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GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Dinei A. Rockenbach, Gabriell Araujo, Dalvan Griebler, Luiz Gustavo Fernandes

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce RTX 3090, OpenCL, OpenMP, Package

January 20, 2025 by hgpu

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

Huanting Wang, Patrick Lenihan, Zheng Wang

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Tags: Artificial intelligence, Computer science, Machine learning, OpenCL, Optimization, Package, Software Engineering

January 6, 2025 by hgpu

A comparison of HPC-based quantum computing simulators using Quantum Volume

Lourens van Niekerk, Dhiraj Kumar, Aasish Kumar Sharma, Tino Meisel, Martin Leandro Paleico, Christian Boehme

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Tags: Benchmarking, CUDA, nVidia, nVidia A100, OpenCL, Overview, Physics, Quantum computing, Review

January 6, 2025 by hgpu

FortranX: Harnessing Code Generation, Portability, and Heterogeneity in Fortran

Sanil Rao, Mike Franusich, , Mohammad Alaul Haque Monil, Het Mankad, Jeffrey S. Vetter, Franz Franchetti

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Tags: AMD, ATI, Code generation, Computer science, CUDA, Differential equations, Fortran, Heterogeneous systems, HIP, nVidia, OpenCL, OpenMP, Partial differential equations, PDEs

December 8, 2024 by hgpu

The Rewriting of DataRaceBench Benchmark for OpenCL Program Validations

Chia-Chen Hsu, Chun-Lin Huang, Chao-Lin Lee, Jenq-Kuen Lee, Pei-Hung Lin

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Tags: Benchmarking, Computer science, LLVM, OpenCL, Performance

November 17, 2024 by hgpu

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale, Farah Ferdaus, Aditya Tanikanti, Ken Raffenetti, Valerie Taylor, Murali Emani, Venkatram Vishwanath

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Tags: AI, AMD Radeon Instinct MI250, AMD Radeon Instinct MI300X, Artificial intelligence, ATI, Benchmarking, Computer science, CUDA, LLM, Machine learning, nVidia, nVidia A100, nVidia GH200, nVidia H100, OpenCL, Performance

November 10, 2024 by hgpu

Data-Driven Dynamic Autotuning: Optimizing Autotuning Overhead with Prior Tuning Data

Jaroslav Oľha

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Tags: AMD Radeon RX Vega 56, ATI, Auto-Tuning, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 680, nVidia GeForce GTX 750, nVidia GeForce RTX 2080 Ti, OpenCL, Performance, Tesla K20, Thesis

November 3, 2024 by hgpu

Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR

Arun Thangamani

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Tags: AMD Radeon Instinct Mi50, ATI, Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia A100, OpenCL, Thesis

October 13, 2024 by hgpu

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Dániel Koics, Endre Kovács 2, Olivér Hornyák

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Tags: nVidia, OpenCL, Package, PDEs, Performance, Physics

October 13, 2024 by hgpu

Deep Learning and Machine Learning with GPGPU and CUDA: Unlocking the Power of Parallel Computing

Ming Li, Ziqian Bi, Tianyang Wang, Yizhu Wen, Qian Niu, Junyu Liu, Benji Peng, Sen Zhang, Xuanhe Pan, Jiawei Xu, Jinlang Wang, Keyu Chen, Caitlyn Heqi Yin, Pohsun Feng, Ming Liu

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Tags: Book, Computer science, CUDA, Deep learning, FPGA, Machine learning, nVidia, OpenCL, OpenGL, TPU, Vulkan

October 13, 2024 by hgpu

Bitstream Database-Driven FPGA Programming Flow Based on Standard OpenCL

Topi Leppänen, Leevi Leppänen, Joonas Multanen, Pekka Jääskeläinen

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Tags: Computer science, Databases, FPGA, Heterogeneous systems, OpenCL, Package

September 29, 2024 by hgpu

Automatic Generation of OpenCL Code through Polyhedral Compilation with LLM

Marek Palkowski, Mateusz Gruzewski

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Tags: AMD Radeon RX 6800, ATI, Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, OpenCL, OpenMP

September 29, 2024 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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