24%
15.02.2012
2
0
0
0
0
0
2
256KB < < 512KB
2
2
2
3
2
2
2
3
512KB < < 1MB
3
2
2
24%
26.01.2012
2
0
0
0
0
0
2
256KB < < 512KB
2
2
2
3
2
2
2
3
512KB < < 1MB
3
2
2
23%
12.05.2020
TAG IMAGE ID CREATED SIZE
nvidia/cuda 10.1-base-ubuntu18.04 3b55548ae91f 4 months ago 106MB
hello-world latest fce289e99eb9 16 months ago 1.84kB
Running the nvidia
23%
04.08.2020
(minified by 25.99X)
from python:2.7-alpine - 84.3MB => 23.1MB (minified by 3.65X)
from python:2.7.15 - 916MB => 27.5MB (minified by 33.29X)
from centos:7 - 647MB => 23MB (minified by 28.57X)
from centos
22%
07.06.2019
sha256:f1ca87d9adb678b180c31bf21eb9798b043c22571f419ed844bca1d103f2a2f7 bf85f2b6bf52 13 months ago 15.5MB
The output shows information on both the original nginx:alpine image and the updated
22%
29.09.2020
-line operations.
To install Dockly [3], you can choose one of two routes: with npm (see the "Installation by npm" box for that route) and in a Docker container. For context, on my laptop, about 43MB of file space
22%
30.11.2025
) DDR3-2133 (1066)
DDR4-1600 (800) to DDR4-3200 (1,600)
Prefetching
Dual prefetch (2-bit)
Quadruple prefetch (4-bit)
8x prefetch (8-bit)
8x prefetch with two
22%
18.12.2013
of the most remarkable things about this output is that only 471 bytes were written for 100 elements (compression perhaps?). This is much less than either C (1,600) or Fortran (1,608).
Next I’ll try 256
22%
16.03.2021
, (T) 4096B-4096B, ioengine=libaio, iodepth=32
fio-3.12
Starting 1 process
Jobs: 1 (f=1)
test: (groupid=0, jobs=1): err= 0: pid=5956: Sat Jan 9 16:38:53 2021
read: IOPS=256k, BW=998MiB/s (1047MB
22%
11.04.2016
(512 MB) copied, 49.1424 s, 10.4 MB/s
If you want to empty the read and write cache for benchmark purposes, you can do so using:
sync; echo 3 > /proc/sys/vm/drop_caches
Sequential access
