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Matrix multiplication normally and with transpose then dot product
var a = [
[1,2,3,4,1,2,3,4],
[5,6,7,8,5,6,8,8],
[11,12,13,14,11,12,13,14],
[15,16,17,18,15,16,17,18],
[1,2,3,4,1,2,3,4],
[5,6,7,8,5,6,8,8],
[11,12,13,14,11,12,13,14],
[15,16,17,18,15,16,17,18]
]
var b = [
[21,22,23,24,21,23,24,25],
[35,36,37,38,35,36,37,38],
[41,42,43,44,41,42,43,44],
[45,46,47,48,45,46,47,48],
[21,22,23,24,21,23,24,25],
[35,36,37,38,35,36,37,38],
[41,42,43,44,41,42,43,44],
[45,46,47,48,45,46,47,48]
]
const initialize = (rows, columns) => {
let final = []
for (let i = 0; i < rows; i++){
let temp = []
for (let j = 0; j < columns; j++){
temp.push(0)
}
final.push(temp)
}
return final
}
const dotProduct = (v1,v2) => {
let sum = 0;
for (let i = 0; i < v1.length; i++){
sum += v1[i] * v2[i]
}
return sum
}
const transpose = matrix => {
let trans = [];
for (let i = 0; i < matrix[0].length; i++){
let temp = [];
for (let j = 0; j < matrix.length; j++){
temp.push(matrix[j][i])
}
trans.push(temp)
}
return trans
}
const mult = (X,Y) => {
let initial = initialize(X.length, Y[0].length)
let YTranspose = transpose(Y)
for (let i = 0; i < X.length; i++){
for (let j = 0; j < Y.length; j++){
initial[i][j] = dotProduct(X[i], YTranspose[j])
}
}
return initial
}
function proposed_multiply(a, b) {
let aRows = a.length;
let aCols = a[0].length;
let bCols = b[0].length;
let result = new Array(aRows);
for (let r = 0; r < aRows; ++r) {
const row = new Array(bCols);
result[r] = row;
const ar = a[r];
for (let c = 0; c < bCols; ++c) {
let sum = 0.;
for (let i = 0; i < aCols; ++i) {
sum += ar[i] * b[i][c];
}
row[c] = sum;
}
}
return result;
}
//schoolbook matrix multiplication
function schoolbook_multiply(m1, m2) {
var result = [];
for (var i = 0; i < m1.length; i++) {
result[i] = [];
for (var j = 0; j < m2[0].length; j++) {
var sum = 0;
for (var k = 0; k < m1[0].length; k++) {
sum += m1[i][k] * m2[k][j];
}
result[i][j] = sum;
}
}
return result;
}
function matrixDot (A, B) {
var result = new Array(A.length).fill(0).map(row => new Array(B[0].length).fill(0));
return result.map((row, i) => {
return row.map((val, j) => {
return A[i].reduce((sum, elm, k) => sum + (elm*B[k][j]) ,0)
})
})
}
Ready to run.
Test | Ops/sec | |
---|---|---|
Plain multiply |
| ready |
Better plain multiply |
| ready |
Transpose then dot product |
| ready |
Map reduce |
| ready |
You can edit these tests or add more tests to this page by appending /edit to the URL.