Benchmark: Difference between revisions

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On ODroid x4, the eMMC is 150MB/s.
On ODroid x4, the eMMC is 150MB/s.


On phenom server, the HDD speed is 150MB/s (WD black WD4003FZEX 4TB, 2013) and 68MB/s (ST ST3640323as 640GB, 2014).
On phenom server, Samsung SSD 860 EVO 500GB is 235 MB/s, the HDD speed is 150MB/s (WD black WD4003FZEX 4TB, 2013) and 68MB/s (ST ST3640323as 640GB, 2014).


On Raspberry Pi 3B ('''sudo apt-get install hdparm'''), the microSD speed is 22MB/s only. The same SSD plugged to a USB2 port has a speed 34MB/s only.
On Raspberry Pi 3B ('''sudo apt-get install hdparm'''), the microSD speed is 22MB/s only. The same SSD plugged to a USB2 port has a speed 34MB/s only.

Revision as of 15:30, 17 May 2020

Geekbench

Geekbench is a cross-platform benchmark that measures the performance of your computer's processor and memory.

Sysbench

sudo apt-get update
sudo apt-get install sysbench
sysbench --num-threads=1 --test=cpu --cpu-max-prime=20000 --validate run
# sysbench version is 0.4.12, Ubuntu 16.04

sysbench --threads=1 cpu --cpu-max-prime=20000 --validate run
# sysbench version 1.0.11, Ubuntu 18.04

The following one was used to benchmark Raspberry Pi 32-bit vs 64-bit. 

sysbench --threads=4 --test=cpu --cpu-max-prime=300000 run && 7za b

Two websites have a database for benchmarks.

Device Total time (1-thread) Total time (all threads) Average CPU Mark
Intel Core i7-8750H @ 2.20GHz Macbook Pro 2018 (6 cores) 12407
Xeon E5-1650 (12 threads) 23s 2.5s 11808
Intel i3-4590T (4-core) Dell Optiplex 3020M 5622
AMD Phenom II X6 1055T (6-core) 28s 5.5s 5058
Intel Core2 Quad Q9500 @2.8GHz (4-core) 3542
Intel Core2 Duo E8400 @3.0GHz (2-core) 21.5s 11.5s 2178
Intel Core i3-4010U @ 1.7GHz (4-core) 47.2s 13.4s 2437
Core(TM) i3-3110M @ 2.40GHz (4-core) 35s 10s 3049
Core(TM) i7-2640M CPU @ 2.80GHz (Lenovo T420s) 10s 10s 3933
Atom(TM) z3735G @ 1.33GHz (hp stream 8 2-core) 918
Atom(TM) z2760 @ 1.8GHz (lenovo lynx 2-core) 576
Atom(TM) N270 @ 1.60GHz (EEE PC 2-core) 192s 120s 272
RPi1 (1-core) 1412s
RPi2 (4-core) 768s 191s
RPi2 (4-core) 768s 191s
RPi0-W (1-core) 624s
BeagleBlack (1-core) 673s
UDoo (2-core) 603s 302s
UDoo X86 Advanced Celeron N3160 2.24 GHZ turbo speed (2-core) 10s 10s 1472
ODroid xu4 (8-core) 372s 60s

Note that 

watch -n1 "cat /proc/cpuinfo | grep \"MHz\""
sudo cat /sys/devices/system/cpu/*/cpufreq/cpuinfo_max_freq

Install 0.4.12 from source

For some reason, the threads option in version 1.0 does not work. See cpu test: single thread and multi-threads get the same result and Question about CPU benchmarking.

If we need to use version 0.4.12, we need to build from the source. 

sudo apt install automake autoconf libtool libmysqlclient-dev libssl1.0.0 libssl-dev make

wget http://pkgs.fedoraproject.org/repo/pkgs/sysbench/sysbench-0.4.12.tar.gz/3a6d54fdd3fe002328e4458206392b9d/sysbench-0.4.12.tar.gz
tar zxvf sysbench-0.4.12.tar.gz
cd sysbench-0.4.12/
./autogen.sh
./configure --without-mysql
sudo make # Cannot establish any listening sockets - Make sure an X server isn't already running(EE)
          # ...
          # ../libtool: line 5281: : command not found
sudo make install

