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Parallel and in-process compilation of individuals for genetic programming on GPU

Hakan Ayral, Songul Albayrak

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Tags: Computer science, CUDA, Genetic programming, nVidia, nVidia GRID K520, Operating systems, Package

May 24, 2017 by hgpu

Intel Xeon Phi acceleration of Hybrid Total FETI solver

Michal Merta, Lubomir Riha, Ondrej Meca, Alexandros Markopoulos, Tomas Brzobohaty, Tomas Kozubek, Vit Vondrak

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Tags: Algorithms, Computer science, Intel Xeon Phi, Laplace and Poisson equation, OpenMP, Package, Sparse direct solvers, Sparse matrix

May 24, 2017 by hgpu

MEDINA: MECCA Development in Accelerators – KPP Fortran to CUDA source-to-source Preprocessor

Michail Alvanos, Theodoros Christoudias

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Tags: Chemistry, Compilers, Computer science, CUDA, Fortran, nVidia, Package, Python

May 22, 2017 by hgpu

Inferring the Scheduling Policies of an Embedded CUDA GPU

Nathan Otterness, Ming Yang, Tanya Amert, James H. Anderson, F. Donelson Smith

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Tegra TX1, Package, Task scheduling

May 22, 2017 by hgpu

CLBlast: A Tuned OpenCL BLAS Library

Cedric Nugteren

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Tags: AMD Radeon R9 M370X, ARM, ATI, BLAS, Computer science, Intel HD 5100, Linear Algebra, Machine learning, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan X, OpenCL, Package

May 18, 2017 by hgpu

Efficient Parallel Methods for Deep Reinforcement Learning

Alfredo V. Clemente, Humberto N. Castejon, Arjun Chandra

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Tags: Algorithms, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GXT 980 Ti, Package, Python, TensorFlow

May 18, 2017 by hgpu

Block-Parallel IDA* for GPUs

Satoru Horie, Alex Fukunaga

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GRID K520, Package

May 11, 2017 by hgpu

Accelerating solutions of PDEs with GPU-based swept time-space decomposition

Daniel J Magee, Kyle E Niemeyer

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Tags: Algorithms, cfd, Computational Physics, CUDA, Differential equations, Fluid dynamics, nVidia, Package, Partial differential equations, PDEs, Physics, Tesla K40

May 11, 2017 by hgpu

DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing

Weihua Guo, You Xu, Xueyang Feng

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Tags: Biology, Computer science, Deep learning, Medicine, nVidia, nVidia GeForce GTX 1080, Package, Python, TensorFlow

May 11, 2017 by hgpu

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Konstantinos Krommydas

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 7660, ATI Radeon HD 7970, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Performance, Tesla K20, Thesis

May 9, 2017 by hgpu

Fast Sorting Algorithms using AVX-512 on Intel Knights Landing

Berenger Bramas

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenMP, Package, Sorting

May 9, 2017 by hgpu

Efficient Parallel Strategy Improvement for Parity Games

John Fearnley

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Logic in Computer Science, nVidia, nVidia GeForce GTX 780, Package

May 9, 2017 by hgpu

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

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

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high performance computing on graphics processing units: hgpu.org

Parallel and in-process compilation of individuals for genetic programming on GPU

Intel Xeon Phi acceleration of Hybrid Total FETI solver

MEDINA: MECCA Development in Accelerators – KPP Fortran to CUDA source-to-source Preprocessor

Inferring the Scheduling Policies of an Embedded CUDA GPU

CLBlast: A Tuned OpenCL BLAS Library

Efficient Parallel Methods for Deep Reinforcement Learning

Block-Parallel IDA* for GPUs

Accelerating solutions of PDEs with GPU-based swept time-space decomposition

DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Fast Sorting Algorithms using AVX-512 on Intel Knights Landing

Efficient Parallel Strategy Improvement for Parity Games

Recent source codes

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

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

TRUST: a thermalhydraulic software package for CFD simulations

Modular: The Modular Platform (includes MAX & Mojo)

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

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