The specs summarize utilities for computer instance
Project description
hardwareSummary
Extracting and Fetching all system and hardware information such as os details, CPU and GPU information, disk and network usage in Python using platform, psutil and gputil libraries.
install and use with pip
pip install nodespecs
python -m specs
python -c "import specs; specs.bench_cpu()"
python -c "import specs; specs.info_gpu()"
# for the machine not compatible with psutil
python -m specs -l=1
python -m specs -u="bcpu"
python -m specs -u="upload"
## server
python -c "import specs; specs.whoish()"
python -c "import specs; specs.server()"
## client upload wt progress bar
python -c "import specs; specs.client('172.25.1.175', 12345,'./README.md',False)"
## client upload wo progress bar
python -c "import specs; specs.client('172.25.1.175', 12345,'./README.md',False)"
sudo apt update
sudo apt install python3-pip
python3 -m pip install nodespecs && python3 -m specs
import specs
specs.info_gpu()
specs.bench_cpu()
Deprecated (install and use with git)
!git clone https://github.com/jinsanity07git/hardwareSummary && python hardwareSummary/hardware.py && python hardwareSummary/cpu-benchmark.py
git clone https://github.com/jinsanity07git/hardwareSummary && python hardwareSummary/hardware.py && python hardwareSummary/cpu-benchmark.py
sudo apt upgrade
sudo apt install python3-pip
git clone https://github.com/jinsanity07git/hardwareSummary && python3 hardwareSummary/hardware.py && python3 hardwareSummary/cpu-benchmark.py
CPU collection
Nickname | CPU | Arch | OS | Benchmarking | Comb | Score |
---|---|---|---|---|---|---|
TC14 | 13th Gen Intel(R) Core(TM) i9-13900K | AMD64 | Windows 10 | 12.991 | Core-i9-13900K | 38.76 |
TC17 TC16 |
Intel(R) Core(TM) i9-14900KF | AMD64 | Windows | 15.654 | Core-i9-14900KF | 39.25 |
iPhone 14 Pro Max iPhone15,3[^3] |
Apple A16 Bionic[^2] | arm64e | Darwin 23.4.0 | 15.962 | ||
TC19 | Intel(R) Core(TM) i7-9700K CPU @ 3.60GHz | sAMD64 | Windows 10 | 20.534 | Core-i7-9700K | 9.45 |
Dell Precision 3561 | 11th Gen Intel(R) Core(TM) i7-11800H @ 2.30GHz | AMD64 | Windows | 23.852 | Core-i7-11800H | 13.47 |
github codespaces | AMD EPYC 7763 64-Core Processor | x86_64 | Linux | 24.259 | EPYC-7763 | 54.65 |
TC07 | Intel(R) Core(TM) i7-9700K CPU @ 3.60GHz | AMD64 | Windows | 26.723 | Core-i7-9700K | 9.45 |
oracle cloudshell | ARM Cortex-A53 | aarch64 | Linux | 27.489 | ||
AWS t2.micro |
Intel(R) Xeon(R) CPU E5-2676 v3 @ 2.40GHz | x86_64 | Linux | 27.785 | Core-i7-9700K | 8.81 |
google cloudshell | Intel(R) Xeon(R) CPU @ 2.20GHz | x86_64 | Linux | 29.818 | ||
WUYING: 8 vCPU / 16 GiB Linux | Intel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz | x86_64 | Linux | 33.572 | Xeon-Platinum-8163 | |
TC03 TC11 |
Intel(R) Xeon(R) Gold 6248R CPU @ 3.00GHz | AMD64 | Window | 34.612 | Xeon-Gold-6248R | 23.26 |
2018 Macbook pro | Intel(R) Core(TM) i7-8559U CPU @ 2.70GHz | x86_64 | Darwin 22.1.0 | 37.105 | Core-i7-8559U | 5.38 |
JVM | Intel(R) Xeon(R) Gold 6126 CPU @ 2.60GHz | x86_64 | Linux | 38.685 | Xeon-Gold-6126 | 12.21 |
TC01 | Intel(R) Xeon(R) CPU E5-2643 v4 @ 3.40GHz | AMD64 | Windows | 39.258 | Xeon-E5-2643-v4 | 7.62 |
Jquant | Intel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz | x86_64 | Linux | 40.128 | Xeon-Platinum-8163 | |
google colab free tier | Intel(R) Xeon(R) CPU @ 2.20GHz | x86_64 | Linux | 43.078 | ||
aws cloudshell | Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz | x86_64 | Linux | 49.396 | ||
JVM | Intel(R) Xeon(R) Gold 6126 CPU @ 2.60GHz | AMD64 | Windows | 62.969 | ||
binder-examples/conda[^4] | Intel(R) Xeon(R) Gold 6140 CPU @ 2.30GHz | x86_64 | Linux | 74.349 | Xeon-Gold-6140 | 15.8 |
serv00-FreeBSD | Intel(R) Xeon(R) Silver 4214R CPU @ 2.40GHz | AMD64 | Linux | 75.571 | ||
Oracle 1G-1G-0.5Gbps | AMD EPYC 7551 32-Core Processor | x86_64 | Linux | 98.732 | EPYC-7551 | 14.67 |
mini PC | Intel(R) Atom(TM) x5-Z8350 CPU @ 1.44GHz | x86_64 | Linux | 135.107 | Atom-x5-Z8350 | 0.57 |
- Note
- Kinds of Arch explanation[^1]
GPU collection
id | name | total memory | Synthetic benchmark | CUDA API |
---|---|---|---|---|
17 | NVIDIA GeForce RTX 4060 | 8188.0MB | 50.69 | NA |
colab | Tesla T4 | 15360.0MB | 28.16 | 70627 |
dell | NVIDIA T600 Laptop GPU | 4096.0MB | 16.69 | 26600 |
01 | Quadro M4000 | 8192.0MB | 17.27 | 16648 |
Feature in develop
- work through ws, transfer file using
websocket
- py-ios-device python based Apple instruments protocol,you can get CPU, Memory and
- Streaming upload server in Python extended from uploadserver.other metrics from real iOS devices
Performance source
- https://browser.geekbench.com/ *
- https://technical.city/en/video/GeForce-RTX-4060-vs-Tesla-T4
- https://technical.city/en/video/Tesla-T4-vs-T600
[^1]: mainstream CPU architecture [^2]: Apple A16 [^3]: apple ios devices name
[^4]: binder: Get your own copy of this repository
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