Run sysbench 0.4.12 using singularity

  1. Install singularity either from pre-build binary or source (See the 'Docs' under https://sylabs.io/singularity/)
  2. Create a new sub and build a container
  3. 'Execute' the container
# step 1: the following method installed an old version (2.6.1) of singularity
#         
$ wget -O- http://neuro.debian.net/lists/bionic.us-nh.libre | sudo tee /etc/apt/sources.list.d/neurodebian.sources.list
$ sudo apt-key adv --recv-keys --keyserver hkp://pool.sks-keyservers.net:80 0xA5D32F012649A5A9
$ sudo apt update
$ sudo apt-get install singularity-container
$ singularity --version

# step 2
$ mkdir sysbench; cd sysbench
$ nano sysbench.def 
$ sudo singularity build sysbench0412 sysbench.def

# step 3
$ singularity exec sysbench0412 sysbench --num-threads=1 --test=cpu --cpu-max-prime=20000 --validate run
$ singularity exec sysbench0412 sysbench --num-threads=4 --test=cpu --cpu-max-prime=20000 --validate run

where the definition file <Singularity> (recall Ubuntu 16.04 still has the old version of sysbench) is 

$ cat sysbench.def
Bootstrap: docker
From: ubuntu:16.04

%post
    apt-get -y update
    apt-get -y install sysbench

%environment
    export LC_ALL=C
    export PATH=/usr/games:$PATH

Interestingly, the container build using singularity 2.6.1 also works on singularity 3.5.0 (compile from source).

Version 1.0.X

I find the correct way to use the utility is to specify the all threads and use the time command. 

$ time sysbench --threads=4 cpu --cpu-max-prime=20000 --validate run
sysbench 1.0.11 (using system LuaJIT 2.1.0-beta3)

Running the test with following options:
Number of threads: 4
Additional request validation enabled.

Initializing random number generator from current time


Prime numbers limit: 20000

Initializing worker threads...

Threads started!

CPU speed:
    events per second:   769.40

General statistics:
    total time:                          10.0053s
    total number of events:              7700

Latency (ms):
         min:                                  5.18
         avg:                                  5.20
         max:                                 14.56
         95th percentile:                      5.18
         sum:                              40003.22

Threads fairness:
    events (avg/stddev):           1925.0000/1.00
    execution time (avg/stddev):   10.0008/0.00


real	0m10.043s
user	0m39.992s
sys	0m0.016s

$ time sysbench --threads=1 cpu --cpu-max-prime=20000 --validate run
sysbench 1.0.11 (using system LuaJIT 2.1.0-beta3)

Running the test with following options:
Number of threads: 1
Additional request validation enabled.

Initializing random number generator from current time


Prime numbers limit: 20000

Initializing worker threads...

Threads started!

CPU speed:
    events per second:   192.45

General statistics:
    total time:                          10.0034s
    total number of events:              1927

Latency (ms):
         min:                                  5.18
         avg:                                  5.19
         max:                                 17.24
         95th percentile:                      5.18
         sum:                              10000.58

Threads fairness:
    events (avg/stddev):           1927.0000/0.00
    execution time (avg/stddev):   10.0006/0.00


real	0m10.049s
user	0m10.028s
sys	0m0.020s

nbench

wget http://www.tux.org/~mayer/linux/nbench-byte-2.2.3.tar.gz
tar xzvf nbench-byte-2.2.3.tar.gz
cd nbench-byte-2.2.3
make
./nbench

geekbench

https://www.geekbench.com/

Google: how to run geekbench on the raspberry pi

Simple C program

See Time the iterations from 0 to_2147483647

R program

Gross inefficiency in influence.lm, r-source on github

Videos

Raspberry Pi 4B vs Jetson Nano

On Ubuntu, use one of the following commands to find out the graphics card information.

  • sudo lshw -C display
  • lspci | grep -i --color 'vga\|3d\|2d'

Disk speed test

dd

Linux and Unix Test Disk I/O Performance With dd Command

  • Test write speed
$ sync; dd if=/dev/zero of=tempfile bs=1M count=1024; sync

# External storage
$ sync; dd if=/dev/zero of=/media/user/MyUSB/tempfile bs=1M count=1024; sync
  • Test read speed
$ dd if=tempfile of=/dev/null bs=1M count=1024  # do not use this

