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A Practical Performance Model for Compute and Memory Bound GPU Kernels

Elias Konstantinidis, Yiannis Cotronis

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Tags: Benchmarking, CUDA, OpenCL, Performance prediction

May 23, 2016 by ekondis

Performance models for CPU-GPU data transfers

B. van Werkhoven, J. Maassen, F.J. Seinstra, H.E. Bal

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Tags: Computer science, CUDA, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, PCIe, Performance, Performance prediction, Tesla K20

June 5, 2014 by bennotsi

A Performance Analysis Framework for Identifying Potential Benefits in GPGPU Applications

Jaewoong Sim, Aniruddha Dasgupta, Hyesoon Kim, and Richard Vuduc

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Tags: Analytical model, CUDA, GPGPU architecture, nVidia, Performance benefit prediction, Performance prediction, Tesla C2050

March 30, 2012 by Moaddeli

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E2C-Sim: a simulator and workload generator for Edge-to-Cloud environments

E2C: A Visual Simulator to Reinforce Education of Heterogeneous Computing Systems

Kernel Tuner

Kernel Launcher: C++ Library for Optimal-Performance Portable CUDA Applications

Clava: C/C++ Source-to-Source Tool based on Clang

Challenges and Opportunities in C/C++ Source-To-Source Compilation

gpuLik

Statistical Computing With Graphics Processing Units

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

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