feat(directConvolution): add optional output argument

Allows to reuse an output array to do many convolutions of the same
size.

Author: targos

README.md

@@ -31,49 +31,41 @@ Current results suggest that from a kernel size of 512, fft convolution should b
 
 | Data x Kernel | fft [ops/s] | direct [ops/s] |
 | ------------- | --- | ------ |
-| 128 x 4 | 17625 | 729087 |
 | 128 x 16 | 17640 | 256329 |
 | 128 x 32 | 17590 | 138211 |
 | 128 x 128 | 17295 | 35486 |
 | 128 x 512 | 4515 | 9308 |
 | 128 x 1024 | 2157 | 4695 |
-| 512 x 4 | 4539 | 191679 |
 | 512 x 16 | 4527 | 66017 |
 | 512 x 32 | 4556 | 35356 |
 | 512 x 128 | 3848 | 8134 |
 | 512 x 512 | 3217 | 2311 |
 | 512 x 1024 | 2079 | 1072 |
-| 2048 x 4 | 703 | 39038 |
 | 2048 x 16 | 681 | 15864 |
 | 2048 x 32 | 977 | 8749 |
 | 2048 x 128 | 1098 | 2164 |
 | 2048 x 512 | 1089 | 591 |
 | 2048 x 1024 | 1088 | 298 |
-| 4096 x 4 | 507 | 23076 |
 | 4096 x 16 | 473 | 8082 |
 | 4096 x 32 | 404 | 4272 |
 | 4096 x 128 | 489 | 1128 |
 | 4096 x 512 | 510 | 296 |
 | 4096 x 1024 | 506 | 149 |
-| 16384 x 4 | 81 | 6190 |
 | 16384 x 16 | 80 | 2112 |
 | 16384 x 32 | 72 | 1107 |
 | 16384 x 128 | 78 | 282 |
 | 16384 x 512 | 79 | 74 |
 | 16384 x 1024 | 77 | 37 |
-| 65536 x 4 | 18 | 1257 |
 | 65536 x 16 | 18 | 491 |
 | 65536 x 32 | 18 | 270 |
 | 65536 x 128 | 18 | 70 |
 | 65536 x 512 | 17 | 18 |
 | 65536 x 1024 | 19 | 9 |
-| 262144 x 4 | 3 | 327 |
 | 262144 x 16 | 4 | 125 |
 | 262144 x 32 | 4 | 67 |
 | 262144 x 128 | 4 | 17 |
 | 262144 x 512 | 4 | 5 |
 | 262144 x 1024 | 4 | 2 |
-| 1048576 x 4 | 1 | 62 |
 | 1048576 x 16 | 1 | 31 |
 | 1048576 x 32 | 1 | 15 |
 | 1048576 x 128 | 1 | 4 |

benchmark/convolution.js

@@ -7,7 +7,7 @@ const {
 
 const tests = {
     data: [128, 512, 2048, 4096, 16384, 65536, 262144, 1048576],
-    kernel: [4, 16, 32, 128, 512, 1024]
+    kernel: [16, 32, 128, 512, 1024]
 };
 
 function test(dataLength, kernelLength) {

src/__tests__/directConvolution.js

@@ -11,4 +11,11 @@ describe('direct convolution', () => {
         expect(directConvolution([0, 1, 2, 3], [1, 1, 1])).toEqual([0, 1, 3, 6, 5, 3]);
         expect(directConvolution([0, 1, 2, 3], [-1, 1, -1])).toEqual([0, -1, -1, -2, 1, -3]);
     });
+
+    it('with existing output array', () => {
+        const output = new Array(6);
+        const result = directConvolution([0, 1, 2, 3], [-1, 1, -1], output);
+        expect(result).toBe(output);
+        expect(output).toEqual([0, -1, -1, -2, 1, -3]);
+    });
 });

src/directConvolution.js

@@ -1,11 +1,19 @@
-export default function directConvolution(input, kernel) {
-    const length = input.length + kernel.length - 1;
-    const output = new Array(length);
-    output.fill(0);
+export default function directConvolution(input, kernel, output) {
+    if (output === undefined) {
+        const length = input.length + kernel.length - 1;
+        output = new Array(length);
+    }
+    fill(output);
     for (var i = 0; i < input.length; i++) {
         for (var j = 0; j < kernel.length; j++) {
             output[i + j] += input[i] * kernel[j];
         }
     }
     return output;
 }
+
+function fill(array) {
+    for (var i = 0; i < array.length; i++) {
+        array[i] = 0;
+    }
+}