Aravind Natarajan

age ~47

from Daly City, CA

Also known as:
  • Aravind Natatajan
  • Natarajan Aravind

Aravind Natarajan Phones & Addresses

  • Daly City, CA
  • Philadelphia, PA
  • Palo Alto, CA
  • Pittsburgh, PA
  • Gainesville, FL
  • Fremont, CA
  • 559 Oaklynn Ct APT 2A, Pittsburgh, PA 15220

Resumes

Aravind Natarajan Photo 1

Aravind Natarajan Dallas, TX

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Work:
Department of Computer Science, The University of Texas at Dallas

Jan 2012 to 2000
Graduate Research Assistant
The University of Texas at Dallas
Richardson, TX
Sep 2010 to Jan 2012
Graduate Teaching Assistant
Reputation.com
Redwood City, CA
Jun 2010 to Aug 2010
Software Engineering Intern
Education:
The University of Texas at Dallas
Richardson, TX
2010 to 2013
Doctor of Philosophy in Computer Engineering
The University of Texas at Dallas
Richardson, TX
2007 to 2009
MS in Computer Engineering
Maulana Azad National Institute of Technology
Bhopal, Madhya Pradesh
2003 to 2007
B.Tech in Electronics and Communication Engineering
Skills:
Algorithms, Data Structures, Programming, Research
Aravind Natarajan Photo 2

Aravind Natarajan Richardson, TX

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Work:
Department of Computer Science, The University of Texas at Dallas

Jan 2012 to 2000
Graduate Research Assistant
The University of Texas at Dallas
Richardson, TX
Sep 2010 to Jan 2012
Graduate Teaching Assistant
Reputation Defender Inc.
Redwood City, CA
Jun 2010 to Aug 2010
Software Engineering Intern
Education:
The University of Texas at Dallas
Richardson, TX
2010 to 2013
PhD in Computer Engineering
The University of Texas at Dallas
Richardson, TX
2007 to 2009
Master of Science in Computer Engineering
Maulana Azad National Institute of Technology
Bhopal, Madhya Pradesh
2003 to 2007
Bachelor of Technology in Electronics and Communication Engineering
Skills:
Algorithm Design and Implementation, Parallel Programming.
Aravind Natarajan Photo 3

Aravind Natarajan Palo Alto, CA

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Work:
Insight

Jun 2014 to 2000
Data Science Fellow
Carnegie Mellon University and University of Pittsburgh
Pittsburgh, PA
Sep 2009 to Aug 2013
Research Associate and Center Fellow
Bielefeld University
Bielefeld
Oct 2007 to Jul 2009
Postdoctoral Fellow in Particle Astrophysics
Education:
University of Florida at Gainesville
Gainesville, FL
Aug 2002 to Aug 2007
Ph.D in Physics
Bangalore University
Bangalore, Karnataka
Sep 2000
Bachelor of Engineering in Electronics and Communication
Skills:
Machine Learning and Natural Language Processing using scikit-learn and NLTK. Bayesian estimation of model parameters using Markov Chain Montecarlo simulations. Languages: Python, C, MySQL, Javascript. Published 26 papers in major journals, with over 300 citations.

Us Patents

  • Speculative Loop Iteration Partitioning For Heterogeneous Execution

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  • US Patent:
    20180060130, Mar 1, 2018
  • Filed:
    Aug 24, 2016
  • Appl. No.:
    15/245604
  • Inventors:
    - San Diego CA, US
    Han Zhao - Santa Clara CA, US
    Aravind Natarajan - Sunnyvale CA, US
  • International Classification:
    G06F 9/50
  • Abstract:
    Embodiments include computing devices, apparatus, and methods implemented by the apparatus for implementing speculative loop iteration partitioning (SLIP) for heterogeneous processing devices. A computing device may receive iteration information for a first partition of iterations of a repetitive process and select a SLIP heuristic based on available SLIP information and iteration information for the first partition. The computing device may determine a split value for the first partition using the SLIP heuristic, and partition the first partition using the split value to produce a plurality of next partitions.
  • Shared Virtual Index For Memory Object Fusion In Heterogeneous Cooperative Computing

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  • US Patent:
    20180052776, Feb 22, 2018
  • Filed:
    Aug 18, 2016
  • Appl. No.:
    15/239937
  • Inventors:
    - San Diego CA, US
    Arun Raman - San Francisco CA, US
    Aravind Natarajan - Sunnyvale CA, US
  • International Classification:
    G06F 12/109
  • Abstract:
    Embodiments include computing devices, apparatus, and methods implemented by the apparatus for implementing shared virtual index translation on a computing device. The computing device may receive a base virtual address for storing an output of a kernel function execution to a dedicated memory and determine whether the virtual address is in a range of virtual addresses for a privatized output buffer within the dedicated memory, which may be smaller than the dedicated memory. The computing device may calculate a first modified physical address using a physical address mapped to the base virtual address and an offset of a first processing device associated with the dedicated memory in response to determining that the base virtual address is in the range of virtual addresses. The computing device may store the output of the kernel function execution to the privatized output buffer at the first modified physical address.
  • Identifying Enhanced Synchronization Operation Outcomes To Improve Runtime Operations

