28%
24.02.2022
.255.255.255 broadcast 0.0.0.0
inet6 fe80::bfd3:1a4b:f76b:872a prefixlen 64 scopeid 0x20
ether 42:01:0a:80:00:02 txqueuelen 1000 (Ethernet)
RX packets 11919 bytes 61663030 (58.8 Mi
28%
07.04.2022
,BROADCAST,RUNNING,MULTICAST> mtu 1460
inet 10.0.0.2 netmask 255.255.255.255 broadcast 0.0.0.0
inet6 fe80::bfd3:1a4b:f76b:872a prefixlen 64 scopeid 0x20
ether 42:01:0a:80:00:02 txqueuelen 1000
28%
16.05.2013
x86_64 6:3.4.3-1.el6 epel 9.1 M
Installing for dependencies:
GraphicsMagick x86_64 1.3.17-1.el6 epel 2.2 M
GraphicsMagick-c++ x
28%
25.09.2023
3.0 (OTG and flash support)
Video
Micro-HDMI
Power
5V, USB or 2.1mm barrel connector
Other
2 CSIs, 1 DSI
I2C, UART, SPI, ADC, PWM, GPIO
28%
06.10.2022
([hostPort:]containerPort)
ubuntu1804 1 weaveworks/ignite-ubuntu:18.04 weaveworks/ignite-kernel:5.13.3 2 2G 20G 22,38080,52812,58080
centos8 1 weaveworks/ignite-centos:8 weaveworks/ignite-kernel:5.13.3 2 2G
28%
28.11.2022
: 42 Celsius
federico@voronoi:~$
Infos
Sound-proofing a Picocluster: https://twitter.com/0xF2/status/1244422315011645444
Noctua NF-A6x25 PWM, Premium Quiet Fan, 4-Pin (60mm): https
28%
01.06.2024
is 20x because only 95 percent of the algorithm can execute in parallel (compute the fraction 1/20 from that 5% number). That limitation led to a search for embarrassingly parallel
algorithms
28%
02.08.2021
%util
sda 10.91 6.97 768.20 584.64 4.87 18.20 30.85 72.31 13.16 20.40 0.26 70.44 83.89 1.97 3.52
nvme0n1 58.80 12.22 17720.47 48.71 230
28%
26.01.2025
version isn't even 3.x. I haven't tested the code with Keras 3.x yet, so your mileage may vary if you go that route.
CIFAR-10
The model and dataset I use is CIFAR-10 [6]. It is a very common dataset
27%
03.12.2024
.9.0. The TensorFlow version is a bit old; 2.16.1 is the latest as of this writing, but I already had it installed. My Keras is also a bit old. I think Keras 3.6 is the latest, and my version isn't even 3.x. I haven
