From 14704da76aa71505d9e8d3ea67792b22f05629f6 Mon Sep 17 00:00:00 2001 From: Maxwell Cai Date: Thu, 9 Dec 2021 16:41:50 +0000 Subject: [PATCH] Update README.md --- README.md | 15 +-------------- 1 file changed, 1 insertion(+), 14 deletions(-) diff --git a/README.md b/README.md index 3a339dd..2d908d7 100644 --- a/README.md +++ b/README.md @@ -249,7 +249,7 @@ The application codes that constitute the UEABS are: - [QCD](#qcd) - [Quantum Espresso](#espresso) - [SPECFEM3D](#specfem3d) -- [TensorFlow](#tensorflow) + # ALYA @@ -482,17 +482,4 @@ QUANTUM ESPRESSO is written mostly in Fortran90, and parallelised using MPI and | [- Website](https://geodynamics.org/cig/software/specfem3d_globe/)
[- Source](https://github.com/geodynamics/specfem3d_globe.git)
[- Bench](https://repository.prace-ri.eu/git/UEABS/ueabs/tree/r2.1-dev/specfem3d)
[- Summary](https://repository.prace-ri.eu/git/UEABS/ueabs/blob/r2.1-dev/specfem3d/PRACE_UEABS_Specfem3D_summary.pdf) | Geodynamics | Fortran & C | yes | yes | Yes (CUDA) | 100k Fortran & 20k C | The software package SPECFEM3D simulates three-dimensional global and regional seismic wave propagation based upon the spectral-element method (SEM). | -# TensorFlow - -TensorFlow (https://www.tensorflow.org) is a popular open-source library for symbolic math and linear algebra, with particular optimization for neural-networks-based machine learning workflow. Maintained by Google, it is widely used for research and production in both the academia and the industry. - -TensorFlow supports a wide variety of hardware platforms (CPUs, GPUs, TPUs), and can be scaled up to utilize multiple compute devices on a single or multiple compute nodes. The main objective of this benchmark is to profile the scaling behavior of TensorFlow on different hardware, and thereby provide a reference baseline of its performance for different sizes of applications. - -There are many open-source datasets available for benchmarking TensorFlow, such as `mnist`, `fashion_mnist`, `cifar`, `imagenet`, and so on. This benchmark suite, however, would like to focus on a scientific research use case. `DeepGalaxy` is a code built with TensorFlow, which uses deep neural network to classify galaxy mergers in the Universe, observed by the Hubble Space Telescope and the Sloan Digital Sky Survey. -- Website: https://www.tensorflow.org/ -- Code download: https://github.com/maxwelltsai/DeepGalaxy -- [Instruction](tensorflow/README.md) -- [Test Case A](tensorflow/Testcase_A/) -- [Test Case B](tensorflow/Testcase_B/) -- [Test Case C](tensorflow/Testcase_C/) -- GitLab