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RESEARCH 》 Power consumption of my Home Lab devices for research

AMD RYZEN 3 1200 - FreeNAS Storage array build
  • CPU: AMD Ryzen 3 1200 (4 cores/4 threads)
  • RAM: Corsair Vengeance 8GB DDR4 LPX 2400MHz C16 Kit
  • Motherboard: Gigabyte GA-A320M-HD2 AM44
  • Graphics/Display: Asus Geforce 210GT 1GB DDR3
  • PSU: Circle CPH698V12-400
  • Storage: WDC WD10JPVX-75JC3T0 - WD 1TB HDD
System BIOS53 watts
Idle System (Linux Ubuntu OS)52 watts
Casual browsing53 watts
Youtube video playback60 watts
Kernel compilation with 4-threads "make -j4" (99% load)74 watts
Kernel compilation with 3-threads "make -j3" (80% load)71 watts

My Intel Core i7-5820K - Desktop build
  • CPU: Intel Core i7-5820K (6 cores/12 threads)
  • RAM: Corsair PC2800 DDR4 14GB Kit
  • Motherboard: Gigabyte X99-UD4
  • Graphics/Display: Asus Geforce 210GT 1GB DDR3
  • PSU: Corsair VS450
  • CPU Liquid Cooling system: Cooler Master Nepton 240m
  • Storage: Transcend TS128GSSD370 128GB SSD
Idle System (Linux Ubuntu OS)70 watts
System BIOS90 watts
Linux kernel compilation (80%) load150 watts

My Intel Celeron CPU 1037U Mini PC WAN Optimization Device
  • CPU: Intel Celeron CPU 1037U
  • RAM: DDR3 PC3L 4GB
  • Storage: Transcend TS128GSSD370 128GB SSD
Idle System (Linux Ubuntu OS)18-20 watts
System BIOS16.5 watts
Linux kernel compilation (95%) load21-24 watts

My HP Envy 15-J111TX Laptop
  • CPU: Intel Corei7-4700MQ
  • RAM: DDR3 PC3L 12GB
  • Storage: WD Blue 250GB Scorpio HDD
Idle System (Linux Ubuntu OS) charging44 watts
Idle System (Linux Ubuntu OS) charged15 watts
Poweroff charging28 watts
Poweroff charged0.1 watts
Poweron charged suspend0.75 watts
Linux kernel compilation (95%) load charging90 watts
Linux kernel compilation (95%) load charged69 watts

My Dell 15R 5537 Laptop
  • CPU: Intel Corei7-4500U
  • RAM: DDR3 PC3L 8GB
  • Storage: Seagate 320GB Momentus HDD
Idle System (Linux Ubuntu OS) charging42 watts
Idle System (Linux Ubuntu OS) charged10 watts
Poweroff charging29 watts
Poweroff charged0.1 watts
Poweron charged suspend0.70 watts
Linux kernel compilation (95%) load charging60 watts
Linux kernel compilation (95%) load charged30 watts

My Acer Aspire 4810T Laptop
  • CPU: Intel Core Solo SU3500 1.4 GHz
  • RAM: DDR3 PC3 4GB
  • Storage: WD Blue 250GB Scorpio HDD
  * No Battery, so no charging.
Idle System (Linux Manjaro OS)16.23 watts
System BIOS24.30 watts
Casual Browsing22.27 watts
Youtube Playback22.45 watts

Raspberry Pi2 Device
  • Powered via 2Amp USB power-supply
  • Raspbian OS
  • USB mouse and USB keyboard connected
Casual browsing2.6 - 3 watts
Youtube video playback (25% load)3 - 3.5 watts
Kernel compilation with 4-threads "make -j4" (99% load)3.9 - 4 watts
Kernel compilation with 3-threads "make -j3"3.67 - 3.75 watts
idle device with no keyboard and no mouse2.08 - 2.1 watts

NETGEAR RN104 ReadyNAS
  • 2x 2.5'' Laptop HDD drives
  • 2x 3.5'' Desktop HDD drives
  • Single x-RAID volume with 4 HDD drives
Device off but plugged-in0.58 watts
Idle device after booting28 watts
File copy (write operation)28.7 watts
RAID Volume scrub operation29.5 watts

APC BX600C-IN UPS - APC Back-UPS 600(UPS not powered-on but connected to live power socket)
Standby Charging13.5 watts
Standby not-Charging7.8 watts

APC BX600CI-IN UPS - APC Back-UPS 600(UPS not powered-on but connected to live power socket)
Standby Charging9.5 watts
Standby not-Charging10-0.9 watts

BenQ LED Monitor 24'' GW2470HM
off plugged-in0.00 watts
Dim11.7 watts

LG LCD TV Monitor 23'' M237WA-PT
off plugged-in0.8 watts
Dim33 watts
Bright45 watts

Samsung LCD Monitor 22'' 2243NWX
off plugged-in0.7 watts
Dim20 watts
Bright33.5 watts

Power consumption of my Home Lab devices for research

Here is my power-consumption measurements of various devices deployed within my home lab. I measured via my kill-a-watt sort of power-meter which is fairly reliable and accurate. I checked its accuracy with various standard load such as Philips LED laps and other constant power-consuming devices to make sure that the power-meter is precise.

