El proyecto TOFFEE
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RESEARCH 》 Introducing TrueBench - a high resolution CPU benchmarking system

TrueBench
TrueBench is an unique open-source benchmarking system in which the core system performance and efficiency parameters are measured at extreme high resolution in the order of several million/billion µ-seconds for a given specific task. TrueBench is a part of The TOFFEE Project research. With TrueBench Raspberry Pi 3, Raspberry Pi 2B, Raspberry Pi 2 and other embedded SoC devices are benchmarked and you can do a comparative analysis with standard mainstream x86 devices.

TrueBench can be used to measure specific system performance of user-space application performance in a systems software point-of-view. With this technique you can isolate multi-core CPU performance, multi-threading CPU performance and derive a precise conclusion about the CPU's true potential.

Advantages:

  • evaluate CPU's current generation versus previous generation architecture
  • multi-platform(x86 32-bit, x86_64, ARM, MIPS)
  • light-weight Linux user-space app which restricts the choice of OS for precise measurements
  • high resolution benchmarking technique
  • precise combination of instructions for over a trillion iterations per test
  • open-source - can be compiled for any Linux based hardware

Applications(use-cases):

  • building low-latency high performance networking devices
  • embedded/SoC cpu (platform) evaluation
  • server and datacenter hardware evalation
  • new product design/architecture evalation
  • scientific applications (such as HPC, Super-Computers, etc)

For more details: visit TrueBench



Suggested Topics:


Generic

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


Temas recomendados:

Streaming CDN Types ↗
Saturday' 13-Mar-2021

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

TOFFEE (and TOFFEE-DataCenter) optimized Wireless Mesh-Networks - B.A.T.M.A.N [open-mesh.org (Open Mesh)] ↗
Saturday' 13-Mar-2021
TOFFEE/TOFFEE-DataCenter can be used to optimize Ad-Hoc Mobile Wireless Mesh-Networks. To learn more about the same here are some references: B.A.T.M.A.N. - https://en.wikipedia.org/wiki/B.A.T.M.A.N. Mobile ad hoc network (MANET) - https://en.wikipedia.org/wiki/Mobile_ad_hoc_network Wireless ad hoc network (WANET) - https://en.wikipedia.org/wiki/Wireless_ad_hoc_network open-mesh.org (Open Mesh) Wiki - https://www.open-mesh.org/projects/open-mesh/wiki

Building my own CDN - Finally Completed - Update: 17-Dec-2017 ↗
Saturday' 13-Mar-2021
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-Mocha WAN Emulation software development - Update: 15-July-2016 ↗
Saturday' 13-Mar-2021
Today I completed doing all the changes which are meant for the new upcoming TOFFEE-Mocha release. I have increased the resolution and the range of all factor variables. Instead 1 to 10 range now they have a range of 1 to 30. Unlike before the value 1 means it is lot more intense (or in some cases less intense) and the uppermost value 30 means lot less intense (or in some cases lot intense).

TEST CASES :: TEST RESULTS :: Raspberry Pi WAN Emulator TOFFEE-Mocha-1.0.14-1-rpi2 ↗
Saturday' 13-Mar-2021

Watch on Youtube - [466//1] 158 VLOG - TOFFEE WAN Optimization Software Development live update - 6-Nov-2016 ↗


TOFFEE-Butterscotch a TOFFEE for Home/SOHO Internet/WAN bandwidth ↗
Saturday' 13-Mar-2021
TOFFEE-Butterscotch a TOFFEE for Home/SOHO Internet/WAN bandwidth

First TOFFEE Code Release ↗
Saturday' 13-Mar-2021
I started working on the new TOFFEE project (which is the fork of my earlier TrafficSqueezer open-source project) starting from 1st January 2016 onwards. Ever since I was busy in research and altering certain old features so that it is more minimal than TrafficSqueezer, a more focused agenda, deliver refined code and a broader vision. I have lined up more things to follow in the upcoming months. I want to focus about all aspects of WAN communication technologies not just on core WAN Optimization research and technology.

Network Packet Queue or Buffer - Packet Flow Control, Fragmentation and MTU ↗
Saturday' 13-Mar-2021
Network Packet Queue or Buffer - Packet Flow Control, Fragmentation and MTU

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



Featured Educational Video:
Watch on Youtube - [435//1] 0x1d3 Who gets Laid off (or Fired) during a recession ? #TheLinuxChannel #KiranKankipati ↗

TOFFEE (and TOFFEE-DataCenter) deployment with web-proxy cache ↗
Saturday' 13-Mar-2021
If you want to deploy TOFFEE along with a web-proxy cache (such as Squid Proxy) you can deploy the same as shown below. TOFFEE does not cache files. TOFFEE does packet level network optimization. So if you want caching your web content you can use transparent mode web-proxy cache intercepting your WAN links. A web-proxy may reduce amount of data being processed (optimized) within these TOFFEE devices and so reduce the CPU overheads and improve its performance.

Building my own CDN - Google PageSpeed Insights - Update: 22-Jul-2016 ↗
Saturday' 13-Mar-2021
Ever since after I launched my new The TOFFEE Project website on 1-May'2016, I can see there is a steep increase in traffic. Soon after the launch when I monitored its Alexa rankings it was reporting about 12 Million or so. But once it is getting more and more traffic the Alexa rankings shot up and now currently it shows around 2 Million (as on 22-July-2016). Alexa is an excellent tool to monitor your overall website global ranking and indirectly its performance. Unlike Google Analytics which is bound one or other way into Google's SEO. Alexa gives you a second opinion about your website's growth.

TOFFEE Documentation :: TOFFEE-1.1.24-3-rpi2 ↗
Saturday' 13-Mar-2021
Here is my VLOG Youtube video of the same which includes details about version release notes, future road-map and so on. The TOFFEE release is highly optimized and customized for hardware platforms such as x86-64 based Intel NUC and other Intel mobile computing platforms such as laptops and so on. This version (or release) is not suited and so not recommended to be used for high-end desktop and server hardware platform.

First TOFFEE Code Release ↗
Saturday' 13-Mar-2021
I started working on the new TOFFEE project (which is the fork of my earlier TrafficSqueezer open-source project) starting from 1st January 2016 onwards. Ever since I was busy in research and altering certain old features so that it is more minimal than TrafficSqueezer, a more focused agenda, deliver refined code and a broader vision. I have lined up more things to follow in the upcoming months. I want to focus about all aspects of WAN communication technologies not just on core WAN Optimization research and technology.




TOFFEE deployment topology guide ↗
Saturday' 13-Mar-2021
Assume you have two sites (such as Site-A and Site-B) connected via slow/critical WAN link as shown below. You can optimize this link by saving the bandwidth as well possibly improve the speed. However, the WAN speed can be optimized only if the WAN link speeds are below that of the processing latency of your TOFFEE installed hardware. Assume your WAN link is 12Mbps, and assume the maximum WAN optimization speed/capacity of Raspberry Pi is 20Mbps, then your link will get speed optimization too. And in another case, assume your WAN link is 50Mbps, then using the Raspberry Pi as WAN Optimization device will actually increase the latency (i.e slows the WAN link). But in all the cases the bandwidth savings should be the same irrespective of the WAN link speed. In other words, if you want to cut down the WAN link costs via this WAN Optimization set up, you can always get it since it reduces the overall bandwidth in almost all the cases (including encrypted and pre-compressed data).



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