31%
30.01.2024
Dell Precision Workstation T7910
Power
1,300W
CPU
2x Intel Xeon Gold E5-2699 V4, 22 cores, 2.4GHz, 55MB of cache, LGA 2011-3
GPU, NPU
n/a*
Memory
31%
04.08.2020
-slim[build]: info=image id=sha256:231d40e811cd970168fb0c4770f2161aa30b9ba6fe8e68527504df69643aa145 size.bytes=126323486 size.human=126 MB
docker-slim[build]: info=image.stack index=0 name='nginx:latest' id='sha256
31%
11.05.2021
sizes (Listing 1). The second script (Listing 2) is the same as Listing 1, but uses double precision.
Listing 1: Single-Precision Square Matrix Multiply
# Example SGEMM
for N = [2, 4, 8, 16, 32, 64, 128, 256
31%
17.02.2015
Galileo
Yocto Linux, VxWorks (RTOS), Windows
Intel Quark X1000
Single 32-bit Intel Pentium (x86) @400MHz
Integrated Intel GPU
256 MB DDR3, 512KB embedded SRAM, 8
31%
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
31%
05.08.2024
catatonit conmon containernetworking-plugins crun golang-github-containers-common
golang-github-containers-image netavark passt podman
0 upgraded, 11 newly installed, 0 to remove and 0 not upgraded.
Need to get 32.3 MB of archives.
After this operation, 131 MB
31%
07.06.2019
IMAGE ID CREATED SIZE
nginx 1.15-alpine sha256:385fbcf0f04621981df6c6f1abd896101eb61a439746ee2921b26abc78f45571 315798907716 5 days ago 17.8MB
nginx alpine
31%
11.04.2016
B/s ( 2.2 Gbit/s)
128 KiB blocks: 2176.5 IO/s, 272.1 MiB/s ( 2.3 Gbit/s)
256 KiB blocks: 751.2 IO/s, 187.8 MiB/s ( 1.6 Gbit/s)
512 KiB blocks: 448.7 IO/s, 224.3 MiB/s ( 1.9 Gbit/s)
1 MiB blocks
30%
25.03.2021
, 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/s)(2045MiB/2049msec
30%
03.04.2024
on machines with only one CPU core and 512MB of RAM; the minimalist K3s setup itself only uses 250MB. As one of the radical cost-cutting measures, K3s dispenses with the I/O-intensive etcd database
