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finish xorshift updating.

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This commit is contained in:
NunoSempere 2023-06-03 04:21:59 -06:00
parent eaee16f205
commit c73476e5aa
6 changed files with 47 additions and 31 deletions
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2
C/README.md
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@ -11,6 +11,8 @@ This repository contains a few implementations of a simple botec (back-of-the-en
- [ ] Add Windows/Powershell time-measuring commands
- [ ] Add CUDA?
- [x] Added results of perf. `rand_r` seems like a big chunk of it, but I'm hesitant to use lower-quality random numbers
- [x] used xorshift instead
- [ ] Use xorshift with a struct instead of a pointer? idk, could be faster for some reason?
- [x] Update repository with correct timing
- [x] Use better profiling approach to capture timing with 1M samples.
- [x] See if program can be reworded so as to use multithreading effectively, e.g., so that you see speed gains proportional to the number of threads used

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C/out/samples
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C/perf.txt
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@ -1,25 +1,26 @@
Samples: 884 of event 'cycles', Event count (approx.): 551167949
Overhead Command Shared Object Symbol
23.94% samples libc-2.31.so [.] rand_r
18.14% samples libgomp.so.1.0.0 [.] 0x000000000001d132
15.43% samples libgomp.so.1.0.0 [.] 0x000000000001d2ea
12.16% samples samples [.] mixture._omp_fn.0
4.36% samples libm-2.31.so [.] __sin_fma
3.49% samples libm-2.31.so [.] __ieee754_log_fma
3.34% samples samples [.] random_to
3.13% samples samples [.] random_uniform
2.77% samples samples [.] split_array_sum._omp_fn.0
2.01% samples samples [.] rand_float
1.65% samples libm-2.31.so [.] __logf_fma
0.88% samples libgomp.so.1.0.0 [.] 0x000000000001d2f5
0.86% samples samples [.] ur_normal
0.75% samples libm-2.31.so [.] __expf_fma
0.70% samples libgomp.so.1.0.0 [.] 0x000000000001d13d
0.69% samples libgomp.so.1.0.0 [.] 0x000000000001d139
0.57% samples libgomp.so.1.0.0 [.] 0x000000000001d2f1
0.57% samples samples [.] sample_1
0.55% samples samples [.] random_lognormal
0.50% samples [kernel.kallsyms] [k] asm_exc_page_fault
0.49% samples [kernel.kallsyms] [k] clear_page_rep
0.47% samples samples [.] random_normal
0.38% samples [kernel.kallsyms] [k] default_send_IPI_single_phys
35.32% samples samples [.] xorshift32
14.09% samples libgomp.so.1.0.0 [.] 0x000000000001d2ea
12.04% samples libgomp.so.1.0.0 [.] 0x000000000001d132
11.53% samples samples [.] mixture._omp_fn.0
4.55% samples libm-2.31.so [.] __sin_fma
4.24% samples samples [.] rand_0_to_1
3.77% samples samples [.] random_to
3.03% samples libm-2.31.so [.] __logf_fma
1.61% samples libm-2.31.so [.] __expf_fma
1.54% samples samples [.] split_array_sum._omp_fn.0
1.38% samples samples [.] random_uniform
0.94% samples samples [.] ur_normal
0.91% samples libm-2.31.so [.] __ieee754_log_fma
0.74% samples libgomp.so.1.0.0 [.] 0x000000000001d13d
0.52% samples samples [.] sample_0
0.41% samples libm-2.31.so [.] __sqrtf_finite@GLIBC_2.15
0.38% samples samples [.] sample_1
0.36% samples libgomp.so.1.0.0 [.] 0x000000000001d139
0.36% samples libgomp.so.1.0.0 [.] 0x000000000001d2f5
0.22% samples [kernel.kallsyms] [k] native_queued_spin_lock_slowpath
0.18% samples [kernel.kallsyms] [k] _raw_spin_lock_irq
0.18% samples samples [.] random_lognormal
0.17% samples libgomp.so.1.0.0 [.] 0x000000000001d2f1

11
C/samples.c
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@ -81,7 +81,9 @@ float split_array_sum(float** meta_array, int length, int divided_into)
uint32_t xorshift32(uint32_t* seed)
{
/* Algorithm "xor" from p. 4 of Marsaglia, "Xorshift RNGs" */
// Algorithm "xor" from p. 4 of Marsaglia, "Xorshift RNGs"
// See <https://stackoverflow.com/questions/53886131/how-does-xorshift32-works>
// https://en.wikipedia.org/wiki/Xorshift
uint32_t x = *seed;
x ^= x << 13;
x ^= x >> 17;
@ -93,6 +95,13 @@ uint32_t xorshift32(uint32_t* seed)
float rand_0_to_1(uint32_t* seed){
return ((float) xorshift32(seed)) / ((float) UINT32_MAX);
/*
uint32_t x = *seed;
x ^= x << 13;
x ^= x >> 17;
x ^= x << 5;
return ((float)(*seed = x))/((float) UINT32_MAX);
*/
// previously:
// ((float)rand_r(seed) / (float)RAND_MAX)
// and before that: rand, but it wasn't thread-safe.

4
README.md
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@ -33,7 +33,7 @@ The title of this repository is a pun on two meanings of "time to": "how much ti
| Language | Time | Lines of code |
|-----------------------------|-----------|---------------|
| C (optimized, 16 threads) | 6ms | 222 |
| C (optimized, 16 threads) | 5ms | 249 |
| Nim | 68ms | 84 |
| C (naïve implementation) | 292ms | 149 |
| Javascript (NodeJS) | 732ms | 69 |
@ -74,6 +74,8 @@ In fact, the C code ended up being so fast that I had to measure its time by run
And still, there are some missing optimizations, like tweaking the code to take into account cache misses. I'm not exactly sure how that would go, though.
Once the code was at 6.6ms, there was a 0.6ms gain possible by using OMP better, and a 1ms gain by using a xorshift algorithm instead of rand_r from stdlib.
Although the above paragraphs were written in the first person, the C code was written together with Jorge Sierra, who translated the algorithmic improvements from nim to it and added the initial multithreading support.
### NodeJS and Squiggle

14
time.txt
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@ -1,22 +1,24 @@
# Optimized C
$ make time-linux
$ make && make time-linux
gcc -O3 samples.c -fopenmp -lm -o out/samples
Requires /bin/time, found on GNU/Linux systems
Running 100x and taking avg time: OMP_NUM_THREADS=1 out/samples
Time using 1 thread: 24.00ms
Time using 1 thread: 20.20ms
Running 100x and taking avg time: OMP_NUM_THREADS=2 out/samples
Time using 2 threads: 21.80ms
Time using 2 threads: 17.50ms
Running 100x and taking avg time: OMP_NUM_THREADS=4 out/samples
Time for 4 threads: 24.40ms
Time for 4 threads: 17.00ms
Running 100x and taking avg time: OMP_NUM_THREADS=8 out/samples
Time using 8 threads: 10.40ms
Time using 8 threads: 8.40ms
Running 100x and taking avg time: OMP_NUM_THREADS=16 out/samples
Time using 16 threads: 6.60ms
Time using 16 threads: 5.00ms
# C