forked from rurban/smhasher
-
Notifications
You must be signed in to change notification settings - Fork 10
/
SpeedTest.cpp
446 lines (352 loc) · 11.3 KB
/
SpeedTest.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
#include "SpeedTest.h"
#include "Random.h"
#include "vmac.h"
#include <stdio.h> // for printf
#include <memory.h> // for memset
#include <math.h> // for sqrt
#include <algorithm> // for sort, min
#include <string>
#include <unordered_map>
#include <parallel_hashmap/phmap.h>
#include <functional>
typedef std::unordered_map<std::string, int,
std::function<size_t (const std::string &key)>> std_hashmap;
typedef phmap::flat_hash_map<std::string, int,
std::function<size_t (const std::string &key)>> fast_hashmap;
//-----------------------------------------------------------------------------
// We view our timing values as a series of random variables V that has been
// contaminated with occasional outliers due to cache misses, thread
// preemption, etcetera. To filter out the outliers, we search for the largest
// subset of V such that all its values are within three standard deviations
// of the mean.
double CalcMean ( std::vector<double> & v )
{
double mean = 0;
for(int i = 0; i < (int)v.size(); i++)
{
mean += v[i];
}
mean /= double(v.size());
return mean;
}
double CalcMean ( std::vector<double> & v, int a, int b )
{
double mean = 0;
for(int i = a; i <= b; i++)
{
mean += v[i];
}
mean /= (b-a+1);
return mean;
}
double CalcStdv ( std::vector<double> & v, int a, int b )
{
double mean = CalcMean(v,a,b);
double stdv = 0;
for(int i = a; i <= b; i++)
{
double x = v[i] - mean;
stdv += x*x;
}
stdv = sqrt(stdv / (b-a+1));
return stdv;
}
double CalcStdv ( std::vector<double> & v )
{
return CalcStdv(v, 0, v.size());
}
// Return true if the largest value in v[0,len) is more than three
// standard deviations from the mean
bool ContainsOutlier ( std::vector<double> & v, size_t len )
{
double mean = 0;
for(size_t i = 0; i < len; i++)
{
mean += v[i];
}
mean /= double(len);
double stdv = 0;
for(size_t i = 0; i < len; i++)
{
double x = v[i] - mean;
stdv += x*x;
}
stdv = sqrt(stdv / double(len));
double cutoff = mean + stdv*3;
return v[len-1] > cutoff;
}
// Do a binary search to find the largest subset of v that does not contain
// outliers.
void FilterOutliers ( std::vector<double> & v )
{
std::sort(v.begin(),v.end());
size_t len = 0;
for(size_t x = 0x40000000; x; x = x >> 1 )
{
if((len | x) >= v.size()) continue;
if(!ContainsOutlier(v,len | x))
{
len |= x;
}
}
v.resize(len);
}
// Iteratively tighten the set to find a subset that does not contain
// outliers. I'm not positive this works correctly in all cases.
void FilterOutliers2 ( std::vector<double> & v )
{
std::sort(v.begin(),v.end());
int a = 0;
int b = (int)(v.size() - 1);
for(int i = 0; i < 10; i++)
{
//printf("%d %d\n",a,b);
double mean = CalcMean(v,a,b);
double stdv = CalcStdv(v,a,b);
double cutA = mean - stdv*3;
double cutB = mean + stdv*3;
while((a < b) && (v[a] < cutA)) a++;
while((b > a) && (v[b] > cutB)) b--;
}
std::vector<double> v2;
v2.insert(v2.begin(),v.begin()+a,v.begin()+b+1);
v.swap(v2);
}
//-----------------------------------------------------------------------------
// We really want the rdtsc() calls to bracket the function call as tightly
// as possible, but that's hard to do portably. We'll try and get as close as
// possible by marking the function as NEVER_INLINE (to keep the optimizer from
// moving it) and marking the timing variables as "volatile register".
