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Soren: Adaptive MapReduce for Programmable GPUs

Reza Mokhtari, Amin Abbasi, Farshad Khunjush, Reza Azimi

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Tags: Computer science, CUDA, MapReduce, nVidia, nVidia GeForce GTX 480

November 23, 2011 by hgpu

Towards solving the Table Maker’s Dilemma on GPU

Pierre Fortin, Mourad Gouicem, Stef Graillat

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Tags: Algorithms, Computer science, CUDA, Elementary functions, nVidia, Tesla C2070

November 23, 2011 by hgpu

Building-Blocks for Performance Oriented DSLs

Tiark Rompf, Arvind K. Sujeeth, HyoukJoong Lee, Kevin J. Brown, Hassan Chafi, Martin Odersky, Kunle Olukotun

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Programming Languages, Tesla C2050

November 23, 2011 by hgpu

TEG: GPU Performance Estimation Using a Timing Model

Junjie Lai, Andre Seznec

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance

November 23, 2011 by hgpu

Dynamic adaptation and distribution of binaries to heterogeneous architectures

Espen Angell Kristiansen

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, nVidia GeForce GT 220, nVidia GeForce GTX 280, OpenCL, Package, Playstation, Thesis

November 22, 2011 by hgpu

Dynamic Heterogeneous Scheduling Decisions Using Historical Runtime Data

Chris Gregg, Michael Boyer, Kim Hazelwood, Kevin Skadron

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Tags: ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, OpenCL, Performance, Task scheduling

November 22, 2011 by hgpu

Parallelizing Multicore Cache Simulations using Heterogeneous Computing on General Purpose and Graphics Processors

Nikolaos Strikos, Georgios Keramidas, Stefanos Kaxiras

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia GeForce 8800 GTX

November 22, 2011 by hgpu

GPU-based Multi-start Local Search Algorithms

The Van Luong, Nouredine Melab, El-Ghazali Talbi

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 280, Optimization, Search

November 22, 2011 by hgpu

Experiences with Achieving Portability across Heterogeneous Architectures

Lukasz G. Szafaryn, Todd Gamblin, Bronis R. de Supinski, Kevin Skadron

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 460, OpenMP, Performance

November 22, 2011 by hgpu

Online Adaptive Code Generation and Tuning

Ananta Tiwari, Jeffrey K. Hollingsworth

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Tags: Code generation, Computer science, Optimization

November 21, 2011 by hgpu

Issues in Heterogenenous GPU Clusters

Patrick Carpenter, William Symon

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Tags: Computer science, GPU cluster, Heterogeneous systems, Review

November 21, 2011 by hgpu

A new approach for sparse matrix vector product on NVIDIA GPUs

F. Vazquez, J. J. Fernandez, E. M. Garzon

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Optimization, Sparse matrix

November 21, 2011 by hgpu

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

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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

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high performance computing on graphics processing units: hgpu.org

Soren: Adaptive MapReduce for Programmable GPUs

Towards solving the Table Maker’s Dilemma on GPU

Building-Blocks for Performance Oriented DSLs

TEG: GPU Performance Estimation Using a Timing Model

Dynamic adaptation and distribution of binaries to heterogeneous architectures

Dynamic Heterogeneous Scheduling Decisions Using Historical Runtime Data

Parallelizing Multicore Cache Simulations using Heterogeneous Computing on General Purpose and Graphics Processors

GPU-based Multi-start Local Search Algorithms

Experiences with Achieving Portability across Heterogeneous Architectures

Online Adaptive Code Generation and Tuning

Issues in Heterogenenous GPU Clusters

A new approach for sparse matrix vector product on NVIDIA GPUs

Recent source codes

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

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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