Hugo Brunie's repositories

PyFloT

Mixed precision tuning tool

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amrex

AMReX: Software Framework for Block Structured AMR

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arctlength

playing with arclength

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ASPIRE-Python

Algorithms for Single Particle Reconstruction

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benchmarks

small benchmarks

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conus

A wrapper for random123 to be used by GalSim

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cublas_benchmarks

Some benchmarks testing gemm and gemv performance

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DG-SparseGrid

Matlab implementation of ASGarD

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finufft

Non-uniform fast Fourier transform library of types 1,2,3 in dimensions 1,2,3

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GalSim

The modular galaxy image simulation toolkit. Documentation:

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hello-numerical-world-atpesc-2020

Hello Numerical World repository copy for ATPESC 2020

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kronmult993

CPU and GPU implementations of kronmult.

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libbacktrace

A C library that may be linked into a C/C++ program to produce symbolic backtraces

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llvm-project

The LLVM Project is a collection of modular and reusable compiler and toolchain technologies. Note: the repository does not accept github pull requests at this moment. Please submit your patches at http://reviews.llvm.org.

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netcdf-c

Official GitHub repository for netCDF-C libraries and utilities.

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opencl_optim_examples

Codelab to learn optimization methods on Kalray MPPA OpenCL

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PeleC

An AMR code for compressible reacting flow simulations

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PeleLM

An adaptive mesh hydrodynamics simulation code for low Mach number reacting flows

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pLiner

pLiner is a framework that helps programmers identify locations in the source of numerical code that are highly affected by compiler optimizations.

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PSyclone

Domain-specific compiler and code transformation system for Finite Difference/Volume/Element Earth-system models in Fortran

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pyworkforce

Standard tools for workforce management, queuing, scheduling, rostering and optimization problems.

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tvm_ttile

Open deep learning compiler stack for cpu, gpu and specialized accelerators

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utvm_staticrt_codegen

This project contains a code generator that produces static C NN inference deployment code targeting tiny micro-controllers (TinyML) as replacement for other µTVM runtimes. This tools generates a runtime, which statically executes the compiled model. This reduces the overhead in terms of code size and execution time compared to having a dynamic on-device runtime.

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