Mojo Programming Language — An Overview
Mojo is a Programming Language which allows to combine the usability of Python but with the performance of C, C++ and Rust. Mojo Programming Language utilizes next-generation compiler technologies with features like caching, multithreading and cloud distribution technologies. Further, Auto-Tuning and compile-time Metaprogramming features allows to write code for several hardware. Mojo Programming Language has advantages like Usability & Programmability, best performance, Interoperability and Extensibility. Mojo Programming Language is being developed and introduced by Modular.
Important Features of Mojo Programming Language are discussed below,
Usability and Programmability:
Mojo Programming Language is designed as a Superset of Python Programming Language, hence many of the language concepts and features we know in python translate directly to Mojo. Existing Python Packages can also be imported to use in Mojo.
Example:
The print statement in Mojo Programming Language is same as in Python Programming Language.
print(“Mojo Programming Language!!”)
Output:
Mojo Programming Language!!
However, Mojo is a New Programming Language on its own. Mojo also has more in common with languages like C++, Rust and also uses Python Syntax and fully supports Python Packages.
Important Features of Mojo Programming Language for Performance Enhancement are,
Progressive Types:
Mojo leverages types for enhanced and better performance, also for Error Checking.
Zero Cost Abstractions:
Gives control of Storage efficiently with inline-allocating values into structures.
Ownership and Borrow Checker:
Mojo gives the advantage of Memory Safety.
Portable Parametric Algorithms:
Mojo leverages compile-time meta-programming which allows developers to write hardware-agnostic algorithms and reduces boilerplate / repeated code.
Language Integrated Auto-Tuning:
Mojo provides Language Integrated Auto-Tuning to automatically find the best values for the parameters thereby to maximize the performance of target hardware.
Full Power of MLIR:
Mojo leverages the full power of MLIR (Multi-Level Intermediate Representation).
Parallel Heterogenous Runtime and Fast Compile Times:
Mojo provides Parallel Heterogenous Runtime and Mojo offers fast compile times which allows the developers for faster code execution and debugging.
Performance:
Mojo offers Parallelization which leverages MLIR (Multi-Level Intermediate Representation) and enables developers to take advantage of Vectors, Threads and AI Hardware Units. The use of Vectors allows processing multiple data simultaneously thereby resulting in enhanced performance. The use of Threads leads to concurrent tasks execution and also the use of AI Hardware Units leads to enhanced performance.
By incorporating these advanced features, Mojo achieves high performance and Mojo claims that it is 35000x faster than Python.
Interoperability:
Mojo offers Interoperability with Python Ecosystem which enables developers to use the existing Libraries and Tools of Python. Thus, Mojo allows developers to use libraries like Matplotlib, etc and developers custom code. Interoperability in Mojo allows developers to use most of the useful Python Libraries and eliminating to again develop these useful libraires in Mojo. This results in code reuse and efficient development by the developers.
Extensibility:
Mojo offers Extensibility to extend the AI Models with pre and post-operating functions or replace with custom operations. Mojo can upgrade the existing operations in the AI Model.
We had seen an Introduction and various features of Mojo Programming Language. Programming with Mojo and accessing Mojo will be discussed further.
Thankyou for reading this blog on Mojo Programming Language — An Overview!!!
Reference: https://www.modular.com/mojo
