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Computing Systems

Revitalizing enterprise system applications.



The computing systems team at TCS works on the development of cost-effective, high-performing, and fault-tolerant systems for current and future applications. This includes engineering research leading to the development of middleware frameworks for artificial intelligence/machine learning- (AI/ML-) driven applications and transactional systems. The team also works on the benchmarking of bleeding-edge hardware and software technologies to determine applications that can benefit from such frameworks.


The sub-groups active within this research area include:

  • High-performance architecture for enterprise AI/ML: This group explores ways to extract large volumes of data to speed up the building of ML models; delivers value from the ML models with the lowest latencies while serving a high throughput workload; and keeps the models updated and deployed in live production in real time

  • Special-purpose hardware and FPGA: This team keeps track of the latest hardware developments and searches for ways to enhance the performance of enterprise systems

  • Performance modeling and optimization: This group works on building highly accurate predictive performance models by considering a number of application, system, and workload characteristics, and optimizing workload configuration to enhance overall system performance by leveraging these models

  • Quantum computing: This team works on identifying algorithms and applications that are likely to benefit from quantum computing in the near future

People & Patents

  • Research team: Led by Principal Scientist Manoj Nambiar, the team comprises of Dheeraj Chahal; Mayank Mishra; Rekha Singhal; Shruti Kunde; and Sunil Puranik

  • Academic partners: Tata Institute of Fundamental Research, India

  • Patents and publications (2016 onwards): This team has been granted more than 10 patents and has had over 40 papers published at key conferences and journals

What’s your challenge?
Let’s work together to solve it.