NEVER_INLINE int64_t timehash ( pfHash hash, const void * key, int len, int seed )
{
volatile int64_t begin, end;
uint32_t temp[16];
begin = timer_start();
hash(key,len,seed,temp);
end = timer_end();
return end - begin;
}
//-----------------------------------------------------------------------------
// Specialized procedure for small lengths. Serialize invocations of the hash
// function, make sure they would not be computed in parallel on an out-of-order CPU.
NEVER_INLINE int64_t timehash_small ( pfHash hash, const void * key, int len, int seed )
{
const int NUM_TRIALS = 200;
volatile unsigned long long int begin, end;
uint32_t hash_temp[16] = {};
uint32_t *buf = new uint32_t[(len + 3) / 4];
memcpy(buf,key,len);
begin = timer_start();
for(int i = 0; i < NUM_TRIALS; i++) {
hash(buf,len,seed,hash_temp);
// XXX Add dependency between invocations of hash-function to prevent parallel
// evaluation of them. However this way the invocations still would not be
// fully serialized. Another option is to use lfence instruction (load-from-memory
// serialization instruction) or mfence (load-from-memory AND store-to-memory
// serialization instruction):
// __asm volatile ("lfence");
// It's hard to say which one is the most realistic and sensible approach.
seed += hash_temp[0];
buf[0] ^= hash_temp[0];
}
end = timer_end();
delete[] buf;
return (int64_t)((end - begin) / (double)NUM_TRIALS);
}
//-----------------------------------------------------------------------------
double SpeedTest ( pfHash hash, uint32_t seed, const int trials, const int blocksize, const int align )
{
Rand r(seed);
uint8_t * buf = new uint8_t[blocksize + 512];
uint64_t t1 = reinterpret_cast<uint64_t>(buf);
t1 = (t1 + 255) & UINT64_C(0xFFFFFFFFFFFFFF00);
t1 += align;
uint8_t * block = reinterpret_cast<uint8_t*>(t1);
r.rand_p(block,blocksize);
//----------
std::vector<double> times;
times.reserve(trials);
for(int itrial = 0; itrial < trials; itrial++)
{
r.rand_p(block,blocksize);
double t;
if(blocksize < 100)
{
t = (double)timehash_small(hash,block,blocksize,itrial);
}
else
{
t = (double)timehash(hash,block,blocksize,itrial);
}
if(t > 0) times.push_back(t);
}
//----------
std::sort(times.begin(),times.end());
FilterOutliers(times);
delete [] buf;
return CalcMean(times);
}
//-----------------------------------------------------------------------------
// 256k blocks seem to give the best results.
void BulkSpeedTest ( pfHash hash, uint32_t seed )
{
const int trials = 2999;
const int blocksize = 256 * 1024;
printf("Bulk speed test - %d-byte keys\n",blocksize);
double sumbpc = 0.0;
volatile double warmup_cycles = SpeedTest(hash,seed,trials,blocksize,0);
for(int align = 7; align >= 0; align--)
{
double cycles = SpeedTest(hash,seed,trials,blocksize,align);
double bestbpc = double(blocksize)/cycles;
double bestbps = (bestbpc * 3000000000.0 / 1048576.0);
printf("Alignment %2d - %6.3f bytes/cycle - %7.2f MiB/sec @ 3 ghz\n",align,bestbpc,bestbps);
sumbpc += bestbpc;
}
sumbpc = sumbpc / 8.0;
printf("Average - %6.3f bytes/cycle - %7.2f MiB/sec @ 3 ghz\n",sumbpc,(sumbpc * 3000000000.0 / 1048576.0));
fflush(NULL);
}
//-----------------------------------------------------------------------------
double TinySpeedTest ( pfHash hash, int hashsize, int keysize, uint32_t seed, bool verbose )
{
const int trials = 99999;
if(verbose) printf("Small key speed test - %4d-byte keys - ",keysize);
double cycles = SpeedTest(hash,seed,trials,keysize,0);