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  • US Patent:
    20170286182, Oct 5, 2017
  • Filed:
    Mar 30, 2016
  • Appl. No.:
    15/085108
  • Inventors:
    - San Diego CA, US
    Gheorghe Cascaval - Palo Alto CA, US
    Han Zhao - Santa Clara CA, US
    Tushar Kumar - San Jose CA, US
    Aravind Natarajan - Sunnyvale CA, US
    Arun Raman - Fremont CA, US
  • International Classification:
    G06F 9/52
  • Abstract:
    Embodiments include computing devices, systems, and methods identifying enhanced synchronization operation outcomes. A computing device may receive a first resource access request for a first resource of a computing device including a first requester identifier from a first computing element of the computing device. The computing device may also receive a second resource access request for the first resource including a second requester identifier from a second computing element of the computing device. The computing device may grant the first computing element access to the first resource based on the first resource access request, and return a response to the second computing element including the first requester identifier as a winner computing element identifier.
  • Random-Access Disjoint Concurrent Sparse Writes To Heterogeneous Buffers

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  • US Patent:
    20170206035, Jul 20, 2017
  • Filed:
    Jan 19, 2016
  • Appl. No.:
    15/000667
  • Inventors:
    - San Diego, CA
    Aravind Natarajan - Sunnyvale CA, US
    Dario Suarez Gracia - Teruel, ES
  • International Classification:
    G06F 3/06
    G06F 12/10
  • Abstract:
    Methods, devices, and non-transitory processor-readable storage media for a computing device to merge concurrent writes from a plurality of processing units to a buffer associated with an application. An embodiment method executed by a processor may include identifying a plurality of concurrent requests to access the buffer that are sparse, disjoint, and write-only, configuring a write-set for each of the plurality of processing units, executing the plurality of concurrent requests to access the buffer using the write-sets, determining whether each of the plurality of concurrent requests to access the buffer is complete, obtaining a buffer index and data via the write-set of each of the plurality of processing units, and writing to the buffer using the received buffer index and data via the write-set of each of the plurality of processing units in response to determining that each of the plurality of concurrent requests to access the buffer is complete.
  • Data Management For Multiple Processing Units Using Data Transfer Costs

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  • US Patent:
    20170060633, Mar 2, 2017
  • Filed:
    Aug 27, 2015
  • Appl. No.:
    14/837156
  • Inventors:
    - San Diego CA, US
    Tushar Kumar - San Francisco CA, US
    Aravind Natarajan - Sunnyvale CA, US
    Ravish Hastantram - San Jose CA, US
    Gheorghe Calin Cascaval - Palo Alto CA, US
    Han Zhao - Santa Clara CA, US
  • International Classification:
    G06F 9/50
  • Abstract:
    Various embodiments include methods for data management in a computing device utilizing a plurality of processing units. Embodiment methods may include generating a data transfer heuristic model based on measurements from a plurality of sample data transfers between a plurality of data storage units. The generated data transfer heuristic model may be used to calculate data transfer costs for each of a plurality of tasks. The calculated data transfer costs may be used to schedule execution of the plurality of tasks in an execution order on selected ones of the plurality of processing units. The data transfer heuristic model may be updated based on measurements of data transfers occurring during the executions of the plurality of tasks (e.g., time, power consumption, etc.). Code executing on the processing units may indicate to a runtime when certain data blocks are no longer needed and thus may be evicted and/or pre-fetched for others.

Flickr

Youtube

tinyML Talks - Aravind Natarajan: Pushing th...

tinyML Talks webcast - recorded July 21, 2020 "Pushing the Limits of U...

  • Duration:
    38m 32s

Aravind Natarajan presents at Cornell's 2017 ...

Finalist Aravind Natarajan.

  • Duration:
    3m 6s

Data Driven Sales & Marketing Using Advanced ...

Crunch your CRM data and convert it to valuable insights. Know in adva...

  • Duration:
    17m 7s

Inauguration of the Every Child A Scientist P...

Inauguration of the Every Child A Scientist Program 2021-2022 26 Septe...

  • Duration:
    1m 4s

An Introduction to Centerfield

In this podcast, Aravind Natarajan is in conversation with Abhishek Th...

  • Duration:
    46m 51s

December Music Season Dec 2021 Concerts - Ka...

Kalyanapuram Aravind Vocal H N Bhaskar Violin Delhi Sairam Mridangam C...

  • Duration:
    2h 6m 38s

Myspace

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Aravind Natarajan

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Locality:
chennai, Tamil Nadu
Gender:
Male
Birthday:
1954

Googleplus

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Facebook

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Aravind Natarajan

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Aravind Natarajan

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Aravind Natarajan

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Aravind Natarajan

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Aravind Natarajan

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