high performance computing on graphics processing units: hgpu.org

Siegfried Benkner, Sabri Pllana, Jesper Larsson Traff, Philippas Tsigas, Andrew Richards, Raymond Namyst, Beverly Bachmayer, Christoph Kessler, David Moloney, Peter Sanders

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Performance, Tesla C1060

February 8, 2012 by hgpu

GMP implementation on CUDA – A Backward Compatible Design With Performance Tuning

Hao Jun Liu, Chu Tong

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Tags: Algorithms, Computer science, CUDA, Elementary functions, nVidia, nVidia GeForce GTX 280, Performance, Security

February 7, 2012 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Better speedups using simpler parallel programming for graph connectivity and biconnectivity

NUMA Data-Access Bandwidth Characterization and Modeling

Performance Analysis of a Novel GPU Computation-to-core Mapping Scheme for Robust Facet Image Modeling

KUDA: GPU Accelerated Split Race Checker

Efficient Performance Evaluation of Memory Hierarchy for Highly Multithreaded Graphics Processors

Speculative Parallelization on GPGPUs

Model-Driven Tile Size Selection for DOACROSS Loops on GPUs

Cross Teaching Parallelism and Ray Tracing: A Project-based Approach to Teaching Applied Parallel Computing

Automatic Performance Optimization in ViennaCL for GPUs

The Boat Hull Model: Adapting the Roofline Model to Enable Performance Prediction for Parallel Computing

The PEPPHER Approach to Programmability and Performance Portability for Heterogeneous many-core Architectures

GMP implementation on CUDA – A Backward Compatible Design With Performance Tuning

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR