high performance computing on graphics processing units: hgpu.org

hgpu.org » Package

SCALSALE: Scalable SALE Benchmark Framework for Supercomputers

Re'em Harel, Matan Rusanovsky, Ron Wagner, Harel Levin, Gal Oren

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, Fortran, HPC, MPI, Package, Performance

September 11, 2022 by hgpu

Lina: a fast design optimisation tool for software-based FPGA programming

Andre Bannwart Perina

View

Download (PDF)

Source codes

Tags: Computer science, Design space exploration, FPGA, nVidia, nVidia Quadro K620, OpenCL, Package, Thesis

September 4, 2022 by hgpu

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Jhe-Yu Liou, Muaaz Awan, Steven Hofmeyr, Stephanie Forrest, Carole-Jean Wu

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, Computer science, CUDA, Evolutionary Computations, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 1080 Ti, Package, performance portability, Sequence alignment, Tesla P100, Tesla V100

September 4, 2022 by hgpu

Towards Understanding and Mitigating Memory-Access Challenges in Computing Systems

Mohammad K. Dashti

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Memory model, nVidia, nVidia GeForce RTX 2070, nVidia Jetson TK1, OpenCL, Package, Thesis

August 28, 2022 by hgpu

Fully Concurrent GPU Data Structures

Muhammad Abdelghaffar Awad

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX Titan V, Package, Tesla V100

August 28, 2022 by hgpu

BenchPress: A Deep Active Benchmark Generator

Foivos Tsimpourlas, Pavlos Petoumenos, Min Xu, Chris Cummins, Kim Hazelwood, Ajitha Rajan, Hugh Leather

View

Download (PDF)

Source codes

Tags: Benchmarking, Code generation, Computer science, Deep learning, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, PyTorch

August 21, 2022 by hgpu

Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training

Jie You, Jae-Won Chung, Mosharaf Chowdhury

View

Download (PDF)

Source codes

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

August 21, 2022 by hgpu

Performance analysis of matrix-free conjugate gradient kernels using SYCL

Igor Baratta, Chris Richardson, Garth Wells

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, Latency, nVidia, nVidia A100, OpenCL, Package, Performance, SYCL

August 21, 2022 by hgpu

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Tim Dettmers, Mike Lewis, Younes Belkada, Luke Zettlemoyer

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, nVidia, nVidia A40, Package, PyTorch

August 21, 2022 by hgpu

A Container-Based Workflow for Distributed Training of Deep Learning Algorithms in HPC Clusters

Jose González-Abad, Álvaro López García, Valentin Y. Kozlov

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, HPC, nVidia, nVidia GeForce GTX 980 Ti, Package, Tesla V100

August 7, 2022 by hgpu

CPU-GPU Layer-Switched Low Latency CNN Inference

Ehsan Aghapour, Dolly Sapra, Andy Pimentel, and Anuj Pathania

View

Download (PDF)

Source codes

Tags: ARM, Computer science, Heterogeneous systems, Machine learning, Neural networks, OpenCL, Package, SoC

July 24, 2022 by hgpu

FPGA Accelerators on Heterogeneous Systems: An Approach Using High Level Synthesis

María Ángelica Dávila Gúzman

View

Download (PDF)

Source codes

Tags: Computer science, FPGA, HLS, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Thesis

July 24, 2022 by hgpu

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

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

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

SCALSALE: Scalable SALE Benchmark Framework for Supercomputers

Lina: a fast design optimisation tool for software-based FPGA programming

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Towards Understanding and Mitigating Memory-Access Challenges in Computing Systems

Fully Concurrent GPU Data Structures

BenchPress: A Deep Active Benchmark Generator

Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training

Performance analysis of matrix-free conjugate gradient kernels using SYCL

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

A Container-Based Workflow for Distributed Training of Deep Learning Algorithms in HPC Clusters

CPU-GPU Layer-Switched Low Latency CNN Inference

FPGA Accelerators on Heterogeneous Systems: An Approach Using High Level Synthesis

Recent source codes

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

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

pplx-garden: Perplexity open source garden for inference technology

LC Framework

Most viewed papers (last 30 days)