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FIESTA 4: optimized Feynman integral calculations with GPU support

Alexander V. Smirnov

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Tags: CUDA, High Energy Physics - Phenomenology, Mathematical Software, nVidia, Package, Physics, Tesla X2070

November 12, 2015 by hgpu

Simulating of query processing on multiprocessor database systems with modern coprocessors

Konstantin Y. Besedin, Pavel S. Kostenetskiy

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Tags: Computer science, CUDA, Databases, Intel Xeon Phi, nVidia, OpenMP, Tesla X2070

May 29, 2014 by hgpu

Collision for 75-step SHA-1: Intensive Parallelization with GPU

E.A. Grechnikov, A.V. Adinetz

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Tags: Computer science, nVidia, OpenCL, Package, Security, Tesla M2050, Tesla X2070

December 18, 2011 by hgpu

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

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

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

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

TRUST: a thermalhydraulic software package for CFD simulations

TRUST: the HPC open-source CFD platform – from CPU to GPU

Modular: The Modular Platform (includes MAX & Mojo)

Mojo: MLIR-Based Performance-Portable HPC Science Kernels on GPUs for the Python Ecosystem

Allo: Accelerator Design Language

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

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