high performance computing on graphics processing units: hgpu.org

Miles D. Cranmer, Benjamin R. Barsdell, Danny C. Price, Jayce Dowell, Hugh Garsden, Veronica Dike, Tarraneh Eftekhari, Alexander M. Hegedus, Joseph Malins, Kenneth S. Obenberger, Frank Schinzel, Kevin Stovall, Gregory B. Taylor, Lincoln J. Greenhill

View

Download (PDF)

Source codes

Tags: Astrophysics, Computer science, CUDA, nVidia, Package, Python, Tesla K80

August 8, 2017 by hgpu

Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL?

Ammar Ahmad Awan, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, GPU cluster, MPI, nVidia, nVidia DGX-1, OpenMPI, Tesla V100

August 1, 2017 by hgpu

Deep Architectures for Neural Machine Translation

Antonio Valerio Miceli Barone, Jindrich Helcl, Rico Sennrich, Barry Haddow, Alexandra Birch

View

Download (PDF)

Source codes

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

August 1, 2017 by hgpu

A GPU Based Memory Optimized Parallel Method For FFT Implementation

Fan Zhang, Chen Hu, Qiang Yin, Wei Hu

View

Download (PDF)

Tags: CUDA, FFT, Image processing, nVidia, Sensing, Signal processing, Tesla C2070

August 1, 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

Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture

Gpufit: An open-source toolkit for GPU-accelerated curve fitting

GARDENIA: A Domain-specific Benchmark Suite for Next-generation Accelerators

Accelerating digital forensic searching through GPGPU parallel processing techniques

Using Graph Properties to Speed-up GPU-based Graph Traversal: A Model-driven Approach

GPU Array Access Auto-Tuning

Practically efficient methods for performing bit-reversed permutation in C++11 on the x86-64 architecture

Bifrost: a Python/C++ Framework for High-Throughput Stream Processing in Astronomy

Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL?

Deep Architectures for Neural Machine Translation

A GPU Based Memory Optimized Parallel Method For FFT Implementation

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)