high performance computing on graphics processing units: hgpu.org

hgpu.org » Memory model

An asymmetric distributed shared memory model for heterogeneous parallel systems

Isaac Gelado, John E. Stone, Javier Cabezas, Sanjay Patel, Nacho Navarro, Wen-mei W. Hwu

View

Download (PDF)

Tags: Computer science, CUDA, Memory, Memory model, nVidia, nVidia GeForce GTX 280

January 6, 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

Cache-efficient numerical algorithms using graphics hardware

Naga K. Govindaraju, Dinesh Manocha

View

Download (PDF)

Tags: Computer science, Memory model, nVidia, nVidia GeForce 6800 Ultra, nVidia GeForce 7900 GTX, nVidia GeForce 8800 GTX, OpenGL

December 5, 2010 by hgpu

A Memory Model for Scientific Algorithms on Graphics Processors

Naga K. Govindaraju, Scott Larsen, Jim Gray, Dinesh Manocha

View

Download (PDF)

Tags: Algorithms, Computer science, FFT, Memory model, nVidia, nVidia GeForce 6800 Ultra, nVidia GeForce 7800 GTX, nVidia GeForce 7900 GTX, Sorting

October 30, 2010 by hgpu

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

An asymmetric distributed shared memory model for heterogeneous parallel systems

Using Reconfigurable Logic to Optimise GPU Memory Accesses

Cache-efficient numerical algorithms using graphics hardware

A Memory Model for Scientific Algorithms on Graphics Processors

Recent source codes

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

LC Framework

Most viewed papers (last 30 days)