A Convergence for Computing
GizmoQuest Computing Lab is an Open Source, Independent laboratory which currently empowers Decentralized Bioinformatics and AI Research, with the help of three compute servers and workstations (specifications available below) to accelerate computational simulations & intelligence modeling and bring out results much faster with GPUs. The lab has been used to author and publish a book on GPU Computing: https://tinyurl.com/GPU-Computing.
Chronologically, the book has been honoured and enlisted at the following places of academic interest:
The book has also been cited at The European Journal of Science and Technology.
Just came to know that I received my first ever citation last January🥲❤️!
— Avimanyu Bandyopadhyay ☸️ (@iAvimanyu) February 19, 2022
It has been cited on a paper about application of deep learning algorithms on GPU/CPU hardware & analysis at the European Journal of Science and Technology.
Grateful🙏!#phdlife @PhDVoice @OpenAcademics pic.twitter.com/xZjXymsv5Z
The Deep Learning Perspective For The Book
Figure:
How deep learning is a subset of machine learning and how machine
learning is a subset of artificial intelligence (AI). Photo by Avimanyu786 / CC BY-SA
Here is a look at our liquid-cooled computer in action!
This laboratory caters to the growing requirements of accelerated research with a 300 mbps internet connection and is used for a wide variety of research applications. It provides modern computational and facilities currently for all kinds of research. It especially provides support for GPU Accelerated Computing. Likewise, it remains busy 24/7.
The aim of this laboratory is to provide required Computing and Simulations facilities to creative learners, researchers and students in order to meet their requirements of the growing trends in Bioinformatics and Science.
Background
This laboratory caters to the growing requirements of accelerated research with a 300 mbps internet connection and is used for a wide variety of research applications. It provides modern computational and facilities currently for all kinds of research. It especially provides support for GPU Accelerated Computing. Likewise, it remains busy 24/7.
Description
The aim of this laboratory is to provide required Computing and Simulations facilities to creative learners, researchers and students in order to meet their requirements of the growing trends in Bioinformatics and Science.
The main emphasis is to do project work in lesser time with the use of GPUs and deep learning. Collaborative research is highly encouraged, and Decentralized Science, or DeSci, makes this very easily possible!
starting to come across a lot of speculative talk regarding a #DeSci future so I think we need to come back down to the tldr for a second: pic.twitter.com/8RE0HJ0Zjp
— talyssa (@T4LYSSA) March 28, 2022
Primary Hardware Configuration
AMD Ryzen 7 2700X Processor at 3.7 Ghz
AMD Radeon VII 16 GB HBM2 GPU (Vega 20 Architecture)
8 GB DDR4 RAM (tentative)
500 GB WD M2 SSD Blue
4 TB Western Digital HDD Red
AMD Radeon VII 16 GB HBM2 GPU (Vega 20 Architecture)
8 GB DDR4 RAM (tentative)
500 GB WD M2 SSD Blue
4 TB Western Digital HDD Red
Secondary Hardware Configuration
Intel Core i7 4770K Processor at 3.5 Ghz
Nvidia RTX 2060 12 GB GDDR6 GPU (Maxwell Architecture)
32 GB GSkill DDR3 RAM
256 GB ADATA SSD
4 TB Western Digital HDD Green
Nvidia RTX 2060 12 GB GDDR6 GPU (Maxwell Architecture)
32 GB GSkill DDR3 RAM
256 GB ADATA SSD
4 TB Western Digital HDD Green
Tertiary Hardware Configuration
AMD Athlon 3000G at 3.5 Ghz
Nvidia RTX 3060 Ti 8 GB GDDR6 GPU x3
Nvidia RTX 3090 24 GB GDDR6X GPU
32 GB Corsair DDR4 RAM
120 GB ADATA M2 SSD
Our primary goal is currently on building a platform for computational research through DeSci with NuNet. We believe in convergence, be it Science or Art! Our founding member, Avimanyu Bandyopadhyay has completed his academic research in Bioinformatics at Heritage Institute of Technology and is currently working as a Systems Scientist at NuNet.
Once NuNet's Decentralized GPU infrastructure is live, we look forward to onboarding all the above machines to contribute on the network and help build a globally decentralized computing economy for researchers!
Future Projects/Ideas on a Decentralized Network
In the field of genomics, a simple modern run of DNA sequencing can take up to 1 TB per run according to computational biologists. So a 4 TB storage would take care of such requirements. Also, as an example, the transfer rate of the Radeon VII happens to be 1 TB/s with 1:4 FP64 performance at 3.46 TFLOPS (great at the consumer level)!
This Mini Open Source Lab will be open to all diverse computational fields and not just Science. One great example would be Computational Archaeology. Such ideas could help preserve heritage sites such as the Kailash temple at Ellora!
We're very much eager to explore the field of Computational Psychiatry and Computational Psychology especially through Video Games.
32 GB Corsair DDR4 RAM
120 GB ADATA M2 SSD
Current Line of Work
Our primary goal is currently on building a platform for computational research through DeSci with NuNet. We believe in convergence, be it Science or Art! Our founding member, Avimanyu Bandyopadhyay has completed his academic research in Bioinformatics at Heritage Institute of Technology and is currently working as a Systems Scientist at NuNet.
Once NuNet's Decentralized GPU infrastructure is live, we look forward to onboarding all the above machines to contribute on the network and help build a globally decentralized computing economy for researchers!
Envisioning a cycle for a people's #DeSci:
— Avimanyu Bandyopadhyay ☸️ (@iAvimanyu) October 27, 2022
1. Solving computational problems with @nunet_global
2. Rewarding researchers for those solutions with @nano
3. Converting required ӾNO to $NTX
4. Cycle repeats#NuNet #Nano#Decentralization #Science #Computehttps://t.co/voVksuxmQy
Future Projects/Ideas on a Decentralized Network
In the field of genomics, a simple modern run of DNA sequencing can take up to 1 TB per run according to computational biologists. So a 4 TB storage would take care of such requirements. Also, as an example, the transfer rate of the Radeon VII happens to be 1 TB/s with 1:4 FP64 performance at 3.46 TFLOPS (great at the consumer level)!
This Mini Open Source Lab will be open to all diverse computational fields and not just Science. One great example would be Computational Archaeology. Such ideas could help preserve heritage sites such as the Kailash temple at Ellora!
We're very much eager to explore the field of Computational Psychiatry and Computational Psychology especially through Video Games.
The BIG 5 Domains of Play have been explored and explained many times by Jason VandenBerghe at Game Developers Conference (GDC) events.
Once our work is completed on building a Decentralized Computing Infrastructure, we look forward to exploring the above and more!
Working Hours (Includes Manual/Automated)
9:00 AM - 12:00 AM IST (Subject to Change)
Contact
avimanyu[at]gizmoquest[dot]com
