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GPU Acceleration of Near-Minimal Logic Minimization

Ibrahim Savran, Jason D. Bakos

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla S1070

February 18, 2011 by hgpu

Axel: a heterogeneous cluster with FPGAs and GPUs

Kuen Hung Tsoi, Wayne Luk

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Tags: Computer science, CUDA, FPGA, GPU cluster, Heterogeneous systems, nVidia, OpenMPI, Tesla C1060

February 7, 2011 by hgpu

A Unified Runtime System for Heterogeneous Multi-core Architectures

Cedric Augonnet, Raymond Namyst

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia Quadro FX 4600

January 7, 2011 by hgpu

The Scalable Heterogeneous Computing (SHOC) benchmark suite

Anthony Danalis,Gabriel Marin,Collin McCurdy,Jeremy S. Meredith,Philip C. Roth,Kyle Spafford,Vinod Tipparaju,Jeffrey S. Vetter

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Tags: ATI, ATI Radeon HD 5770, ATI Radeon HD 5870, ATI Stream, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, nVidia GeForce 9400 M, OpenCL, Package, Performance, Tesla C1060

November 5, 2010 by hgpu

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

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high performance computing on graphics processing units: hgpu.org

GPU Acceleration of Near-Minimal Logic Minimization

Axel: a heterogeneous cluster with FPGAs and GPUs

A Unified Runtime System for Heterogeneous Multi-core Architectures

The Scalable Heterogeneous Computing (SHOC) benchmark suite

Recent source codes

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

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