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 BIOS 53 watts

Idle System (Linux Ubuntu OS) 52 watts

Casual browsing 53 watts

Youtube video playback 60 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 BIOS 90 watts

Linux kernel compilation (80%) load 150 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 BIOS 16.5 watts

Linux kernel compilation (95%) load 21-24 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) charging 44 watts

Idle System (Linux Ubuntu OS) charged 15 watts

Poweroff charging 28 watts

Poweroff charged 0.1 watts

Poweron charged suspend 0.75 watts

Linux kernel compilation (95%) load charging 90 watts

Linux kernel compilation (95%) load charged 69 watts

My Dell 15R 5537 Laptop

CPU: Intel Corei7-4500U

RAM: DDR3 PC3L 8GB

Storage: Seagate 320GB Momentus HDD

Idle System (Linux Ubuntu OS) charging 42 watts

Idle System (Linux Ubuntu OS) charged 10 watts

Poweroff charging 29 watts

Poweroff charged 0.1 watts

Poweron charged suspend 0.70 watts

Linux kernel compilation (95%) load charging 60 watts

Linux kernel compilation (95%) load charged 30 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 BIOS 24.30 watts

Casual Browsing 22.27 watts

Youtube Playback 22.45 watts

Raspberry Pi2 Device

Powered via 2Amp USB power-supply

Raspbian OS

USB mouse and USB keyboard connected

Casual browsing 2.6 - 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 mouse 2.08 - 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-in 0.58 watts

Idle device after booting 28 watts

File copy (write operation) 28.7 watts

RAID Volume scrub operation 29.5 watts

APC BX600C-IN UPS - APC Back-UPS 600 (UPS not powered-on but connected to live power socket)

Standby Charging 13.5 watts

Standby not-Charging 7.8 watts

APC BX600CI-IN UPS - APC Back-UPS 600 (UPS not powered-on but connected to live power socket)

Standby Charging 9.5 watts

Standby not-Charging 10-0.9 watts

BenQ LED Monitor 24'' GW2470HM

off plugged-in 0.00 watts

Dim 11.7 watts

LG LCD TV Monitor 23'' M237WA-PT

off plugged-in 0.8 watts

Dim 33 watts

Bright 45 watts

Samsung LCD Monitor 22'' 2243NWX

off plugged-in 0.7 watts

Dim 20 watts

Bright 33.5 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.

Suggested Topics:

Generic Home Lab Research

💎 TOFFEE-MOCHA new bootable ISO: Download

💎 TOFFEE Data-Center Big picture and Overview: Download PDF

The TOFFEE Project website is hosted on Inmotion Hosting. And so I am looking for alternate hosting provider to build my first CDN node. My plan is to make multiple sub-domains of my website such as cdn1.the-toffee-project.org, cdn2.the-toffee-project.org and point each of this corresponding subdomain(s) to various alternative web hosting servers geographically spread across the world. Sometimes choosing the same vendor for multiple CDN nodes may result multiple servers existing in the data-center. And this becomes an issue if there is some catastrophic network disaster.

A study on Deep Space Networks (DSN) ↗
Saturday' 13-Mar-2021

When you are dealing Deep Space Networks (DSN) one among the most challenging parts is the Interplanetary distances and communicating data across such vast distances. This is where we are not dealing with common Internet type traffic such as HTTP/FTP/VoIP/etc but it is completely different when it comes to DSN so far. So optimizing data in DSN becomes mandatory. For example if you think one of the Mars Rovers, they have used LZO lossless compression.

Introducing TOFFEE-DataCenter ↗
Saturday' 13-Mar-2021

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.

CDN Content Delivery Networks - Types ↗
Saturday' 13-Mar-2021

Replacing in Lab Intel Core i7 5820K Desktop PC with Intel Celeron 1037U Mini-PC ↗
Saturday' 13-Mar-2021

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.

TEST CASES :: TEST RESULTS :: TOFFEE-Mocha-1.0.32 asymmetric constant packet delay feature ↗
Saturday' 13-Mar-2021

TOFFEE-DataCenter WAN Optimization - Google Hangouts Demo and VOIP Optimization ↗
Saturday' 13-Mar-2021

TOFFEE-DataCenter screenshots on a Dual CPU - Intel(R) Xeon(R) CPU E5645 @ 2.40GHz - Dell Server ↗
Saturday' 13-Mar-2021

WAN Optimization - Animated demo of Packet Optimization in TOFFEE-DataCenter ↗
Saturday' 13-Mar-2021

Detect and Monitor Failing Harddrive in Linux - My Seagate 500GB HDD Died ↗
Saturday' 13-Mar-2021

My 500GB Seagate Barracuda 7200RPM hard-drive suddenly started making mild clicking noise. I found this happening since morning. I was suspicious that something wrong in this drive and when I opened the Linux Disks app, I can find the cause of this issue. The disk is increasingly getting read errors. Besides I can see various other parameters such as Power-On Hours, Temperature, Head flying hours, etc.

Featured Educational Video:

在YouTube上观看 - [8613//1] x254 Kernel Init Code without Kernel Module - Kernel Programming Tip #linode ↗

TOFFEE-Butterscotch Documentation :: TOFFEE-Butterscotch-1.0.11-rpi2-23-nov-2016 ↗
Saturday' 13-Mar-2021

TOFFEE-Butterscotch Documentation :: TOFFEE-Butterscotch-1.0.11-rpi2-23-nov-2016

Multi-dimensional (Multi-universe) Internet Technology - A Proposal ↗
Saturday' 13-Mar-2021

Currently what we have is a single homogeneous (sort of) WWW Internet. Which we can consider as a single-dimensional network. What I propose is that we can create complete independent multiple Internets with each Internet having its own IP-address space, Domain namespace and an authority to manage Domain names. And these networks/Internets can be entirely IPv4 only based or IPv6 only based.

A study on Deep Space Networks (DSN) ↗
Saturday' 13-Mar-2021

TOFFEE WAN Optimization software development, roadmap, live-demo - Update: 06-Nov-2016 ↗
Saturday' 13-Mar-2021

Here are some of the screenshots of the new upcoming TOFFEE WAN Optimization release and live demo.

Communication data network standards and data transfer speeds :: Chart ↗
Saturday' 13-Mar-2021

Here is a complete chart comprising popular communication data network standards and their respective transfer rates. I hope this reference chart will help network engineers and network software developers while performing networking tests and experiments, building WAN/network products, building WAN simulated networks of a specific standard and so on. This may also helps us to track technological advancements of communication data networks.

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 [CDN]

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

💎 TOFFEE-MOCHA new bootable ISO:	Download

💎 TOFFEE Data-Center Big picture and Overview:	Download PDF