OpenGenus Tech Review Team - OpenGenus IQ: Learn Algorithms, DL, System Design (Page 145)

ONNX format for interchangeable AI models

The Open Neural Network Exchange Format (ONNX) is a format for exchanging deep learning/ artificial intelligence models. It will make deep learning models portable thus preventing vendor lock in. We have provided a real life use case of ONNX, benefits of ONNX and the key ideas and challenges of ONNX

Machine Learning (ML)

MKL (Math Kernel Library), a Basic Linear Algebra Subprograms (BLAS) Library

Intel's Math Kernel Library (Intel MKL) is a Basic Linear Algebra Subprograms (BLAS) Library that optimizes code with minimal effort for future generations of Intel processors. We have presented how to download and use MKL using an example of matrix multiplication in MKL Library

Machine Learning (ML)

FLAME BLIS, a Basic Linear Algebra Subprograms Library

FLAME BLIS is an open source portable software framework/ Basic Linear Algebra Subprograms (BLAS) library for instantiating high-performance BLAS-like dense linear algebra libraries. We have presented how to install and use BLIS using an example of matrix multiplication in FLAME BLIS

Machine Learning (ML)

OpenBLAS, a Basic Linear Algebra Subprograms Library

OpenBLAS is an open source optimized BLAS (Basic Linear Algebra Subprograms) library based on GotoBLAS2 1.13 BSD version. We have presented how to install and use OpenBLAS with a matrix multiplication example in OpenBLAS

Machine Learning (ML)

Basic Linear Algebra Subprograms (BLAS) Library

The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations. There are three levels within the BLAS library. The various implementations include Intel's MKL, BLIS, NetLib's BLAS, OpenBLAS, BLAS++ and others

Machine Learning (ML)

PyTorch vs TensorFlow

We have compared PyTorch and TensorFlow on the basis of various metrics to help you determine the framework you should go forward with. In short, TensorFlow gives you more control and high computational efficiency while PyTorch gives you the simplicity to develop applications.

Machine Learning (ML)

Install and use NNVM Compiler

NNVM compiler is a graph compiler for the TVM Stack that takes in models in NNVM Intermediate Representation format and compiles them for various backends such as LLVM, METAL, CUDA and others. We have presented how to install and build NNVM from source and how to use it with the configurations

Machine Learning (ML)

NNVM Intermediate Representation

NNVM is a reusable graph Intermediate Representation stack for deep learning systems. It provides useful API to construct, represent and transform computation graphs to get most high-level optimization needed in deep learning. NNVM is a part of TVM stack for deep learning and has a compiler as well

Machine Learning (ML)

Run a ResNet34 model in ONNX format on TVM Stack with LLVM backend

In this guide, we will run a ResNet34 model in ONNX format on the TVM Stack with LLVM backend. You do not need any specialized equipment like GPU and TPU to follow this guide. A simple CPU is enough.

Machine Learning (ML)

Run a ResNet18 model in ONNX format on TVM Stack with LLVM backend

In this guide, we will run a ResNet18 model in ONNX format on the TVM Stack with LLVM backend. You do not need any specialized equipment like GPU and TPU to follow this guide. A simple CPU is enough.

Machine Learning (ML)

Run a ResNet101 model in ONNX format on TVM Stack with LLVM backend

In this guide, we will run a ResNet101 model in ONNX format on the TVM Stack with LLVM backend. You do not need any specialized equipment like GPU and TPU to follow this guide. A simple CPU is enough.

Machine Learning (ML)

Run a ResNet152 model in ONNX format on TVM Stack with LLVM backend

In this guide, we will run a ResNet152 model in ONNX format on the TVM Stack with LLVM backend. You do not need any specialized equipment like GPU and TPU to follow this guide. A simple CPU is enough.

Machine Learning (ML)

Run a ResNet50 model in ONNX format on TVM Stack with LLVM backend

In this guide, we will run a ResNet50 model in ONNX format on the TVM Stack with LLVM backend. You do not need any specialized equipment like GPU and TPU to follow this guide. A simple CPU is enough.

Machine Learning (ML)

Run a VGG16 model in ONNX format on TVM Stack with LLVM backend

In this guide, we will run a VGG16 model in ONNX format on the TVM Stack with LLVM backend. You do not need any specialized equipment like GPU and TPU to follow this guide. A simple CPU is enough.

Machine Learning (ML)

Run a VGG19 model in ONNX format on TVM Stack with LLVM backend

In this guide, we will run a VGG19 model in ONNX format on the TVM Stack with LLVM backend. You do not need any specialized equipment like GPU and TPU to follow this guide. A simple CPU is enough.

Machine Learning (ML)

Install TVM and NNVM from source

In this guide, we will walk you through the process of installing TVM and NNVM compiler from source along with all its dependencies such as HalideIR, DMLC-CORE, DLPACK and COMPILER-RT. Once installed, you can enjoy compiling models in any frameworks on any backend of your choice.

Machine Learning (ML)

TVM: A Deep Learning Compiler Stack

TVM is an open source deep learning compiler stack for CPUs, GPUs, and specialized accelerators that takes in models in various frameworks like TensorFlow, Keras, ONNX and others and deploys them on various backends like LLVM, CUDA, METAL and OpenCL. It gives comparably better performance than other

game theory

Traveler's dilemma

In game theory, the traveler's dilemma (abbreviated TD) is a type of non-zero-sum game in which two players attempt to maximize their own payoff, without any concern for the other player's payoff. We have presented the code and applications for Traveler's dilemma in O(1) time complexity.

Software Engineering

Git: git remote add command

git remote add command is a basic git command which add a remote repository as an origin of your local repository. The basic idea is that the remote repository is the final working repository which is considered by everyone and your local repository is your local copy holding your changes

git

Git: git commit command

git commit is a basic git command which saves the staged changes made to your local repository. We have explored how we can skip the add command and the information provided by the commit command of Git

git

Git diff command

Git diff command show changes between the working tree and the index or a tree, changes between the index and a tree, changes between two trees, changes between two blob objects, or changes between two files on disk.

git

Git add command: track a new file

In this article, we learnt how to track a new file in a project using Git. In the process, we explored the git add command to add a new file to tracking, touch command to create a new file and git status command on two different occasions to explore the status of the content tracked by Git.

git

Git Status command: File stages in Git

In this article, we have explored the various stages that a file assumes in Git. In the process, we came across tracked and untracked files and committed, modified and staged files and the significance of each stage in relation to git status.

git

Git: git status command

In this article, we have explored the git status command which gives us information regarding our current branch, remote repository, changes that have been staged for commit and changes that have not been staged for commit. In the process, we have explored the clear command as well.

git

Git: Initialize a Git repository

In this article, we have explored the procedure to initializing a new Git repository. In the process, we have explored the cd (change directory) command, git init command, cd .git command and ls command to explore the hidden files in the .git folder.