我使用以下两个makefile来编译我的程序以进行高斯模糊处理。
g++ -Ofast -ffast-math -march=native -flto -fwhole-program -std=c++11 -fopenmp -o interpolateFloatImg interpolateFloatImg.cpp g++ -O3 -std=c++11 -fopenmp -o interpolateFloatImg interpolateFloatImg.cpp 我的两个测试环境是:
但是，第一个输出在E5上的速度是2倍，而在i7上的速度是0.5倍。
第二个输出在i7上表现较快，但在E5上则较慢。
谁能提供一些解释？
这是源代码:https://github.com/makeapp007/interpolateFloatImg
我将尽快给出更多细节。
i7上的程序将在8个线程上运行。
我不知道该程序将在E5上生成多少个线程。
====更新====
我是该项目原始作者的队友，以下是结果。
Arch-Lenovo-Y50 ~/project/ca/3/12 (git)-[master] % perf stat -d ./interpolateFloatImg lobby.bin out.bin 255 20
Kernel kernelSize : 255
Standard deviation : 20
Kernel maximum: 0.000397887
Kernel minimum: 1.22439e-21
Reading width 20265 height 8533 = 172921245
Micro seconds: 211199093
Performance counter stats for './interpolateFloatImg lobby.bin out.bin 255 20':
1423026.281358 task-clock:u (msec) # 6.516 CPUs utilized
0 context-switches:u # 0.000 K/sec
0 cpu-migrations:u # 0.000 K/sec
2,604 page-faults:u # 0.002 K/sec
4,167,572,543,807 cycles:u # 2.929 GHz (46.79%)
6,713,517,640,459 instructions:u # 1.61 insn per cycle (59.29%)
725,873,982,404 branches:u # 510.092 M/sec (57.28%)
23,468,237,735 branch-misses:u # 3.23% of all branches (56.99%)
544,480,682,764 L1-dcache-loads:u # 382.622 M/sec (37.00%)
545,000,783,842 L1-dcache-load-misses:u # 100.10% of all L1-dcache hits (31.44%)
38,696,703,292 LLC-loads:u # 27.193 M/sec (26.68%)
1,204,703,652 LLC-load-misses:u # 3.11% of all LL-cache hits (35.70%)
218.384387536 seconds time elapsed
这些是工作站的结果:
workstation:~/mossCAP3/repos/liuyh1_liujzh/12$ perf stat -d ./interpolateFloatImg ../../../lobby.bin out.bin 255 20
Kernel kernelSize : 255
Standard deviation : 20
Kernel maximum: 0.000397887
Kernel minimum: 1.22439e-21
Reading width 20265 height 8533 = 172921245
Micro seconds: 133661220
Performance counter stats for './interpolateFloatImg ../../../lobby.bin out.bin 255 20':
2035379.528531 task-clock (msec) # 14.485 CPUs utilized
7,370 context-switches # 0.004 K/sec
273 cpu-migrations # 0.000 K/sec
3,123 page-faults # 0.002 K/sec
5,272,393,071,699 cycles # 2.590 GHz [49.99%]
0 stalled-cycles-frontend # 0.00% frontend cycles idle
0 stalled-cycles-backend # 0.00% backend cycles idle
7,425,570,600,025 instructions # 1.41 insns per cycle [62.50%]
370,199,835,630 branches # 181.882 M/sec [62.50%]
47,444,417,555 branch-misses # 12.82% of all branches [62.50%]
591,137,049,749 L1-dcache-loads # 290.431 M/sec [62.51%]
545,926,505,523 L1-dcache-load-misses # 92.35% of all L1-dcache hits [62.51%]
38,725,975,976 LLC-loads # 19.026 M/sec [50.00%]
1,093,840,555 LLC-load-misses # 2.82% of all LL-cache hits [49.99%]
140.520016141 seconds time elapsed
====更新====
E5的规范:
workstation:~$ cat /proc/cpuinfo | grep name | cut -f2 -d: | uniq -c
20 Intel(R) Xeon(R) CPU E5-2650 v3 @ 2.30GHz
workstation:~$ dmesg | grep cache
[ 0.041489] Dentry cache hash table entries: 4194304 (order: 13, 33554432 bytes)
[ 0.047512] Inode-cache hash table entries: 2097152 (order: 12, 16777216 bytes)
[ 0.050088] Mount-cache hash table entries: 65536 (order: 7, 524288 bytes)
[ 0.050121] Mountpoint-cache hash table entries: 65536 (order: 7, 524288 bytes)
[ 0.558666] PCI: pci_cache_line_size set to 64 bytes
[ 0.918203] VFS: Dquot-cache hash table entries: 512 (order 0, 4096 bytes)
[ 0.948808] xhci_hcd 0000:00:14.0: cache line size of 32 is not supported
[ 1.076303] ehci-pci 0000:00:1a.0: cache line size of 32 is not supported
[ 1.089022] ehci-pci 0000:00:1d.0: cache line size of 32 is not supported
[ 1.549796] sd 4:0:0:0: [sda] Write cache: enabled, read cache: enabled, doesn't support DPO or FUA
[ 1.552711] sd 5:0:0:0: [sdb] Write cache: enabled, read cache: enabled, doesn't support DPO or FUA
[ 1.552955] sd 6:0:0:0: [sdc] Write cache: enabled, read cache: enabled, doesn't support DPO or FUA
最佳答案
您的程序具有很高的缓存未命中率。对程序有利还是不利？
545,000,783,842 L1-dcache-load-misses:u＃所有L1-dcache命中次数的100.10％
545,926,505,523 L1-dcache-load-misses＃所有L1-dcache命中率的92.35％
i7和E5中的缓存大小可能有所不同，因此这是差异的来源之一。其他是-不同的汇编代码，不同的gcc版本，不同的gcc选项。
您应该尝试查看代码内部，找到热点，分析命令处理的像素数量，以及处理顺序对于cpu和内存可能更好。重写热点(花费大部分时间的代码部分)是解决任务http://shtech.org/course/ca/projects/3/的关键。
您可以在perf/record/report模式下使用annotate探查器查找热点(如果您添加-g选项重新编译项目，会更容易):
# Profile program using cpu cycle performance counter; write profile to perf.data file
perf record ./test test_arg1 test_arg2
# Read perf.data file and report functions where time was spent
# (Do not change ./test file, or recompile it after record and before report)
perf report
# Find the hotspot in the top functions by annotation
# you may use Arrows and Enter to do "annotate" action from report; or:
perf annonate -s top_function_name
perf annonate -s top_function_name > annotate_func1.txt
我可以在具有2个核心(启用HT的4个虚拟核心)和AVX2 + FMA的移动i5-4 *(英特尔Haswell)上，以7倍的速度提高小型bin文件和277个10个参数的速度。
需要重写一些循环/循环嵌套。您应该了解CPU缓存的工作原理以及更容易使用的方法:经常错过还是不经常错过。另外，gcc可能很笨，可能无法始终检测到读取数据的模式。可能需要进行此检测才能并行处理几个像素。