high performance computing on graphics processing units: hgpu.org

hgpu.org » CUDA

Acceleration of tensor-product operations for high-order finite element methods

Kasia Swirydowicz, Noel Chalmers, Ali Karakus, Timothy Warburton

View

Tags: Computer science, CUDA, FEM, Finite element method, Mathematical Software, Numerical Analysis, nVidia, Overview, Performance, Tesla P100

November 7, 2017 by hgpu

Dynamic Load Balancing Strategies for Graph Applications on GPUs

Ananya Raval, Rupesh Nasre, Vivek Kumar, Vasudevan R, Sathish Vadhiyar, Keshav Pingali

View

Download (PDF)

Tags: Computer science, CUDA, load balancing, nVidia, Tesla K20

November 5, 2017 by hgpu

A Dynamic Hash Table for the GPU

Saman Ashkiani, Martin Farach-Colton, John D. Owens

View

Download (PDF)

Tags: Computer science, CUDA, Graph theory, Hashing, nVidia, Tesla K40

November 5, 2017 by hgpu

ChainerMN: Scalable Distributed Deep Learning Framework

Takuya Akiba, Keisuke Fukuda, Shuji Suzuki

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X, Package, Python

November 5, 2017 by hgpu

Automatic Scan Parallelization in OpenMP

Maicol Zegarra, Marcio Pereira, Xavier Martorell, Guido Araujo

View

Download (PDF)

Tags: Algorithms, ARM, Computer science, CUDA, nVidia, OpenCL, OpenMP, Sorting, Tesla K40

October 31, 2017 by hgpu

An efficient GPU algorithm for tetrahedron-based Brillouin-zone integration

Daniel Guterding, Harald O. Jeschke

View

Download (PDF)

Tags: Algorithms, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 970, Physics

October 31, 2017 by hgpu

Performance optimizations for scalable CFD applications on hybrid CPU+MIC heterogeneous computing system with millions of cores

Yong-Xian Wang, Li-Lun Zhang, Wei Liu, Xing-Hua Cheng, Yu Zhuang, Anthony T. Chronopoulos

View

Download (PDF)

Tags: cfd, Computer science, CUDA, Fluid dynamics, Heterogeneous systems, MPI, nVidia, OpenMP, Performance, supercomputer, Tesla M2050, Xeon Phi

October 31, 2017 by hgpu

GooFit 2.0

Henry Schreiner, Christoph Hasse, Bradley Hittle, Himadri Pandey, Michael Sokoloff, Karen Tomko

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Mathematical Software, MPI, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, Package, Probability, Tesla K40, Tesla P100

October 29, 2017 by hgpu

Deep Voice 3: 2000-Speaker Neural Text-to-Speech

Wei Ping, Kainan Peng, Andrew Gibiansky, Sercan O. Arik, Ajay Kannan, Sharan Narang, Jonathan Raiman, John Miller

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, nVidia, Speech recognition, Tesla P100

October 24, 2017 by hgpu

A Fast and Generic GPU-Based Parallel Reduction Implementation

Walid Jradi, Hugo do Nascimento, Wellington Martins

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, OpenCL, Performance, Tesla C2075

October 24, 2017 by hgpu

GPU acceleration and performance of the particle-beam-dynamics code Elegant

J.R. King, I.V. Pogorelov, K.M. Amyx, M. Borland, R. Soliday

View

Download (PDF)

Tags: Computational Physics, CUDA, MPI, nVidia, Physics, Tesla K20

October 24, 2017 by hgpu

Revisiting the Case of ARM SoCs in High-Performance Computing Clusters

Tyler Fox

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, nVidia Tegra TX1, SoC, Thesis

October 21, 2017 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Acceleration of tensor-product operations for high-order finite element methods

Dynamic Load Balancing Strategies for Graph Applications on GPUs

A Dynamic Hash Table for the GPU

ChainerMN: Scalable Distributed Deep Learning Framework

Automatic Scan Parallelization in OpenMP

An efficient GPU algorithm for tetrahedron-based Brillouin-zone integration

Performance optimizations for scalable CFD applications on hybrid CPU+MIC heterogeneous computing system with millions of cores

GooFit 2.0

Deep Voice 3: 2000-Speaker Neural Text-to-Speech

A Fast and Generic GPU-Based Parallel Reduction Implementation

GPU acceleration and performance of the particle-beam-dynamics code Elegant

Revisiting the Case of ARM SoCs in High-Performance Computing Clusters

Recent source codes

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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

Most viewed papers (last 30 days)