high performance computing on graphics processing units: hgpu.org

hgpu.org » Applications » Computer science

Deep Graph Library Optimizations for Intel(R) x86 Architecture

Sasikanth Avancha, Vasimuddin Md, Sanchit Misra, Ramanarayan Mohanty

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Package

July 19, 2020 by hgpu

Automated Partitioning of Data-Parallel Kernels using Polyhedral Compilation

Alexander Matz, Johannes Doerfert, Holger Fröning

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, LLVM, nVidia, Package, Tesla K80

July 12, 2020 by hgpu

GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks

Guyue Huang, Guohao Dai, Yu Wang, Huazhong Yang

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce RTX 2080, Package, Sparse matrix

July 12, 2020 by hgpu

SYCL-Bench: A Versatile Cross-Platform Benchmark Suite for Heterogeneous Computing

Sohan Lal, Aksel Alpay, Philip Salzmann, Biagio Cosenza, Alexander Hirsch, Nicolai Stawinoga, Peter Thoman, Thomas Fahringer, Vincent Heuveline

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, PTX, SYCL

July 5, 2020 by hgpu

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

Hartwig Anzt, Terry Cojean, Goran Flegar, Fritz Göbel, Thomas Grützmacher, Pratik Nayak, Tobias Ribizel, Yuhsiang Mike Tsai, Enrique S. Quintana-Ortí

View

Download (PDF)

Source codes

Tags: Algorithms, AMD Radeon VII, ATI, Computer science, CUDA, HIP, Linear Algebra, Mathematical Software, nVidia, Package, Sparse, Sparse matrix, Tesla V100

July 5, 2020 by hgpu

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP

Yuhsiang M. Tsai, Terry Cojean, Tobias Ribizel, Hartwig Anzt

View

Download (PDF)

Source codes

Tags: AMD Radeon VII, ATI, Computer science, CUDA, Linear Algebra, Mathematical Software, nVidia, Package

June 28, 2020 by hgpu

The Rodinia Benchmark Suite in SYCL

Zheming Jin

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, Heterogeneous systems, OpenCL, Package, SYCL

June 14, 2020 by hgpu

Neural Architecture Search without Training

Joseph Mellor, Jack Turner, Amos Storkey, Elliot J. Crowley

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Package

June 14, 2020 by hgpu

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

Jiajian Xiao, Philipp Andelfinger, Wentong Cai, Paul Richmond, Alois Knoll, David Eckhoff

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 2080 Ti, OpenCL, Package

June 7, 2020 by hgpu

SOFF: An OpenCL High-Level Synthesis Framework for FPGAs

Gangwon Jo, Heehoon Kim, Jeesoo Lee, Jaejin Lee

View

Download (PDF)

Source codes

Tags: Compilers, Computer science, FPGA, OpenCL, Package, Performance

June 7, 2020 by hgpu

Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format

Shaohuai Shi, Qiang Wang, Xiaowen Chu

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, Package, Sparse matrix, Tesla P100

June 7, 2020 by hgpu

Evaluating the performance of HPC-style SYCL applications

Tom Deakin, Simon McIntosh-Smith

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, Heterogeneous systems, OpenCL, OpenMP, Package, Performance, SYCL

May 31, 2020 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

Packages

Deep Graph Library Optimizations for Intel(R) x86 Architecture

Automated Partitioning of Data-Parallel Kernels using Polyhedral Compilation

GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks

SYCL-Bench: A Versatile Cross-Platform Benchmark Suite for Heterogeneous Computing

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP

The Rodinia Benchmark Suite in SYCL

Neural Architecture Search without Training

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

SOFF: An OpenCL High-Level Synthesis Framework for FPGAs

Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format

Evaluating the performance of HPC-style SYCL applications

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)