high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia

Kernel Tuning Toolkit

Filip Petrovič, Jiří Filipovič

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 680, nVidia GeForce GTX 750, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Performance, Python, Vulkan

April 16, 2023 by hgpu

ParaGraph: Weighted Graph Representation for Performance Optimization of HPC Kernels

Ali TehraniJamsaz, Alok Mishra, Akash Dutta, Abid M. Malik, Barbara Chapman, Ali Jannesari

View

Download (PDF)

Tags: AMD Radeon Instinct Mi50, ATI, Computer science, HPC, Machine learning, Neural networks, nVidia, nVidia V100, OpenMP, Performance

April 16, 2023 by hgpu

Portability and Scalability of OpenMP Offloading on State-of-the-art Accelerators

Yehonatan Fridman, Guy Tamir, Gal Oren

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, Intel, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, oneAPI, OpenMP, Package, performance portability

April 16, 2023 by hgpu

Energy-Efficient GPU Clusters Scheduling for Deep Learning

Diandian Gu, Xintong Xie, Gang Huang, Xin Jin, Xuanzhe Liu

View

Download (PDF)

Tags: Computer science, Deep learning, Energy-efficient computing, GPU cluster, Neural networks, nVidia, Tesla V100

April 16, 2023 by hgpu

ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

Xingfu Wu, Prasanna Balaprakash, Michael Kruse, Jaehoon Koo, Brice Videau, Paul Hovland, Valerie Taylor, Brad Geltz, Siddhartha Jana, Mary Hall

View

Download (PDF)

Source codes

Tags: Bayesian, Computer science, Energy-efficient computing, MPI, nVidia, OpenMP, Package, Tesla V100

April 2, 2023 by hgpu

Managing heterogeneous device memory using C++17 memory resources

S.N. Swatman, A. Krasznahorkay, P. Gessinger

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, HIP, Memory model, nVidia, Package, SYCL

April 2, 2023 by hgpu

Pgx: Hardware-accelerated parallel game simulation for reinforcement learning

Sotetsu Koyamada, Shinri Okano, Soichiro Nishimori, Yu Murata, Keigo Habara, Haruka Kita, Shin Ishii

View

Download (PDF)

Source codes

Tags: Artificial intelligence, Computer science, Deep learning, nVidia, nVidia A100, Package

April 2, 2023 by hgpu

PopSparse: Accelerated block sparse matrix multiplication on IPU

Zhiyi Li, Douglas Orr, Valeriu Ohan, Godfrey Da costa, Tom Murray, Adam Sanders, Deniz Beker, Dominic Masters

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Linear Algebra, Machine learning, Matrix multiplication, nVidia, nVidia A100, Package, Sparse matrix

April 2, 2023 by hgpu

Comparing SYCL data transfer strategies for tracking use cases

S.Joube, H. Grasland, D. Chamont, E.Brunet

View

Download (PDF)

Tags: Benchmarking, Computer science, Memory model, nVidia, nVidia Quadro RTX 5000, SYCL

March 26, 2023 by hgpu

Kernel Launcher: C++ Library for Optimal-Performance Portable CUDA Applications

Stijn Heldens, Ben van Werkhoven

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Fluid dynamics, nVidia, nVidia A100, Package, Performance, performance portability

March 26, 2023 by hgpu

DSDP: A Blind Docking Strategy Accelerated by GPUs

YuPeng Huang, Hong Zhang, Siyuan Jiang, Dajiong Yue, Xiaohan Lin, Jun Zhang, Yi Qin Gao

View

Download (PDF)

Tags: Chemical Physics, CUDA, Machine learning, nVidia, nVidia GeForce RTX 2080, Physics

March 26, 2023 by hgpu

Challenges and Opportunities in C/C++ Source-To-Source Compilation

João Bispo, Nuno Paulino, Luís Miguel Sousa

View

Download (PDF)

Source codes

Tags: Compilers, Computer science, CUDA, nVidia, OpenCL, Package

March 19, 2023 by hgpu

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

* * *

high performance computing on graphics processing units: hgpu.org

Kernel Tuning Toolkit

ParaGraph: Weighted Graph Representation for Performance Optimization of HPC Kernels

Portability and Scalability of OpenMP Offloading on State-of-the-art Accelerators

Energy-Efficient GPU Clusters Scheduling for Deep Learning

ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

Managing heterogeneous device memory using C++17 memory resources

Pgx: Hardware-accelerated parallel game simulation for reinforcement learning

PopSparse: Accelerated block sparse matrix multiplication on IPU

Comparing SYCL data transfer strategies for tracking use cases

Kernel Launcher: C++ Library for Optimal-Performance Portable CUDA Applications

DSDP: A Blind Docking Strategy Accelerated by GPUs

Challenges and Opportunities in C/C++ Source-To-Source Compilation

Recent source codes

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

LC Framework

pplx-garden: Perplexity open source garden for inference technology

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

OpScanner

INT v.s. FP: A framework to compare low-bit integer and float-point formats

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Most viewed papers (last 30 days)