# Clear the cache
$ sudo /sbin/sysctl -w vm.drop_caches=3
$ dd if=tempfile of=/dev/null bs=1M count=1024  # consistent with 'disks' utility

hdparm

hdparm is a Linux command line utility that allows to set and view hardware parameters of hard disk drives. -t and --direct measures data transfer rate but bypassing hard drive's buffer cache memory thus reading directly from the disk. 

lsblk   # find the root "/" device

sudo hdparm -t --direct /dev/mmcblk0p1  # eg internal
sudo hdparm -t --direct /dev/mmcblk0p2  # eg sd card
sudo hdparm -t --direct /dev/sda1       # eg USB 
sudo hdparm -Tt /dev/sda
sudo hdparm -t /dev/vdb                 # Measure Hard Disk Device Read Speed
sudo hdparm -T /dev/vdb                 # Measure Hard Disk Cache Read Speed
# Reading cache will give more higher performance than reading 
# from disk because only the cached data will be used and tested.

hdparm -I /dev/sda                      # show information about disk

Example: Silicon-power 512GB ssd. The box says it can read up to 560MB/s & write up to 530MB/s. Below is a test result running on NUC Pentium Silver J5005 CPU. 

$ sudo hdparm -t --direct /dev/sdb1
[sudo] password for brb: 

/dev/sdb1:
 Timing O_DIRECT disk reads: 1068 MB in  3.01 seconds = 355.34 MB/sec

On UDOO x86, the SSD is 341.77MB/s. The eMMC speed on UDOO x86 is 130MB/s. A portable HDD has a speed 24-29MB/s.

On ODroid x4, the eMMC is 150MB/s.

On phenom server, Samsung SSD 860 EVO 500GB is 235 MB/s, the HDD speed is 150MB/s (WD black WD4003FZEX 4TB, 2013) and 68MB/s (ST ST3640323as 640GB, 2014).

On Raspberry Pi 3B (sudo apt-get install hdparm), the microSD speed is 22MB/s only. The same SSD plugged to a USB2 port has a speed 34MB/s only.

on Dell t3600 Xeon E5-1650, the HDD (WD Blue 3TB 5400 rpm) speed is 50MB/s and the external USB (WD My Book 4T) is 25MB/s (216.50 kB/s before waking up).

Website loading

# http
$ curl -s -w 'Testing Website Response Time for :%{url_effective}\n\nLookup Time:\t\t%{time_namelookup}\nConnect Time:\t\t%{time_connect}\nPre-transfer Time:\t%{time_pretransfer}\nStart-transfer Time:\t%{time_starttransfer}\n\nTotal Time:\t\t%{time_total}\n' -o /dev/null http://192.168.1.88/wiki/index.php/C

# https
$ curl -s -w 'Testing Website Response Time for :%{url_effective}\n\nLookup Time:\t\t%{time_namelookup}\nConnect Time:\t\t%{time_connect}\nAppCon Time:\t\t%{time_appconnect}\nRedirect Time:\t\t%{time_redirect}\nPre-transfer Time:\t%{time_pretransfer}\nStart-transfer Time:\t%{time_starttransfer}\n\nTotal Time:\t\t%{time_total}\n' -o /dev/null https://taichimd.us/mediawiki/index.php/C

Lookup Time:		0.004311
Connect Time:		0.010050
AppCon Time:		0.049561 (https only)
Redirect Time:		0.000000 (https only)
Pre-transfer Time:	0.049659
Start-transfer Time:	5.035105

Total Time:		5.174981

$ wget -c https://raw.githubusercontent.com/reorx/httpstat/master/httpstat.py
$ python httpstat.py https://taichimd.us/mediawiki/index.php/C
...
  DNS Lookup   TCP Connection   TLS Handshake   Server Processing   Content Transfer
[     4ms    |       8ms      |     34ms      |      31300ms      |       169ms      ]
             |                |               |                   |                  |
    namelookup:4ms            |               |                   |                  |
                        connect:12ms          |                   |                  |
                                    pretransfer:46ms              |                  |
                                                      starttransfer:31346ms          |
                                                                                 total:31515ms

ApacheBench (ab)

Network speed

  • 4.5MB/s wifi on raspberry pi 3B+ at home wifi-to-wifi, 7.3MB/s ethernet-to-wifi (tested using scp)
  • 5.3MB/s ethernet on UDOO x86 at home wifi-to-ethernet, 62MB/s ethernet-to-ethernet (scp).

SSH speed test

Linux Fu 

yes | pv | ssh user@remote_host "cat >/dev/null"
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