high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

High-performance CUDA kernel execution on FPGAs

Alexandros Papakonstantinou, Karthik Gururaj, John A. Stratton, Deming Chen, Jason Cong, Wen Mei

View

Download (PDF)

Tags: Computer science, CUDA, FPGA, Performance, Programming techniques

January 11, 2011 by hgpu

Comparing Hardware Accelerators in Scientific Applications: A Case Study

Rick Weber, Akila Gothandaraman, Robert J. Hinde, Gregory D. Peterson

Tags: ATI, Brook, Computer science, CUDA, FPGA, nVidia, OpenCL, Performance

January 10, 2011 by hgpu

Self-Configuring Applications for Heterogeneous Systems: Program Composition and Optimization Using Cognitive Techniques

M. W. Hall, Y. Gil, R. F. Lucas

View

Download (PDF)

Tags: Compilers, Computer science, FPGA, nVidia, Optimization, Performance

January 8, 2011 by hgpu

FPGA-based acceleration of CHARMM-potential minimization

Bharat Sukhwani, Martin C. Herbordt

View

Download (PDF)

Tags: Chemistry, FPGA, Molecular modeling, nVidia, Performance, Tesla C1060

January 3, 2011 by hgpu

Using Reconfigurable Logic to Optimise GPU Memory Accesses

Ben Cope, Peter Y. K. Cheung, Wayne Luk

View

Download (PDF)

Tags: Computer science, Memory model, nVidia, nVidia GeForce 7900 GTX, Performance

December 27, 2010 by hgpu

Performance analysis of memory transfers and GEMM subroutines on NVIDIA Tesla GPU cluster

Veerendra Allada, Troy Benjegerdes, Brett Bode

View

Download (PDF)

Tags: Computer science, CUDA, GPU cluster, nVidia, Performance, Presentation, Tesla S1070, Tesla T10

December 27, 2010 by hgpu

Performance comparison of single-precision SPICE Model-Evaluation on FPGA, GPU, Cell, and multi-core processors

Nachiket Kapre, Andre DeHon

View

Download (PDF)

Tags: Cell processor, Computer science, CUDA, FPGA, nVidia, nVidia GeForce 9600 GT, Performance

December 26, 2010 by hgpu

Fine-grain Parallelism Using Multi-core, Cell/BE, and GPU Systems: Accelerating the Phylogenetic Likelihood Function

Frederico Pratas, Pedro Trancoso, Alexandros Stama

View

Download (PDF)

Tags: Cell processor, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, Performance, Programming techniques

December 24, 2010 by hgpu

Pushing the Envelope: Extreme Network Coding on the GPU

Hassan Shojania, Baochun Li

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques

December 22, 2010 by hgpu

Demystifying GPU microarchitecture through microbenchmarking

Henry Wong, Misel-Myrto Papadopoulou, Maryam Sadooghi-Alvandi, Andreas Moshovos

View

Download (PDF)

Tags: Architecture, Computer science, nVidia, nVidia GeForce GTX 280, Performance

December 21, 2010 by hgpu

Shader Performance Analysis on a Modern GPU Architecture

Victor Moya, Carlos Gonzalez, Jordi Roca, Agustin Fernandez, Roger Espasa

View

Download (PDF)

Tags: 3D Graphics and Realism, ATI, Computer science, OpenGL, Performance, Rendering

December 18, 2010 by hgpu

Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures

Kaushik Datta, Mark Murphy, Vasily Volkov, Samuel Williams, Jonathan Carter, Leonid Oliker, David Patterson, John Shalf, Katherine Yelick

View

Download (PDF)

Tags: Cell processor, Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 280, Performance

December 14, 2010 by hgpu

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

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

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

High-performance CUDA kernel execution on FPGAs

Comparing Hardware Accelerators in Scientific Applications: A Case Study

Self-Configuring Applications for Heterogeneous Systems: Program Composition and Optimization Using Cognitive Techniques

FPGA-based acceleration of CHARMM-potential minimization

Using Reconfigurable Logic to Optimise GPU Memory Accesses

Performance analysis of memory transfers and GEMM subroutines on NVIDIA Tesla GPU cluster

Performance comparison of single-precision SPICE Model-Evaluation on FPGA, GPU, Cell, and multi-core processors

Fine-grain Parallelism Using Multi-core, Cell/BE, and GPU Systems: Accelerating the Phylogenetic Likelihood Function

Pushing the Envelope: Extreme Network Coding on the GPU

Demystifying GPU microarchitecture through microbenchmarking

Shader Performance Analysis on a Modern GPU Architecture

Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures

Recent source codes

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

CUDAnalyst (CUDA + Analyst)

CodegenBench

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

Most viewed papers (last 30 days)