VEGA Microprocessors

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Short description: Type of microprocessor developed in India
VEGA Microprocessors
VEGA Microprocessor logo
VEGA Processor logo
General Info
Designed byCentre for Development of Advanced Computing
Common manufacturer(s)
Architecture and classification
ApplicationIoT, Storage, Smart NICs, Edge Analytics, Data Analytics, Autonomous Machines, Storage, Networking
Instruction setRISC-V
History

VEGA Microprocessors (also referred to as VEGA Processors) is an initiative to develop a portfolio of microprocessors, and their hardware ecosystem, by the Centre for Development of Advanced Computing (C-DAC) in India.[1][2] The portfolio includes several indigenously-developed processors based on the RISC-V instruction set architecture (ISA).[3][4][5]

The programme was started by the Ministry of Electronics and Information Technology with the objective of designing a set of microprocessors, and developing a product line for commercial purposes, to be used as part of a "Make in India" strategy.[6]

Products

The initiative has developed the following product lines:[5]

VEGA

The initiative has developed 5 RISC-V microprocessors that run on FPGAs boards.[7] The ET1031 is a 32-bit processor, with all other processors being 64-bit.[7] Only the 32-bit variant has been physically manufactured within a THEJAS SOC.[8]

THEJAS

From the VEGA processor cores, 2 SOCs have been created running on the Digilent ARTY A7 FPGA.[7] Only the THEJAS32 has been taped-out for manufacturing for the ARIES microcontroller boards.[8]

ARIES

The ARIES microcontroller boards have been described by researchers as alternatives to Arduino Uno boards.[5][9]

As of May 2023, the ARIES v3.0 board can be purchased for "around 1,000 Rs each, or about $12".[8] It can be programmed with the Arduino IDE.[8]

References

  1. "CDAC all set to develop crucial technology indigenously". The Times of India. 30 March 2019. https://timesofindia.indiatimes.com/city/pune/cdac-all-set-to-develop-crucial-tech-indigenously/articleshow/68638592.cms. 
  2. "India to build 11 new supercomputers, with indigenous processors developed by C-DAC". The Print. 22 December 2019. https://theprint.in/science/india-to-build-11-new-supercomputers-with-indigenous-processors-developed-by-c-dac/339196/. 
  3. "India Preps RISC-V Processors". 27 January 2016. https://www.eetimes.com/india-preps-risc-v-processors/. 
  4. "DESIGN AND IMPLEMENTATION OF A RISC-V ISA-BASED IN-ORDER DUAL ISSUE SUPERSCALAR PROCESSOR". RISC-V Summit. 5 December 2018. https://riscv.org/wp-content/uploads/2018/12/16.00-Rao-TT-Design-and-Implementation-of-a-RISC-V-ISA-based-In-order-Dual-Issue-Superscalar-Processor-Libin-T.-T-S-and-Krishnakumar-Rao.pdf. 
  5. 5.0 5.1 5.2 Kaur, Roopmeet; Dash, Biswajeet; Shiney O, Jeba; Singh, Sukhpreet (19 July 2023). "Revolutionizing CanSat Technology with Vega Processors: A Comparative Study". 2023 2nd International Conference on Edge Computing and Applications (ICECAA). pp. 1276–1282. doi:10.1109/ICECAA58104.2023.10212104. ISBN 979-8-3503-4757-9. https://doi.org/10.1109/ICECAA58104.2023.10212104. Retrieved 17 January 2024. 
  6. "स्वदेशी Microprocessor Challenge - Innovate Solutions for #आत्मनिर्भर भारत". My Gov India. https://innovate.mygov.in/swadeshi-microprocessor-challenge/. 
  7. 7.0 7.1 7.2 Aufranc, Jean-Luc (4 February 2022). "India goes RISC-V with VEGA processors - CNX Software". CNX Software - Embedded Systems News (CNXSoft). https://www.cnx-software.com/2022/02/04/india-goes-risc-v-with-vega-processors/. 
  8. 8.0 8.1 8.2 8.3 Aufranc, Jean-Luc (31 May 2023). "ARIES v3.0 development board features India-made VEGA RISC-V processor - CNX Software". CNX Software - Embedded Systems News (CNXSoft). https://www.cnx-software.com/2023/05/31/aries-v3-0-development-board-features-india-made-vega-risc-v-processor/. 
  9. Sharma, Devansh; Kumar, Ashish; Dhall, Aryan; Tomar, Riya; Pundir, Vikrant Singh; Bhandari, Hemant (November 2023). "fficient Parking & Toll Management: A RFID-Enabled Approach with Vega Aries Development Board". International Journal of Innovative Science and Research Technology 8 (11): 1559–1564. https://ijisrt.com/assets/upload/files/IJISRT23NOV1691.pdf. Retrieved 17 January 2024. 

External links




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