Ch. Bhaskar Vishnuvardhan - Software Engineer 2 at KLA-Tencor Software India Private... - Bangalore

Ch. Bhaskar Vishnuvardhan
Bangalore, Karnataka, India
Core Java C Language Aptitude Computer Programmer
SSSPGC-Sri Satya Sai Post Graduation College

About Ch. Bhaskar Vishnuvardhan

Ch. Bhaskar Vishnuvardhan works as Software Engineer 2 at KLA-Tencor Software India Private Limited and is based in Bangalore, India. Ch. studied Master of Engineering or Technology (CS-Computer Science) at Sri Satya Sai Post Graduation College (2014-2016). On Youth4work, Ch. has taken skill tests in Core Java (rank 723 of 348,020, top 1%), C Language (rank 1,490 of 193,364, top 1%) and Aptitude (rank 9,883 of 3,606,048, top 1%). Ch. also lists talents in Computer Programmer, Operating System, C Plus Plus and Python.

Talents

Computer Programmer

... among ... users in Bangalore

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among … users worldwide
Computer Programmer

... among ... users in Bangalore

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among … users worldwide
Core Java

... among ... users in Bangalore

723

among 348020 users worldwide

97.91

percentile among worldwide users
Operating System

... among ... users in Bangalore

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among … users worldwide
C Plus Plus

... among ... users in Bangalore

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among … users worldwide

Complete Talent Profile »

Professional Path

Software Engineer 2

KLA-Tencor Software India Private Limited Full Time

Jun-2016 To present 10 years 3 months

Design and Development of the product.

» 3 Projects

Scaling up Training of Deep BLSTM Networks for Handwritten Text Recognition

Student at SSSPGC-Sri Satya Sai Post Graduation College

Jul-2015 to Sep-2015

Deep BLSTM based Recurrent Neural Networks are one of the important deep learning models which are extensively used for Vision and Speech applications. In this work we parallelized the training of Deep BLSTM networks for handwriting text recognition. We have achieved speedup of 10x using OpenMP and 7.2x using MIC. We have also used Intel MKL functions for optimizing the code and achieved speedup of about 8.3x.

Improving the Performance of Heterogeneous Hadoop Cluster.

Student at SSSPGC-Sri Satya Sai Post Graduation College

Jun-2015 to Feb-2016

The current Hadoop implementation assumes that computing nodes in a cluster are homogeneous in nature. Hadoop relies on its capability to take computation to the nodes rather than migrating the data around the nodes which might cause a significant network overhead. This strategy has its potential benefits on homogeneous environment but it might not be suitable on an heterogeneous environment. The time taken to process the data on a slower node on a heterogeneous environment might be significantly higher than the sum of network overhead and processing time on a faster node. Hence, it is necessary to study the data placement policy where we can distribute the data based on the processing power of a node.

Clustering Algorithms using Hadoop MapReduce Framework

Nov-2012 to Mar-2013

Clustering is a common technique which is applied across many fields. But as the data becomes larger and larger it becomes a tough task to cluster the data, Map Reduce will be attractive solution for this problem. This report explains about different clustering algorithms like K-Means clustering, Fuzzy K-Means clustering and Canopy clustering. We have also explained about the Netflix dataset and the results produced by different algorithms when applied on the netflix data. The algorithms were implemented in Apache Mahout using the Hadoop MapReduce framework.

Qualifications

Sri Satya Sai Post Graduation College

Master of Engineering or Technology Computer Science

2014-2016

82%

Sri Sathya Sai Institute of Higher Learning

Master of Science Computer Application

2012-2014

81%

Extra-Curricular Interests

Shuttle Badminton Cricket Volley Ball Table Tennis Music

My Story

A passionate learner with analytical and communication skills.
Interested in Data Analytics, Big Data, Machine Learning and High Performance Computing. Ready to take up anything that comes my way.

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