high performance computing on graphics processing units: hgpu.org

hgpu.org » Computer science

Performant Automatic BLAS Offloading on Unified Memory Architecture with OpenMP First-Touch Style Data Movement

Junjie Li

View

Download (PDF)

Tags: Computer science, CUDA, HPC, Linear Algebra, nVidia, nVidia GH200, OpenMPI, Physics, Quantum Physics

January 6, 2025 by hgpu

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Avinash Maurya

View

Download (PDF)

Source codes

Tags: AI, Artificial intelligence, Computer science, CUDA, Deep learning, HPC, nVidia, nVidia DGX-A100, Package, Thesis

December 29, 2024 by hgpu

Asynchronous-Many-Task Systems: Challenges and Opportunities – Scaling an AMR Astrophysics Code on Exascale machines using Kokkos and HPX

Gregor Daiß, Patrick Diehl, Jiakun Yan, John K. Holmen, Rahulkumar Gayatri, Christoph Junghans, Alexander Straub, Jeff R. Hammond, Dominic Marcello, Miwako Tsuji, Dirk Pflüger, Hartmut Kaiser

View

Download (PDF)

Source codes

Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, Astrophysics, ATI, Computer science, CUDA, Heterogeneous systems, HIP, HPC, nVidia, nVidia A100, Package, performance portability, Physics

December 29, 2024 by hgpu

A survey on FPGA-based accelerator for ML models

Feng Yan, Andreas Koch, Oliver Sinnen

View

Download (PDF)

Tags: Computer science, FPGA, Hardware Architecture, Machine learning, survey

December 29, 2024 by hgpu

Development of a new framework for high performance volunteer computing

Ehab Saleh, B. S. Chandrasekar

View

Download (PDF)

Tags: Computer science, Distributed computing, Heterogeneous computing, HPC

December 29, 2024 by hgpu

Utilizing Tensor Cores in Futhark

Kristoffer August Kortbæk, Rune Ejnar Bang Lejbølle

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, High-level Languages, Matrix multiplication, nVidia, nVidia A100, Package, PTX

December 24, 2024 by hgpu

CPPJoules: An Energy Measurement Tool for C++

Shivadharshan S, Akilesh P, Rajrupa Chattaraj, Sridhar Chimalakonda

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Energy-efficient computing, nVidia, Package, Software Engineering

December 24, 2024 by hgpu

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization

Ka Wai Wu

View

Download (PDF)

Tags: Computer science, CUDA, Graph, Heterogeneous systems, Neural networks, nVidia, PyTorch, Tesla V100

December 24, 2024 by hgpu

HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages

Aman Chaturvedi, Daniel Nichols, Siddharth Singh, Abhinav Bhatele

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, HIP, HPC, LLM, MPI, nVidia, nVidia A100, OpenMP, Package

December 24, 2024 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

Ezhilmathi Krishnasamy, Pascal Bouvry

View

Download (PDF)

Source codes

Tags: BLAS, Computer science, CUDA, Differential equations, HPC, Linear Algebra, Matrix multiplication, nVidia, nVidia A100, OpenACC, Package, Partial differential equations, PDEs, Performance

December 24, 2024 by hgpu

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

Manuel Costanzo, Enzo Rucci, Carlos García-Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

View

Download (PDF)

Source codes

Tags: AMD Radeon RX 6700 XT, AMD Radeon RX Vega 6, ATI, Bioinformatics, Biology, Computer science, CUDA, Databases, Heterogeneous systems, HPC, Intel, Intel Arc A770, Intel UHD 630, Intel UHD 770, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3070, nVidia GeForce RTX 3090, oneAPI, Package, performance portability, SYCL, Tesla V100

December 15, 2024 by hgpu

Towards Performance-Aware Allocation for Accelerated Machine Learning on GPU-SSD Systems

Ayush Gundawar, Euijun Chung, Hyesoon Kim

View

Download (PDF)

Tags: Computer science, Hardware Architecture, Machine learning, Performance

December 15, 2024 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Performant Automatic BLAS Offloading on Unified Memory Architecture with OpenMP First-Touch Style Data Movement

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Asynchronous-Many-Task Systems: Challenges and Opportunities – Scaling an AMR Astrophysics Code on Exascale machines using Kokkos and HPX

A survey on FPGA-based accelerator for ML models

Development of a new framework for high performance volunteer computing

Utilizing Tensor Cores in Futhark

CPPJoules: An Energy Measurement Tool for C++

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization

HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

Towards Performance-Aware Allocation for Accelerated Machine Learning on GPU-SSD Systems

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Most viewed papers (last 30 days)