high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications

Hybrid quantum programming with PennyLane Lightning on HPC platforms

Ali Asadi, Amintor Dusko, Chae-Yeun Park, Vincent Michaud-Rioux, Isidor Schoch, Shuli Shu, Trevor Vincent, Lee James O'Riordan

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Tags: AMD Radeon Instinct MI250X, ATI, HPC, nVidia, nVidia A100, OpenMP, Package, Physics, Quantum Physics

March 10, 2024 by hgpu

Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale

Dan Zhao, Siddharth Samsi, Joseph McDonald, Baolin Li, David Bestor, Michael Jones, Devesh Tiwari, Vijay Gadepally

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Tags: AI, Computer science, Energy-efficient computing, HPC, nVidia, nVidia A100

March 3, 2024 by hgpu

Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks

Kade M. Heckel, Thomas Nowotny

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia RTX A6000, Package, Python

March 3, 2024 by hgpu

Parallel programming in mobile devices with FancyJCL

Sergio Afonso, Óscar Gómez-Cárdenes, Paula Expósito, Vicente Blanco, Francisco Almeida

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Tags: Computer science, DSP, Heterogeneous systems, Image processing, Java, OpenCL, Package

March 3, 2024 by hgpu

Low-Overhead Trace Collection and Profiling on GPU Compute Kernels

Sébastien Darche, Michel R. Dagenais

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, CUDA, HIP, nVidia, Package, Performance, Profiling

March 3, 2024 by hgpu

Using AI libraries for Incompressible Computational Fluid Dynamics

Boyang Chen, Claire E. Heaney, Christopher C. Pain

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Tags: AI, Artificial intelligence, cfd, CUDA, Fluid dynamics, Neural networks, nVidia, Partial differential equations, PDEs, Tesla T4

March 3, 2024 by hgpu

APPy: Annotated Parallelism for Python on GPUs

Tong Zhou, Jun Shirako, Vivek Sarkar

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Tags: Code generation, Compilers, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce RTX 3090, Python

February 25, 2024 by hgpu

Analyzing GPU Performance in Virtualized Environments: A Case Study

Adel Belkhiri, Michel Dagenais

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Tags: Computer science, CUDA, Java, nVidia, OpenCL, Package, Performance, Virtualization

February 25, 2024 by hgpu

Green AI: A Preliminary Empirical Study on Energy Consumption in DL Models Across Different Runtime Infrastructures

Negar Alizadeh, Fernando Castor

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Tags: Computer science, CUDA, Deep learning, Energy-efficient computing, nVidia, nVidia GeForce RTX 3070, Package, PyTorch, TensorFlow

February 25, 2024 by hgpu

Benchmarking and Dissecting the Nvidia Hopper GPU Architecture

Weile Luo, Ruibo Fan, Zeyu Li, Dayou Du, Qiang Wang, Xiaowen Chu

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Tags: Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, nVidia, nVidia A100, nVidia GeForce RTX 4090, nVidia H800, Performance, PTX

February 25, 2024 by hgpu

Assessing opportunities of SYCL for biological sequence alignment on GPU-based systems

Manuel Costanzo, Enzo Rucci, Carlos García-Sanchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: AMD Radeon RX 6700 XT, AMD Radeon RX Vega 6, ATI, Bioinformatics, Biology, Computational biology, CUDA, Heterogeneous systems, Intel Arc A770, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, nVidia V100, oneAPI, Package, Sequence alignment, SYCL

February 25, 2024 by hgpu

pSTL-Bench: A Micro-Benchmark Suite for Assessing Scalability of C++ Parallel STL Implementations

Ruben Laso, Diego Krupitza, Sascha Hunold

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Ampere A2, OpenMP, performance portability, Tesla P4

February 18, 2024 by hgpu

Tutoring LLM into a Better CUDA Optimizer

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

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

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

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high performance computing on graphics processing units: hgpu.org

Applications

Hybrid quantum programming with PennyLane Lightning on HPC platforms

Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale

Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks

Parallel programming in mobile devices with FancyJCL

Low-Overhead Trace Collection and Profiling on GPU Compute Kernels

Using AI libraries for Incompressible Computational Fluid Dynamics

APPy: Annotated Parallelism for Python on GPUs

Analyzing GPU Performance in Virtualized Environments: A Case Study

Green AI: A Preliminary Empirical Study on Energy Consumption in DL Models Across Different Runtime Infrastructures

Benchmarking and Dissecting the Nvidia Hopper GPU Architecture

Assessing opportunities of SYCL for biological sequence alignment on GPU-based systems

pSTL-Bench: A Micro-Benchmark Suite for Assessing Scalability of C++ Parallel STL Implementations

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