Qualification: 
M.Tech
b_meena@blr.amrita.edu

Meena Belwal currently serves as Assistant Professor at department of Computer Science,Amrita School of Engineering.She is currently pursuing her Ph.D.

Publications

Publication Type: Conference Paper

Year of Publication Title

2019

Meena Belwal, Abhinav, K., G. sahith, R., and Sasank, J. V. V. Srir, “Credit Card Fraud Detection Using Various Classification and Sampling Techniques: A Comparative Study”, in International Conference on Communication and Electronics Systems [ICCES 2019], PPG Institute of Technology, Coimbatore, 2019.

2019

R. .G and Meena Belwal, “Hardware Implementation of VANET Communication based Collision Warning System”, in International Conference on Communication and Electronics Systems [ICCES 2019], PPG Institute of Technology, Coimbatore, 2019.

2019

R. .G and Meena Belwal, “Vehicle Collision Avoidance in a VANET Environment by Data Communication”, in 3rd International Conference on Computing Methodologies and Communication [ICCMC 2019], Surya Engineering College, Erode , 2019.

2019

V. T. Sai Sandee Raju and Meena Belwal, “Driver Drowsiness Detection”, in International Conference on ISMAC in Computational Vision and Bio-Engineering (ISMAC -CVB 2019), 2019.

2018

S. Vanaja and Meena Belwal, “Aspect-Level Sentiment Analysis on E-Commerce Data”, in International Conference on Inventive Research in Computing Applications (ICIRCA 2018), RVS College of Engineering and Technology, Coimbatore, Tamil Nadu, India, 2018.

2018

D. Gupta and Meena Belwal, “Pest Identification and Control of Diseases in Crop Fields through Image Processing and Tracking of Atmospheric Parameters”, in 2nd International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC 2018) , SCAD Institute of Technology, Palladam, India, 2018.

2017

K. S. M and Meena Belwal, “Performance Dashboard Cutting-Edge Business Intelligence and Data Visualization”, in International Conference On Smart Technologies For Smart Nation (SmartTechCon2017), Reva University, Bengaluru, 2017.

2015

Meena Belwal and TSB, S., “Intermediate representation for heterogeneous multi-core: A survey”, in 2015 International Conference on VLSI Systems, Architecture, Technology and Applications (VLSI-SATA), Amrita School of Engineering, Bengaluru., 2015.[Abstract]


One of the necessary conditions to gain performance improvement through heterogeneous multi-core is to exploit the parallelism in the program. Compiler applies various transformations to the code to achieve execution efficiency. Code optimization is one of the important tasks performed by the compiler before generating the target code. With the availability of various parallel programming models in literature, Intermediate representation (IR) is the key point of applying several optimizations. IR is a form of program which is independent of the source language and the target architecture. There are several IR techniques specifically designed for each compiler framework depending on the input programming language. This article studies the most popular IR techniques for heterogeneous multi-core, classifies them into three broad categories and performs a comparison among them based on the data structure used and their importance in academia and research.

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2014

Meena Belwal and Sudarshan, T. S. B., “A survey on design space exploration for heterogeneous multi-core”, in 2014 International Conference on Embedded Systems (ICES), Coimbatore, India, 2014.[Abstract]


Design Space Exploration (DSE) plays an important role during the process of Hardware/Software co-design for heterogeneous multi-core architecture. DSE is the process of discovering and evaluating design alternatives, prior to implementation. The various designs can be compared with each other on the basis of required metrics and the optimized design can then be chosen to develop the system. The main goal of DSE is rapid prototyping and it is also used to find configurations and legal assemblies to satisfy a particular set of overall design constraints. This paper surveys the various DSE approaches used for heterogeneous multi-cores and compares them.

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