ssgmath

ssgmath's Stars

• dask/dask

  Parallel computing with task scheduling

  Language:Python12.7k2135.2k1.7k

• intel/scikit-learn-intelex

  Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

  Language:Python1.2k29239175

• PrincetonUniversity/athena-public-version

  (MOVED) Athena++ GRMHD code and adaptive mesh refinement (AMR) framework. Active repository --->

  Language:C++1605367117

• NCAR/ParallelIO

  A high-level Parallel I/O Library for structured grid applications

  Language:C1402195953

• PhysicsofFluids/AFiD

  A highly parallel application for Rayleigh-Benard and Taylor-Couette flows

  Language:Fortran90231139

• geodynamics/Rayleigh

  Rayleigh: Pseudo-spectral MHD

  Language:Fortran63276748

• PredictiveIntelligenceLab/UQPINNs

  Language:Jupyter Notebook626131

• zonca/python_hpc_tutorial

  Language:Jupyter Notebook502012

• PhysicsofFluids/AFiD_GPU_opensource

  Version of the AFiD code ported to GPU accelerators

  Language:Fortran4222119

• sdsc/sdsc-summer-institute-2019

  SDSC Summer Institute 2019 material

  Language:HTML189243

• stevenireeves/GPU_Computing

  Repository for supplemental codes for GPU Programming

  Language:C++17109

• sdsc/sdsc-summer-institute-2018

  SDSC Summer Institute 2018 Teaching Material

  Language:HTML1110150

• sparticlesteve/cori-intml-examples

  Examples for interactive distributed machine learning on the Cori supercomputer

  Language:Jupyter Notebook11607

• dtamayo/MachineLearning

  Files for the UTSC machine learning seminar

  Language:Jupyter Notebook6809

• olcf/XC30-Training

  Sides and Exercises from October 17 XC30 training

  Language:C65

• cinemascience/cinemascience.github.io

  Cinema Science Organization web page

  Language:JavaScript43

• MustafaMustafa/data-day-2018-DL-Scaling

  Scaling Deep Learning on Cori: Hands-on Activities

  Language:Jupyter Notebook4203

• sdsc-training/webinars

  Site that will contain webinar materials

  4503

• jonwoodring/ortrta

  A Scientist's Guide to the Relational Data Model (or One Reader to Rule Them All) - LambdaConf 2017 talk

  Language:HTML20