So far I maintained this data in my personal Google drive spreadsheet documents. But now I thought perhaps its good to share these numbers so that it is useful for various users to access their equipment such as:

  • decide UPS and battery backup ratings
  • off-grid solar power installations
  • choose new upgraded hardware which consumes less power and deliver better performance such as SSD over traditional HDD, new CPU, new Monitor, new laptop, servers, desktops and so on. And discard obsolete old hardware.
  • choosing the right PSU (power supply unit) for your desktop PC build

Before posting this article I shot a VLOG regarding the same and posted in my Youtube channel The Linux Channel. You can kindly watch the same:

Explore my lab's historical month wise power-usage trends: I started logging my entire lab monthly power-consumption readings. You can read the article HERE.

Off-Grid Solar Power System for Raspberry Pi: When you choose to use your Raspberry Pi device as your IoT based remote weather station or if you are building Linux kernel (like kernel compilation) within the same, you need a good uninterrupted power source (UPS). But if you are using it on site or in some research camping location you can choose to power your Raspberry Pi device with your custom off-grid solar power source. Kindly read my complete article about the same HERE.
Off-Grid Solar Power System for Raspberry Pi



Suggested Topics:


Generic Home Lab Research

💎 TOFFEE-MOCHA new bootable ISO: Download
💎 TOFFEE Data-Center Big picture and Overview: Download PDF


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TOFFEE-DataCenter Live Demo with Clash of Clans game data - 30-Aug-2016 ↗
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Today I have done a test setup so that I can able to connect my Android Samsung Tab via TOFFEE DataCenter. Below is my complete test topology of my setup. For demo (and research/development) context I configured TOFFEE DataCenter in engineering debug mode. So that I do not need two devices for this purpose.

Setting up a WAN Emulator within VirtualBox ↗
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Replacing in Lab Intel Core i7 5820K Desktop PC with Intel Celeron 1037U Mini-PC ↗
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As a research experiment I replaced my Intel Core i7 5820K desktop PC with my Intel Celeron 1037U Mini-PC as my everyday desktop system. This is an attempt to reduce my overall monthly power consumption. As well an attempt to do feasibility tests and research to know how far Mini PC will dominate the market in future and to study the real potential of Mini PCs.

Introducing TOFFEE-DataCenter ↗
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TOFFEE TOFFEE Data-Center is specifically meant for Data Center, Cluster Computing, HPC applications. TOFFEE is built in Linux Kernel core. This makes it inflexible to adapt according to the hardware configuration. It does sequential packet processing and does not scale up well in large multi-core CPU based systems (such as Intel Xeon servers, Core i7 Extreme Desktop systems,etc). Apart from this since it is kernel based, if there is an issue in kernel, it may crash entire system. This becomes a challenge for any carrier grade equipment (CGE) hardware build.



Setting up a WAN Emulator within VirtualBox ↗
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WAN Optimization Network Stack Architecture - Linux Kernel vs Intel DPDK vs Custom Packet Forward ↗
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Building my own CDN - Finally Completed - Update: 17-Dec-2017 ↗
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Today I finally completed building my own private CDN. As I discussed so far in my earlier topics (Building my own CDN), I want to custom build the same step-by-step from scratch. And I don't want to for now use/buy third-party CDN subscriptions from Akamai, CloudFlare, Limelight, etc as I discussed earlier.

TOFFEE (and TOFFEE-DataCenter) optimized Satellite (inflight/marine/defense) ISP Networks ↗
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TOFFEE Optimized Satellite ISP Network: TOFFEE/TOFFEE-DataCenter can be used to optimize Satellite Networks (Satellite based Internet Networks, VoIP, Data, private leased-links) as shown. Ground station transponders can be connected via array of TOFFEE Devices and in the remote CPE can have dedicated or inbuilt TOFFEE with which you can establish a WAN Optimized Satellite Network Tunnel as shown.



Featured Educational Video:
在YouTube上观看 - [943//1] x23e TrueNAS ZFS Pool Resilver over and over again issue | ZFS NAS Storage | Forever Resilver ↗

TOFFEE-DataCenter Live Demo with Clash of Clans game data - 30-Aug-2016 ↗
Saturday' 13-Mar-2021
Today I have done a test setup so that I can able to connect my Android Samsung Tab via TOFFEE DataCenter. Below is my complete test topology of my setup. For demo (and research/development) context I configured TOFFEE DataCenter in engineering debug mode. So that I do not need two devices for this purpose.

Benchmark Raspberry Pi and other embedded SoC with TrueBench ↗
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TOFFEE-DataCenter a TOFFEE variant for Data Center applications ↗
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Setting up a WAN Emulator within VirtualBox ↗
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TOFFEE-Mocha Documentation :: TOFFEE-Mocha-1.0.18-1-x86_64 ↗
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Research :: Optimization of network data (WAN Optimization) at various levels:
Network File level network data WAN Optimization


Learn Linux Systems Software and Kernel Programming:
Linux, Kernel, Networking and Systems-Software online classes [CDN]


Hardware Compression and Decompression Accelerator Cards:
TOFFEE Architecture with Compression and Decompression Accelerator Card


TOFFEE-DataCenter on a Dell Server - Intel Xeon E5645 CPU:
TOFFEE-DataCenter screenshots on a Dual CPU - Intel(R) Xeon(R) CPU E5645 @ 2.40GHz - Dell Server