high performance computing on graphics processing units: hgpu.org

hgpu.org » Machine learning

Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Gabin Schieffer, Ruimin Shi, Stefano Markidis, Andreas Herten, Jennifer Faj, Ivy Peng

View

Download (PDF)

Tags: AMD, AMD Radeon Instinct MI250X, ATI, Computer science, HIP, Machine learning, Memory, Performance

October 6, 2024 by hgpu

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Zheming Jin

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, CUDA, HIP, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, nVidia H100, oneAPI, Performance, performance portability, SYCL, Tesla A100, Tesla V100

August 14, 2024 by hgpu

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs

Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui

View

Download (PDF)

Tags: AI, Computer science, CUDA, LLM, Machine learning, NLP, nVidia, nVidia A800

July 28, 2024 by hgpu

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

Jacob O. Tørring, Carl Hvarfner, Luigi Nardi, Magnus Själander

View

Download (PDF)

Source codes

Tags: Benchmarking, Compilers, Computer science, Machine learning, nVidia, nVidia GeForce GTX Titan V, nVidia Titan RTX, OpenCL, Package

June 30, 2024 by hgpu

COOK Access Control on an embedded Volta GPU

Benjamin Lesage, Frédéric Boniol, Claire Pagetti

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia Jetson AGX Xavier

June 23, 2024 by hgpu

Fast and Practical Strassen’s Matrix Multiplication using FPGAs

Afzal Ahmad, Linfeng Du, Wei Zhang

View

Download (PDF)

Source codes

Tags: BLAS, Computer science, FPGA, GEMM, Linear Algebra, Machine learning, Matrix multiplication, OpenCL, Package

June 9, 2024 by hgpu

Machine learning enhanced code optimization for high-level synthesis (ML-ECOHS)

Robert P. Munafo

View

Download (PDF)

Source codes

Tags: Compilers, Computer science, FPGA, HLS, Machine learning, OpenCL, Package, Thesis

June 2, 2024 by hgpu

Addressing Challenges in Utilizing GPUs for Accelerating Privacy-Preserving Computation

Ardhi Wiratama Baskara Yudha

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, Security, Thesis

June 2, 2024 by hgpu

STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep Learning

Roberto L. Castro, Diego Andrade, Basilio B. Fraguela

View

Download (PDF)

Tags: Auto-Tuning, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia A100, Tesla T4

May 26, 2024 by hgpu

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach

Urvij Saroliya, Eishi Arima, Dai Liu, Martin Schulz

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia A100, PC cluster, Task scheduling

May 20, 2024 by hgpu

A Systematic Literature Survey of Sparse Matrix-Vector Multiplication

Jianhua Gao, Bingjie Liu, Weixing Ji, Hua Huang

View

Download (PDF)

Tags: Computer science, FPGA, Heterogeneous systems, Linear Algebra, Machine learning, Overview, Sparse matrix

April 14, 2024 by hgpu

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

SW#SYCL

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

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

COOK Access Control on an embedded Volta GPU

Fast and Practical Strassen’s Matrix Multiplication using FPGAs

Machine learning enhanced code optimization for high-level synthesis (ML-ECOHS)

Addressing Challenges in Utilizing GPUs for Accelerating Privacy-Preserving Computation

STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep Learning

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach

A Systematic Literature Survey of Sparse Matrix-Vector Multiplication

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

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

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

Most viewed papers (last 30 days)