019 by hgpu

An optimizing multi-platform source-to-source compiler framework for the NEURON MODeling Language

Pramod Kumbhar, Omar Awile, Liam Keegan, Jorge Blanco Alonso, James King, Michael Hines, Felix Schuermann

View

Download (PDF)

Source codes

Tags: Biophysics, Code generation, Compilers, Computer science, CUDA, HPC, Intel Xeon Phi, LLVM, nVidia, OpenACC, OpenMP, Package

May 15, 2019 by hgpu

Allo: Accelerator Design Language

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Packages

TensorNetwork for Machine Learning

SYCL Code Generation for Multigrid Methods

Parallel scalable simulations of biological neural networks using TensorFlow: A beginner’s guide

Diagnosing Performance Bottlenecks in HPC Applications

Dynamic Distribution Pruning for Efficient Network Architecture Search

Raising the Performance of the Tinker-HP Molecular Modeling Package on Intel’s HPC Architectures: a Living Review [Article v1.0]

A Development Platform for Embedded Domain-Specific Languages

Breadth-First Search using Dynamic Parallelism on the GPU

Multi-GPU Rendering with Vulkan API

Comparing Energy Efficiency of CPU, GPU and FPGA Implementations for Vision Kernels

Neural Query Language: A Knowledge Base Query Language for Tensorflow

An optimizing multi-platform source-to-source compiler framework for the NEURON MODeling Language

Recent source codes

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

HDM: Home made Diffusion Models

General Matrix Multiplication (GEMM)

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Most viewed papers (last 30 days)