high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Assessment of various GPU acceleration strategies in text categorization processing flow

Lukasz Kordula, Maciej Wielgosz, Michal Karwatowski, Marcin Pietron, Dominik Zurek, Kazimierz Wiatr

View

Download (PDF)

Tags: AMD Radeon R9 280, ATI, Computer science, NLP, nVidia, nVidia Quadro NVS 4200 M, OpenCL

June 13, 2018 by hgpu

Aspect-Driven Mixed-Precision Tuning Targeting GPUs

Ricardo Nobre, Luis Reis, Joao Bispo, Tiago Carvalho, Joao M.P. Cardoso, Stefano Cherubin, Giovanni Agosta

View

Download (PDF)

Source codes

Tags: AMD Vega 10 XT, ATI, Code generation, Computer science, Mixed precision, nVidia, OpenCL, Package

June 13, 2018 by hgpu

Efficient Large-scale Approximate Nearest Neighbor Search on OpenCL FPGA

Jialiang Zhang, Soroosh Khoram, Jing Li

View

Download (PDF)

Tags: Computer science, FPGA, Nearest neighbour, nVidia, nVidia GeForce GTX Titan XP, OpenCL

June 13, 2018 by hgpu

GPU Virtualization and Scheduling Methods: A Comprehensive Survey

Cheol-Ho Hong, Ivor Spence, Dimitrios S. Nikolopoulos

View

Download (PDF)

Tags: Cloud, Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, OpenCL, Review, Virtualization

June 9, 2018 by hgpu

Fast Locality Sensitive Hashing for Beam Search on GPU

Xing Shi, Shizhen Xu, Kevin Knight

View

Download (PDF)

Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Data Structures and Algorithms, Hashing, NLP, nVidia, Tesla K20

June 9, 2018 by hgpu

clMF: A fine-grained and portable alternating least squares algorithm for parallel matrix factorization

Jing Chen, Jianbin Fanga, Weifeng Liub, Tao Tang, Canqun Yang

View

Download (PDF)

Source codes

Tags: AMD Radeon R9 Fury X, ATI, Computer science, Factorization, Linear Algebra, nVidia, OpenCL, Package, Tesla K20

June 2, 2018 by hgpu

NengoDL: Combining deep learning and neuromorphic modelling methods

Daniel Rasmussen

View

Download (PDF)

Source codes

Tags: Artificial intelligence, Benchmarking, Computer science, Deep learning, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Python

June 2, 2018 by hgpu

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

Li Luo, Yakun Wu, Fei Qiao, Yi Yang, Qi Wei, Xiaobo Zhou, Yongkai Fan, Shuzheng Xu, Xinjun Liu, Huazhong Yang

View

Download (PDF)

Tags: Algorithms, CNN, Computer science, Deep learning, FPGA, Heterogeneous systems, Neural networks, OpenCL

June 2, 2018 by hgpu

Marian: Cost-effective High-Quality Neural Machine Translation in C++

Marcin Junczys-Dowmunt, Kenneth Heafield, Hieu Hoang, Roman Grundkiewicz, Anthony Aue

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Machine learning, NLP, nVidia, Package

June 2, 2018 by hgpu

FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL

Haomiao Wang, Prabu Thiagaraj, Oliver Sinnen

View

Download (PDF)

Tags: AMD Radeon R7 370, Astrophysics, ATI, FPGA, OpenCL

June 2, 2018 by hgpu

OpenCL 2.2 API Specification

Khronos OpenCL Working Group

View

Download (PDF)

Tags: Computer science, OpenCL, Whitepaper

May 26, 2018 by hgpu

Transformations of High-Level Synthesis Codes for High-Performance Computing

Johannes de Fine Licht, Simon Meierhans, Torsten Hoefler

View

Download (PDF)

Tags: Computer science, FPGA, HLS, OpenCL

May 26, 2018 by hgpu

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: Benchmarking LLMs for Concurrent Code Generation

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Programming

Assessment of various GPU acceleration strategies in text categorization processing flow

Aspect-Driven Mixed-Precision Tuning Targeting GPUs

Efficient Large-scale Approximate Nearest Neighbor Search on OpenCL FPGA

Fast Locality Sensitive Hashing for Beam Search on GPU

clMF: A fine-grained and portable alternating least squares algorithm for parallel matrix factorization

NengoDL: Combining deep learning and neuromorphic modelling methods

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

Marian: Cost-effective High-Quality Neural Machine Translation in C++

FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL

OpenCL 2.2 API Specification

Transformations of High-Level Synthesis Codes for High-Performance Computing

Recent source codes

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

HIPRT: Ray Tracing using HIP

MXFP4 Training Support Codebase

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

Most viewed papers (last 30 days)