This repo contains the code that shows how optimizations of level 1 data cache access can influence matrices multiplication performance. I got some ideas from the famous article What Every Programmer Should Know About Memory.
More explanation can be found in my article How Much Access to RAM Costs.
gcc -DCLS=$(getconf LEVEL1_DCACHE_LINESIZE) -Wall -O2 mem-speed.c
./a.out
The results I got on Ubuntu 20.04 with Intel Core i7-10700K CPU and 3000 MHz DDR4 memory:
matrix_multiply:
| Matrix size | execution time |
|---|---|
| 100 | 733 |
| 300 | 21485 |
| 500 | 101610 |
| 1000 | 843546 |
| 2000 | 25787985 |
| 3000 | 107763896 |
matrix_multiply_t:
| Matrix size | execution time | % of matrix_multiply |
|---|---|---|
| 100 | 719 | 98.09% |
| 300 | 20885 | 97.21% |
| 500 | 96832 | 95.30% |
| 1000 | 788834 | 93.51% |
| 2000 | 7268999 | 28.19% |
| 3000 | 24179636 | 22.44% |
matrix_multiply_fast:
| Matrix size | execution time | % of matrix_multiply |
|---|---|---|
| 100 | 606 | 82.67% |
| 300 | 15503 | 72.16% |
| 500 | 72558 | 71.41% |
| 1000 | 600223 | 71.15% |
| 2000 | 5203588 | 20.18% |
| 3000 | 17501126 | 16.24% |
matrix_multiply_seq:
| Matrix size | execution time | % of matrix_multiply |
|---|---|---|
| 100 | 459 | 62.62% |
| 300 | 11773 | 54.80% |
| 500 | 56441 | 55.55% |
| 1000 | 480246 | 56.93% |
| 2000 | 4164429 | 16.15% |
| 3000 | 14001852 | 12.99% |