high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Scalable Lattice Boltzmann Solvers for CUDA GPU Clusters

Christian Obrecht, Frederic Kuznik, Bernard Tourancheau, Jean-Jacques Roux

View

Download (PDF)

Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, nVidia, OpenMPI, Tesla M2070

June 15, 2014 by hgpu

Image Denoising Using Wavelet Transform and CUDA

Hovhannes M. Bantikyan

View

Download (PDF)

Tags: Algorithms, Compression, CUDA, Discrete Wavelet Transform, Image processing, nVidia, nVidia GeForce GT 630

June 14, 2014 by hgpu

Dynamic loop vectorization for executing OpenCL kernels on CPUs

Izzat El Hajj

View

Download (PDF)

Tags: Computer science, Heterogeneous systems, OpenCL, Performance, Thesis

June 14, 2014 by hgpu

A GPU Implementation of Large Neighborhood Search for Solving Constraint Optimization Problems

F. Campeotto, A. Dovier, F. Fioretto, E. Pontelli

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Optimization, Search

June 14, 2014 by hgpu

Parallel technologies for solving system of the linear equations by the conjugate gradient method

Eduard Bondarenko

View

Download (PDF)

Tags: Computer science, Conjugate gradient solver, CUBLAS, nVidia, OpenACC, OpenMP, Tesla M2070

June 14, 2014 by hgpu

Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment

Azzam Haidar, Chongxiao Cao, Asim YarKhan, Piotr Luszczek, Stanimire Tomov, Khairul Kabir, Jack Dongarra

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, Linear Algebra, nVidia, Tesla K20, Tesla M2090

June 14, 2014 by hgpu

Realizing Accelerated Cost-Effective Distributed RAID

Aleksandr Khasymski, M. Mustafa Rafique, Ali R. Butt, Sudharshan S. Vazhkudai, Dimitrios S. Nikolopoulos

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Storage system, Tesla C2070, Tesla X2090

June 13, 2014 by hgpu

LTE Physical Layer Implementation Using GPU Based High Performance Computing

Sangeeta Bhattacharjee, Satyendra Singh Yadav, Sarat Kumar Patra

View

Download (PDF)

Tags: CUDA, FFT, nVidia, Signal processing, Tesla M2090

June 13, 2014 by hgpu

GPU-accelerated Computation for Statistical Analysis of the Next-Generation Sequencing Data

Yilan Liu

View

Download (PDF)

Tags: Bioinformatics, Biology, Computer science, CUDA, Next-Generation sequencing, nVidia, nVidia GeForce GTX 770

June 13, 2014 by hgpu

Secure Distributed Computing on a Manycore Cloud

Flavio Lombardi

View

Download (PDF)

Tags: Cloud, Computer science, CUDA, Data acquisition, Distributed computing, Heterogeneous systems, nVidia, nVidia GeForce GT 640, Security, Tesla C2050, Thesis

June 13, 2014 by hgpu

GPPE: a GPU-based Parallel Processing Environment for Large Scale Concurrent Data Streams

Jianwei Cao, Qingkui Chen, Songlin Zhuang

View

Download (PDF)

Tags: Cloud, Clustering, Computer science, CUDA, GPU cluster, H.264/AVC, MPI, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480

June 12, 2014 by hgpu

Multi-threaded Kernel Offloading to GPGPU Using Hyper-Q on Kepler Architecture

Florian Wende, Thomas Steinke, Frank Cordes

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Tesla M2090

June 12, 2014 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Scalable Lattice Boltzmann Solvers for CUDA GPU Clusters

Image Denoising Using Wavelet Transform and CUDA

Dynamic loop vectorization for executing OpenCL kernels on CPUs

A GPU Implementation of Large Neighborhood Search for Solving Constraint Optimization Problems

Parallel technologies for solving system of the linear equations by the conjugate gradient method

Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment

Realizing Accelerated Cost-Effective Distributed RAID

LTE Physical Layer Implementation Using GPU Based High Performance Computing

GPU-accelerated Computation for Statistical Analysis of the Next-Generation Sequencing Data

Multi-threaded Kernel Offloading to GPGPU Using Hyper-Q on Kepler Architecture

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

Most viewed papers (last 30 days)