high performance computing on graphics processing units: hgpu.org

hgpu.org » Package

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

Matteo Croci, Garth N. Wells

View

Tags: AVX, Computer science, Finite element method, Floating point error, Intel, Matrix multiplication, Mixed precision, Package

October 27, 2024 by hgpu

General-Purpose Computing on Tensor Processors

Kuan-Chieh Hsu

View

Tags: Artificial intelligence, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, nVidia Jetson Nano, Package, Sparse matrix, Thesis, TPU

October 27, 2024 by hgpu

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

Xiongxiao Xu, Solomon Abera Bekele, Brice Videau, Kai Shu

View

Tags: Computer science, Energy-efficient computing, HPC, Intel, Intel Data Center GPU Max 1550, Package

October 20, 2024 by hgpu

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Reza Abbasi, Sernam Lim

View

Tags: AI, Artificial intelligence, Computer science, CUDA, LLM, Machine learning, Memory, nVidia, nVidia GeForce RTX 3090, nVidia Quadro RTX 8000, Package

October 20, 2024 by hgpu

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Dennis Liew, Tiago Cogumbreiro, Julien Lange

View

Tags: Artificial intelligence, Computer science, CUDA, nVidia, Package, Performance

October 13, 2024 by hgpu

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Dániel Koics, Endre Kovács 2, Olivér Hornyák

View

Tags: nVidia, OpenCL, Package, PDEs, Performance, Physics

October 13, 2024 by hgpu

Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

Alex Brooks, Philip Marshall, David Ozog, Md. Wasi-ur- Rahman, Lawrence Stewart, Rithwik Tom

View

Tags: Artificial intelligence, Computer science, Heterogeneous systems, Intel, Intel Data Center GPU Max 1550, oneAPI, Package, SYCL

October 6, 2024 by hgpu

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

E.M. Garzón, J.A. Martínez, J.J. Moreno, M.L. Puertas

View

Tags: Algorithms, Computer science, CUDA, Graph theory, HPC, nVidia, OpenMP, Package, Tesla V100

September 29, 2024 by hgpu

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

Luigi Crisci, Biagio Cosenza, Giorgio Amati, Matteo Turisini

View

Tags: AMD Radeon Instinct MI100, ATI, cfd, Fluid dynamics, nVidia, Package, SYCL, Tesla V100

September 29, 2024 by hgpu

Bitstream Database-Driven FPGA Programming Flow Based on Standard OpenCL

Topi Leppänen, Leevi Leppänen, Joonas Multanen, Pekka Jääskeläinen

View

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

September 29, 2024 by hgpu

OpenACC offloading of the MFC compressible multiphase flow solver on AMD and NVIDIA GPUs

Benjamin Wilfong, Anand Radhakrishnan, Henry A. Le Berre, Steve Abbott, Reuben D. Budiardja, Spencer H. Bryngelson

View

Tags: AMD Radeon Instinct MI250X, ATI, cfd, Fluid dynamics, MPI, nVidia, OpenACC, Package, Tesla V100

September 29, 2024 by hgpu

Refining HPCToolkit for application performance analysis at exascale

Laksono Adhianto, Jonathon Anderson, Robert Matthew Barnett, Dragana Grbic, Vladimir Indic, Mark Krentel, Yumeng Liu, Srdan Milakovíc, Wileam Phan, John Mellor-Crumme

View

Tags: AMD Radeon Instinct MI300A, ATI, Computer science, CUDA, HPC, MPI, OpenCL, Package, Performance

September 15, 2024 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

Inside VOLT: Designing an Open-Source GPU Compiler (Tool)

SciDef: Automated Definition Extraction from Scientific Literature

SciDef: Automating Definition Extraction from Academic Literature with Large Language Models

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

See all packages

* * *

* * *

HGPU group © 2010-2026 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: