high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » paper

Deep In-GPU Experience Replay

Ben Parr

View

Download (PDF)

Tags: Artificial intelligence, Computer science, nVidia, nVidia GeForce GTX Titan X

January 13, 2018 by hgpu

GPU Acceleration of a High-Order Discontinuous Galerkin Incompressible Flow Solver

Ali Karakus, Noel Chalmers, Kasia Swirydowicz, Timothy Warburton

View

Download (PDF)

Tags: Computational Physics, CUDA, Fluid dynamics, Navier-Stokes equations, NSEs, Numerical Analysis, nVidia, Tesla P100

January 6, 2018 by hgpu

Rubus: A compiler for seamless and extensible parallelism

Muhammad Adnan, Faisal Aslam, Zubair Nawaz, Syed Mansoor Sarwar

View

Download (PDF)

Source codes

Tags: Aparapi, Benchmarking, Computer science, CUDA, Java, Matrix multiplication, nVidia, nVidia GeForce GT 630 M, OpenCL, OpenGL, Package

January 6, 2018 by hgpu

ThunderSVM: A Fast SVM Library on GPUs and CPUs

Zeyi Wen, Jiashuai Shi, Bingsheng He, Qinbin Li, Jian Chen

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Data mining, Machine learning, nVidia, OpenMP, Package, Tesla P100

January 6, 2018 by hgpu

Analysing the Performance of GPU Hash Tables for State Space Exploration

Nathan Cassee, Anton Wijs

View

Download (PDF)

Tags: Computer science, CUDA, Design space exploration, Hashing, nVidia, nVidia GeForce GT 750 M, Performance

January 6, 2018 by hgpu

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

Amrita Mathuriya, Thorsten Kurth, Vivek Rane, Mustafa Mustafa, Lei Shao, Debbie Bard, Prabhat, Victor W Lee

View

Download (PDF)

Tags: Benchmarking, Computer science, Deep learning, Intel Xeon Phi, Neural networks, Performance, TensorFlow

January 6, 2018 by hgpu

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Xinying Wang

View

Download (PDF)

Tags: Computer science, Data mining, Factorization, FPGA, Intel Xeon Phi, Matrix decomposition, Semantic indexing, Signal processing, Text mining, Thesis

December 28, 2017 by hgpu

Design and Implementation of the Futhark Programming Language

Troels Henriksen

View

Download (PDF)

Source codes

Tags: AMD FirePro W8100, ATI, Computer science, Haskell, High-level Languages, nVidia, OpenCL, Package, Tesla K40, Thesis

December 28, 2017 by hgpu

A Generic Inverted Index Framework for Similarity Search on the GPU

Jingbo Zhou, Qi Guo, H. V. Jagadish, Lubos Krcal, Siyuan Liu, Wenhao Luan, Anthony K. H. Tung, Yueji Yang, Yuxin Zheng

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Hashing, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan X, OpenMPI, Package

December 28, 2017 by hgpu

A Survey of FPGA Based Neural Network Accelerator

Kaiyuan Guo, Shulin Zeng, Jincheng Yu, Yu Wang, Huazhong Yang

View

Download (PDF)

Tags: Computer science, Computer vision, FPGA, Machine learning, Neural networks

December 28, 2017 by hgpu

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Waqar Ali, Heechul Yun

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia Jetson TK1, Operating systems, Performance, Security, SoC

December 28, 2017 by hgpu

Pass a Pointer: Exploring Shared Virtual Memory Abstractions in OpenCL Tools for FPGAs

Felix Winterstein, George Constantinides

View

Download (PDF)

Source codes

Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, Package

December 24, 2017 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Deep In-GPU Experience Replay

GPU Acceleration of a High-Order Discontinuous Galerkin Incompressible Flow Solver

Rubus: A compiler for seamless and extensible parallelism

ThunderSVM: A Fast SVM Library on GPUs and CPUs

Analysing the Performance of GPU Hash Tables for State Space Exploration

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Design and Implementation of the Futhark Programming Language

A Generic Inverted Index Framework for Similarity Search on the GPU

A Survey of FPGA Based Neural Network Accelerator

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Pass a Pointer: Exploring Shared Virtual Memory Abstractions in OpenCL Tools for FPGAs

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

Most viewed papers (last 30 days)