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8 8888          8 8888 ,8 8888       `8. 8 8888         Y88888o.       8       8 8888       8 8888     `88   8 8888   `8.`8888.  ,8'   
8 8888          8 8888 88 8888           8 8888         .`Y888888o.    8       8 8888       8 8888     ,88   8 8888    `8.`8888.,8'    
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root

44k

226 GiB

IO%

Used: 39%

88.8 GiB

Free: 61%

137 GiB

Swap

Used: 48%

2.37 GiB

Free: 52%

2.56 GiB

Media2

IO%

Used: 48%

2.67 GiB

Free: 52%

2.56 GiB

Status:

Sleeping

Elapsed:

00:01:23

IO/R:

20.2 kiB

IO/W:

4.00 kiB

Memory: 0.0%

..........

::::::

4.68 MiB

CMD

./bin/eigentrix

Download

1.30 Kib/s

Tops:

Total:

346 Bytes/s

Tops:

Total:

(10.4 Kibps)

(152 Mibps)

896 GiB

(2.70 Kibps)

(1.59 Mibps)

486 GiB

Upload

Pid:

1186798

999834

474394

3144881

1639

1211129

1186800

3145432

1186781

3145189

1210131

7378

1000249

7266

3145058

2123456

7654321

9876543

4567890

8765432

6543210

5432109

Program:

mpv

node

python3

firefox

Xorg

tracker-extract

java

Web Content

python3

Web Content

btop

compiz

node

terminator

Web Content

chrome

vlc

emacs

gedit

htop

bash

nano

Command:

mpv --geometry=1462

/home/gnm/.vscode-s

python3 /home/gnm/b

/usr/lib/firefox/fi

/usr/lib/xorg/Xorg

/usr/libexec/tracke

java -Dswing.default

/usr/lib/firefox/fi

/usr/bin/python3 /h

/usr/lib/firefox/fi

./bin/btop

compiz

/home/gnm/.vscode-s

/usr/bin/python3 /u

/usr/lib/firefox/fi

/usr/lib/chrome/ch

vlc /media/videos

emacs /usr/share

gedit /tmp/docs

htop

/bin/bash

nano /etc/hosts

Thread:

15

12

3

140

2

16

64

27

4

30

3

4

15

4

27

50

60

32

22

18

55

99

User:

gnm

gnm

gnm

gnm

root

gnm

gnm

gnm

gnm

gnm

gnm

gnm

gnm

gnm

gnm

guest

admin

testuser

root

user123

developer

system

MemB:

547M

308M

796M

757M

79M

41M

621M

206M

76M

314M

5M

114M

585M

56M

234M

129M

87M

343M

220M

432M

300M

98M

Cpu%:

......19.0

......18.5

......0.5

......1.0

......2.5

......0.5

......0.5

......0.5

......0.0

......1.0

......0.0

......5.5

......5.5

......0.5

......0.5

......2.0

......4.0

......3.0

......6.0

......1.5

......8.5

......7.0

eigentrix@dev:root/home/aboutus$ls

Predict GPU failure with 95% accuracy at least four days before they occur

  • Monitor GPU performance trends and anomalies to gain early insights into potential risks before they escalate
  • Leverage data trends to make informed decisions about system performance and manage hardware lifecycles more effectively
  • Detect early warning signs to better manage GPU health, optimizing usage and potentially extending its lifespan

Expand the lifespan of the GPU card by up to 20% by helping manage the way it deals with the load

  • Adjust GPU workload distribution dynamically to prevent overloading, ensuring balanced usage and reducing wear on components
  • Implement strategies to regulate temperature fluctuations, preventing overheating and prolonging the GPU's overall health
  • Identify periods of excessive resource consumption and adjust performance settings, preventing unnecessary strain and enhancing long-term durability

Optimise load management to improve task completion time by an average of 25%

  • Adjust the distribution of workloads based on task priority and complexity, ensuring critical tasks are completed faster while maintaining efficiency
  • Fine-tune resource usage to allocate the right amount of processing power for each task, reducing bottlenecks and improving overall performance
  • Continuously monitor and adjust workloads in real-time, ensuring optimal distribution across available resources and reducing idle times for quicker task completion

╔════════════════════════════════════════════════════════════════════════════════════════╗
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║    ██████   ████████   ██████   ██████   ██████   ██████   ██████   ██████   ██████    ║
╠════════════════════════════════════════════════════════════════════════════════════════╣
║       ❄️❄️❄️  ██████████████████████████████ GPU █████████████████████████████  ❄️❄️❄️       ║
╠════════════════════════════════════════════════════════════════════════════════════════╣
║      ⚡██████████████████████████████████████████████████████████████████████████⚡      ║
╚════════════════════════════════════════════════════════════════════════════════════════╝

                                                                                                                                                               
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Email us at [email protected]