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DISC: A Dynamic Shape Compiler for Machine Learning Workloads

Kai Zhu, Wenyi Zhao, Zhen Zheng, Tianyou Guo, Pengzhan Zhao, Junjie Bai, Jun Yang, Xiaoyong Liu, Lansong Diao, Wei Lin

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Tags: Compilers, Comuter science, CUDA, Machine learning, nVidia, Tesla T4

March 14, 2021 by hgpu

Performance Improvement of Data Mining in Weka through GPU Acceleration

Tiago Augusto Engel, Andrea Schwertner Charao, Manuele Kirsch-Pinheiro, Luiz-Angelo Steffenel

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Tags: Comuter science, CUDA, Data mining, Java, Matrix multiplication, nVidia, nVidia Quadro K 2000, Package, Tesla K20, Tesla M2050

June 13, 2014 by hgpu

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations

microSYCL: SYCL micro-benchmarks repository

Exploring SYCL as a Portability Layer for High-Performance Computing on CPUs

XaaS containers

Acceleration as a Service (XaaS) Source Containers

CASS: Cuda-Amd aSSembly

CASS: Nvidia to AMD Transpilation with Data, Models, and Benchmark

Cluser of smartphones for edge computing application using TensorFlow

Low-cost edge computing using upcycled smartphones

SYCL Container

Exploring SYCL for batched kernels with memory allocations

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Can Large Language Models Predict Parallel Code Performance?

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