high performance computing on graphics processing units: hgpu.org

hgpu.org » Applications

Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores

Kai Zhang, Kaibo Wang, Yuan Yuan, Lei Guo, Rubao Lee, Xiaodong Zhang

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Data parallelism, Databases, nVidia, nVidia GeForce GTX 780, Package

July 6, 2015 by hgpu

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Amir Gholami, Judith Hill, Dhairya Malhotra, George Biros

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, FFT, MPI, nVidia, OpemMP, Package, Tesla K20

June 30, 2015 by hgpu

Optimization and Parallelization Methods for the Design of Next-Generation Radio Networks

Lucas Benedicic

View

Download (PDF)

Source codes

Tags: Algorithms, Cellular automata, Metaheuristics, nVidia, nVidia GeForce GTX 660 Ti, OpenCL, Package, Signal processing, Thesis

June 22, 2015 by hgpu

RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles

Nicholas P. Bailey, Trond S. Ingebrigtsen, Jesper Schmidt Hansen, Arno A. Veldhorst, Lasse Bohling, Claire A. Lemarchand, Andreas E. Olsen, Andreas K. Bacher, Heine Larsen, Jeppe C. Dyre, Thomas B. Schroder

View

Download (PDF)

Source codes

Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 780 Ti, Package, Physics, Python

June 17, 2015 by hgpu

Type-safe Runtime Code Generation: Accelerate to LLVM

Trevor L. McDonell, Manuel M. T. Chakravarty, Vinod Grover, Ryan R. Newton

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, nVidia, Package, Sparse matrix, Tesla K40

June 14, 2015 by hgpu

Accelerating parameter synthesis for stochastic models

Petr Pilar

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Probability, Sparse matrix, Thesis

June 14, 2015 by hgpu

Poisson-Boltzmann model for protein-surface electrostatic interactions and grid-convergence study using the PyGBe code

Christopher D. Cooper, Lorena A. Barba

View

Download (PDF)

Source codes

Tags: Biomolecules, Boltzmann equation, Computational Physics, CUDA, Electrostatics, nVidia, Package, Physics, Poisson Boltzmann, Python, Tesla C2075

June 14, 2015 by hgpu

Practical Symbolic Execution Analysis and Methodology for GPU Programs

Peng Li

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Thesis

June 10, 2015 by hgpu

Improving OpenCL Programmability with the Heterogeneous Programming Library

Moises Vinas, Basilio B. Fraguela, Zeki Bozkus, Diego Andrade

View

Download (PDF)

Source codes

Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Tesla C2050

June 8, 2015 by hgpu

Bi-directional Path Tracing on GPU

Vilem Otte

View

Download (PDF)

Source codes

Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 720 M, nVidia GeForce GTX 580, Package, Raytracing, Rendering, Thesis

June 8, 2015 by hgpu

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun

View

Download (PDF)

Source codes

Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, Package, Tesla K40

June 7, 2015 by hgpu

Blocks and Fuel: Frameworks for deep learning

Bart van Merrienboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, Yoshua Bengio

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Linear Algebra, Machine learning, MPI, Neural networks, nVidia, Package, Python, Symbolic Computation, Visualization

June 5, 2015 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

Packages

Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Optimization and Parallelization Methods for the Design of Next-Generation Radio Networks

RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles

Type-safe Runtime Code Generation: Accelerate to LLVM

Accelerating parameter synthesis for stochastic models

Poisson-Boltzmann model for protein-surface electrostatic interactions and grid-convergence study using the PyGBe code

Practical Symbolic Execution Analysis and Methodology for GPU Programs

Improving OpenCL Programmability with the Heterogeneous Programming Library

Bi-directional Path Tracing on GPU

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Blocks and Fuel: Frameworks for deep learning

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)