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OpenCL/CUDA algorithms for parallel decoding of any irregular LDPC code using GPU

Jan Broulim, Alexander Ayriyan, Vjaceslav Georgiev

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Tags: Algorithms, Computer science, CUDA, Error recovery, nVidia, OpenCL, Tesla K40, Tutorial

September 8, 2016 by hgpu

Parallel Tree Traversal for Nearest Neighbor Query on the GPU

Moohyeon Nam, Jinwoong Kim, Beomseok Nam

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Tags: Algorithms, Biology, Computational biology, Computer science, CUDA, Information Retrieval, Nearest neighbour, nVidia, Tesla K40

September 5, 2016 by hgpu

Implementation and Performance Analysis of Many-body Quantum Chemical Methods on the Intel Xeon Phi Coprocessor and NVIDIA GPU Accelerator

Bobo Shi

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Tags: Algorithms, Chemistry, Computational chemistry, CUDA, Intel Xeon Phi, nVidia, OpenMP, Tesla K40, Thesis

September 5, 2016 by hgpu

Improving the Performance of the Contextual Spaces Re-Ranking Algorithm on Heterogeneous Systems

Flavia Pisani, Daniel C. G. Pedronette, Ricardo da S. Torres, Edson Borin

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Tags: Algorithms, ATI, ATI Radeon HD 6550, Computer science, Heterogeneous systems, List ranking, OpenCL

September 5, 2016 by hgpu

Matrix Computations and Optimization in Apache Spark

Reza Bosagh Zadeh, Xiangrui Meng, Alexander Ulanov, Burak Yavuz, Li Pu, Shivaram Venkataraman, Evan Sparks, Aaron Staple, Matei Zaharia

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, Package, Scala, Spark, Tesla M2050

September 3, 2016 by hgpu

Ultra-Fast Detection of Higher-Order Epistatic Interactions on GPUs

Daniel Junger, Christian Hundt, Jorge Gonzalez-Dominguez, Bertil Schmidt

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Tags: Algorithms, Bioinformatics, Clustering, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX Titan X

September 3, 2016 by hgpu

Fast 4D Sheared Filtering for Interactive Rendering of Distribution Effects

Ling-Qi Yan, Soham Uday Mehta, Ravi Ramamoorthi, Fredo Durand

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX Titan, Package, Raytracing, Rendering

September 3, 2016 by hgpu

Optimization of RAID Erasure Coding Algorithms for Intel Xeon Phi

Aleksei Marov, Andrey Fedorov

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Tags: Algorithms, Computer science, Error recovery, Intel Xeon Phi

August 31, 2016 by hgpu

SafeGPU: Contract- and Library-Based GPGPU for Object-Oriented Languages

Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz

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Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, nVidia Quadro K 2000 M, Package

August 31, 2016 by hgpu

Massively parallel simulations of relativistic fluid dynamics on graphics processing units with CUDA

Dennis Bazow, Ulrich W. Heinz, Michael Strickland

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Tags: Algorithms, Computational Physics, CUDA, Fluid dynamics, High Energy Physics - Phenomenology, Intel Xeon Phi, Nuclear Theory, nVidia, nVidia GeForce GTX 560 M, nVidia GeForce GTX 980 Ti, nVidia GeForce GTX Titan Z, Physics

August 28, 2016 by hgpu

Accelerating Exact and Approximate Inference for (Distributed) Discrete Optimization with GPUs

Ferdinando Fioretto, Enrico Pontelli, William Yeoh, Rina Dechter

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Tags: Algorithms, Artificial intelligence, Bayesian, Computer science, nVidia, nVidia GeForce GTX Titan, nVidia GeForce GTX Titan X, Optimization, Package, Tesla M2075

August 23, 2016 by hgpu

Hybrid CPU-GPU Framework for Network Motifs

Ryan A. Rossi, Rong Zhou

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Tags: Algorithms, Computer science, Graph theory, Machine learning, nVidia, nVidia GeForce GTX Titan Black

August 23, 2016 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

OpenCL/CUDA algorithms for parallel decoding of any irregular LDPC code using GPU

Parallel Tree Traversal for Nearest Neighbor Query on the GPU

Implementation and Performance Analysis of Many-body Quantum Chemical Methods on the Intel Xeon Phi Coprocessor and NVIDIA GPU Accelerator

Matrix Computations and Optimization in Apache Spark

Ultra-Fast Detection of Higher-Order Epistatic Interactions on GPUs

Fast 4D Sheared Filtering for Interactive Rendering of Distribution Effects

Optimization of RAID Erasure Coding Algorithms for Intel Xeon Phi

SafeGPU: Contract- and Library-Based GPGPU for Object-Oriented Languages

Massively parallel simulations of relativistic fluid dynamics on graphics processing units with CUDA

Accelerating Exact and Approximate Inference for (Distributed) Discrete Optimization with GPUs

Hybrid CPU-GPU Framework for Network Motifs

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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