Projects and Programs

Our programs are organized into four broad categories.

Computer Architecture -- Machine Learning & Data Analytics -- Network Systems -- Secure Systems

Computer Architecture and Systems

Shakti Processors

RISC-V based open source processor family

The project will develop a complete reference SoC for each family which will serve as an exemplar for that category of processor. While the cores and most of the SoC components (including bus and interconnect fabrics) will be in open source, some standard components like PCIe controller, DDR controller and PHY IP will be proprietary 3rd part IP. All source will be licensed using a 3 part BSD license and will be royalty and patent free (as far as IIT-Madras is concerned, we will not assert any patents).

Coordinators: Prof. V. Kamakoti, G S Madhusudan
Students: Neel Gala, Arjun Menon
Project Staff: Rahul Bodduna

Lightstor Storage System

LightStor aims to build a comprehensive Storage and Backup system with unlimited size and bandwidth scalability using a RapidIO fabric. While other routable fabrics like Infiniband or quasi-fabrics like PCIe can be used, LightStor benefits are best demonstrated when RapidIO is used.

Coordinators: Prof. V. Kamakoti, G S Madhusudan
Students: Gopinathan, Vishvesh

Machine Learning and Data Analytics

Network Analytics on Spark

One of the common theme underlying much of the work in the group is that of network analytics. In diverse areas such as transportation and systems biology the data is typically associated with a network of interacting entities. Analyzing the effects on a node in isolation is often not fructuous and we need to look at the network of entities as a whole. This leads to additional challenges in map-reduce style parallelism. We look to leverage the availability of several graph abstractions on Spark, such as Graphx and pregel, in order to develop efficient libraries for several common and specialized network related tasks. These libraries will be available to the campus community at large and would be deployed on our compute cluster.

Coordinators: Ravindran B, Kamakoti, V
Project Staff: Tania Khan, Tulasi Bai
Students: Prashant Tatan, Madhur Charkha, Akash Jain, Ashish Bhayana
Collaborator: Madhusudan G S.

Biological Networks & Data Analysis

ILDS also works on a variety of problems related to biological networks/data analysis, such as predicting protein essentiality from protein interaction networks, mining biochemical reaction rules from complex reaction networks, identifying synthetic lethals in metabolic networks as well as learning protein function from protein interaction networks. We are also looking at integrating biological data from different levels of biological organisation, such as genomic, proteomic, transcriptiomic and phosphoproteomics data.

Coordinators: Karthik Raman, B. Ravindran, Sayan Ranu, Raghunathan Rengasamy
Students: Karthik A, Malvika Sudhakar, Pallavi Gudipati, Beethika Tripathy
Collaborator: Ashok Venkitaraman (Cambridge)

Intelligent Transportation Systems

Rich real-time traffic data is being obtained using advanced sensors such as Video and GPS as well as communication technologies at a data centre in the Intelligent Transportation Systems laboratory. This data offers tremendous scope to investigate empirical patterns and use these insights to operate and manage the transportation system towards desired objectives including reduced congestion, improved reliability and safety, better fuel efficiency and decrease in environmental pollution. The focus of this work will be to mine this data to derive empirical understanding and develop models towards this broad goal. Specific focus areas include: quantification of the ITS data to investigate the role of various sources that affect system performance (demand, incidents, weather, construction, special events, control devices etc.) and applying this knowledge towards the development of algorithms for optimizing and improving system performance.

Coordinators: Karthik K. Srinivasan, Gitakrishnan Ramadurai, B. Ravindran, Sayan Ranu
Students: Deepak Mittal, Nandani Garg
Staff: Thulasi Bai

Network Systems

AFDX Networking Switch

AFDX was designed as the next-generation aircraft data network for safety critical applications to harness the increasing bandwidth while providing deterministic quality of service. This posed new challenges to the designers of the AFDX systems/switches not previously seen in other aircraft avionic buses. Designers had to provide the systems with the capacity to process Ethernet frames that may be carrying packet traffic at near wire-line speed. To achieve this high level of performance, hardware and software has to be equipped to perform the core AFDX functions and other mundane operations like time stamping, IP header checksum etc in real time. We had developed the indigenous AFDX prototype solution using an enterprise Freescale 1020/1040 processor based board.

Key Members: Prof. V. Kamakoti, Vasan V S
Students: K.P. Sareena

Secure Systems Engineering

Integrated Threat Management Appliance

The objective behind the work was to develop a security device which will sit in the network perimeter of any organization and act as a protection mechanism for both incoming and outgoing network traffic. As part of this project, different features like firewall, proxy and intrusion detection systems were implemented.

Key Members: Prof. V. Kamakoti, Vasan V S

ANURAKSHA: A secure tablet

The objective behind the work was to design and develop a secure tablet device with high assurance boot and other security features like tamper detection, encryption of complete root file system on the device with Android running on the device.

Key Members: Prof. V. Kamakoti, Vasan V S, KS Venkataraghavan
Project Staff: Raja Mohammed

Kedarnath Project

The goal of this project is to monitor heritage structures and take efforts to preserve them. We embarked on a project jointly with the Department of Civil Engineering to develop an embedded platform that monitors the Kedarnath temple for its structural health. The data received from the devices placed at critical locations in the temple will be used to monitor and predict periodic maintenance activity for this heritage structure.

Key Members: Prof. V. Kamakoti, Shankar Raman

About Us

R.I.S.E. Group is a research group in the CSE Dept. of IIT Madras working the in the areas of Computer Architecture, Security, Machine Learning and VLSI Design. If you wish to collaborate with us, please contact the relevant Faculty members from the People's page

Contact Us
  • CSE Dept., IIT Madras, Chennai, 600036, India
  • +91-44-2257 5390