printf("%8.2f cycles/hash\n",cycles);
return cycles;
}
double HashMapSpeedTest ( pfHash pfhash, const int hashbits,
std::vector<std::string> words,
const int trials, bool verbose )
{
//using phmap::flat_node_hash_map;
Rand r(82762);
const uint32_t seed = r.rand_u32();
std_hashmap hashmap(words.size(), [=](const std::string &key)
{
// 256 needed for hasshe2, but only size_t used
static char out[256] = { 0 };
pfhash(key.c_str(), key.length(), seed, &out);
return *(size_t*)out;
});
fast_hashmap phashmap(words.size(), [=](const std::string &key)
{
static char out[256] = { 0 }; // 256 for hasshe2, but stripped to 64/32
pfhash(key.c_str(), key.length(), seed, &out);
return *(size_t*)out;
});
std::vector<std::string>::iterator it;
std::vector<double> times;
double t1;
printf("std::unordered_map\n");
printf("Init std HashMapTest: ");
fflush(NULL);
times.reserve(trials);
{ // hash inserts and 1% deletes
volatile int64_t begin, end;
int i = 0;
begin = timer_start();
for (it = words.begin(); it != words.end(); it++, i++) {
std::string line = *it;
hashmap[line] = 1;
if (i % 100 == 0)
hashmap.erase(line);
}
end = timer_end();
t1 = (double)(end - begin) / (double)words.size();
}
fflush(NULL);
printf("%0.3f cycles/op (%zu inserts, 1%% deletions)\n",
t1, words.size());
printf("Running std HashMapTest: ");
if (t1 > 10000.) { // e.g. multiply_shift 459271.700
printf("SKIP");
return 0.;
}
fflush(NULL);
for(int itrial = 0; itrial < trials; itrial++)
{ // hash query
volatile int64_t begin, end;
int i = 0, found = 0;
double t;
begin = timer_start();
for ( it = words.begin(); it != words.end(); it++, i++ )
{
std::string line = *it;
if (hashmap[line])
found++;
}
end = timer_end();
t = (double)(end - begin) / (double)words.size();
if(found > 0 && t > 0) times.push_back(t);
}
hashmap.clear();
std::sort(times.begin(),times.end());
FilterOutliers(times);
double mean = CalcMean(times);
double stdv = CalcStdv(times);
printf("%0.3f cycles/op", mean);
printf(" (%0.1f stdv)\n", stdv);
times.clear();
printf("\ngreg7mdp/parallel-hashmap\n");
printf("Init fast HashMapTest: ");
#ifndef NDEBUG
if ((pfhash == VHASH_32 || pfhash == VHASH_64) && !verbose)
{
printf("SKIP");
return 0.;
}
#endif
fflush(NULL);
times.reserve(trials);
{ // hash inserts and 1% deletes
volatile int64_t begin, end;
int i = 0;
begin = timer_start();
for (it = words.begin(); it != words.end(); it++, i++) {
std::string line = *it;
phashmap[line] = 1;
if (i % 100 == 0)
phashmap.erase(line);
}
end = timer_end();
t1 = (double)(end - begin) / (double)words.size();
}
fflush(NULL);
printf("%0.3f cycles/op (%zu inserts, 1%% deletions)\n",
t1, words.size());
printf("Running fast HashMapTest: ");
if (t1 > 10000.) { // e.g. multiply_shift 459271.700
printf("SKIP");
return 0.;
}
fflush(NULL);
for(int itrial = 0; itrial < trials; itrial++)
{ // hash query
volatile int64_t begin, end;
int i = 0, found = 0;
double t;
begin = timer_start();
for ( it = words.begin(); it != words.end(); it++, i++ )
{
std::string line = *it;
if (phashmap[line])
found++;
}
end = timer_end();
t = (double)(end - begin) / (double)words.size();
if(found > 0 && t > 0) times.push_back(t);
}
phashmap.clear();
fflush(NULL);
std::sort(times.begin(),times.end());
FilterOutliers(times);
double mean1 = CalcMean(times);
double stdv1 = CalcStdv(times);
printf("%0.3f cycles/op", mean1);
printf(" (%0.1f stdv) ", stdv1);
fflush(NULL);
return mean;
}
//-----------------------------------------------------------------------------