SEMICON India 2026 Concludes With Focus On Indigenous Innovation, Sovereign Computing And Semiconductor Talent Development
SEMICON India 2026 concludes with 15 collaborations, boosting indigenous semiconductor, AI, and quantum tech innovation, fostering sovereign computing and talent development.
An EY and India Semiconductor and Electronics Association (ISEA) report projected India's semiconductor market to reach USD 200 billion by 2035.
Detailed Insights:
The concluding session of SEMICON India 2026 brought together government, industry, academia, and skilling organizations to advance India's semiconductor ambitions.
The Digital India RISC-V Grand Challenge, under MeitY's Chips to Startup (C2S) Programme, awarded teams for innovative solutions using indigenous processors.
Bharat AI-SoC Challenge is supported by the UK Government, fostering advanced computing and system-on-chip design skills.
SCL DMIS is an indigenous manufacturing execution system designed for efficient management of wafer fabrication activities.
C-DAC partnered with NLC India Limited and Bharat Electronics Limited to develop indigenous high-performance computing and data center solutions.
PARAM Vidya offers a ready-to-deploy AI lab-in-a-box, while PARAM Shavak-QS provides a compact platform for quantum research and education.
Multiple partnerships were forged for semiconductor workforce development, including ATMP skilling and Digital Twin technology initiatives by NIELIT.
The EY and ISEA report highlights a roadmap for India to achieve leadership in manufacturing, advanced packaging, and innovation.
Key Concepts Involved:
RISC-V: An open-source instruction set architecture (ISA) for processor design, promoting customization and innovation.
Chips to Startup (C2S) Programme: A MeitY initiative to foster semiconductor design and manufacturing startups and talent development.
ATMP (Assembly, Testing, Marking and Packaging): The crucial final stages of semiconductor manufacturing before chips are ready for use.
Digital Twin: A virtual model designed to accurately reflect a physical object, process, or system in real-time.