Setup of Sushi2 and introduction of basic usage

Sushi2 is a matrix library for JavaScript. It works with modern web browsers and node.js server-side JavaScript environment. By using WebCL technology, the wrapper of OpenCL, matrix operations are significantly accelerated with the power of GPU. Even there are no WebCL support, most function of Sushi2 works.

Setup for node.js

A npm package is provided, so installing it may be convenient.

npm install milsushi2

Sushi2 depends on node-opencl for GPU computing which allows dramatically faster computation. This dependency is optional, so even the installation of node-opencl fails, Sushi2 can work without it.

In my environment (Ubuntu 14.04 + NVIDIA CUDA 7.5), installation with node-opencl requires additional environment variables.

CPLUS_INCLUDE_PATH=/usr/local/cuda/include LIBRARY_PATH=/usr/local/cuda/lib64 npm install milsushi2
$ node
> var $M=require('milsushi2');
> $M.initcl();//OpenCL initialization, true if succeeds
> var x = $M.jsa2mat([[1,2],[3,4]]);
> var y = $M.jsa2mat([[0.1,0.5],[0.7,0.0]]);
> $, y);
Matrix 2x2 single
1.100000023841858       2.5
3.700000047683716       4

Setup for web browsers

Loading milsushi2.js (without WebCL support) or milsushi2_cl.js (WebCL support version) from html page is needed. Download the js file from releases page.

Unfortunately, currently a plugin is needed to enable WebCL. We tested on webcl-firefox plugin with Firefox 32. Compiled version of webcl-firefox plugin for Linux is here (Ubuntu 14.04 + CUDA 7.5, commit d87447f, License: MPL 2.0).

If WebCL is enabled, $M.initcl() should return true.

Sample page is plain page with only milsushi2_cl.js is loaded.

Basic usage of Sushi2

The function set of Sushi2 is designed to be similar to MATLAB / Octave for making new users understand how to use easily.

In the documantation, we call milsushi2 object as $M. $M can be obtained by var $M=require('milsushi2');(in node.js), var $M=milsushi2;(in web browsers).

Functions for generating and operating matrices are placed under $M object. Matrix object belongs to $M.Matrix class.

A matrix has at least 2 dimensions, and may have more than 2 dimensions. The numeric type of elements in a matrix is 32-bit floating point number (noted as ‘single’) by default. 32-bit signed integer (‘int32’), 8-bit unsigned integer (‘uint8’), boolean value (‘logical’) are also supported. The numeric type is noted as klass in the arguments in functions.

Common functions for generating a matrix:

Common functions for operating a matrix:

Since JavaScript does not support operator overload, the expression A+B is invalid. $, B) does the computation instead.

MATLAB expression Sushi2 expression Comment
A+B $, B) Element-wise addition
A-B $M.minus(A, B) Element-wise subtraction
A.*B $M.times(A, B) Element-wise multiplication
A./B $M.rdivide(A, B) Element-wise division
A*B $M.mtimes(A, B) Matrix product
-A $M.uminus(A) Inversion of sign

Most functions returns newly generated matrix instance and do not modify input matrices.

Get an element or subset from a matrix:

A.get(idx1, idx2), where A is a matrix and idx1, idx2 are scalar number, the expression returns the scalar number corresponding A(idx1, idx2). idx* can be colon object, which can be constructed by $M.colon(start, stop) function. A colon object represents a range. By using colon object, a subset of a matrix is returned instead of scalar number.


var A = $M.jsa2mat([[1,2,3],
A.get(2, 1);//4
A.get(2, $M.colon());//Matrix of [[4,5,6]]
A.get($M.colon(2, 3), 3);//Matrix of [[6],[9]]

Set an element of a matrix:

A.set(idx1, idx2, val), where A is a matrix and idx1, idx2, val are scalar number, the expression sets the value of A(idx1, idx2) as val. Similar to get operation, idx* can be colon object and val can be either scalar number and matrix.


var A = $M.jsa2mat([[1,2,3],
A.set(2, 1, 40);
// A: [[1,2,3],[40,5,6],[7,8,9]]
A.set(2, $M.colon(), $M.jsa2mat([[14, 15, 16]]));
// A: [[1,2,3],[14,15,16],[7,8,9]]
A.set($M.colon(2, 3), 3, 99);//Setting scalar number to multiple elements
// A: [[1,2,3],[14,15,99],[7,8,99]]

The way of specifying element(s) of a matrix is called indexing, and Sushi2 allows most operations supported by MATLAB, except for expanding the size of matrix.