Ananth Krishna Prasad

School of Computing, University of Utah · ananth@cs.utah.edu

Welcome to my Personal Webpage

I am a third year PhD Student under Prof. Mahdi Nazm Bojnordi in the School of Computing in University of Utah. I am broadly interested in the fields of Computer Architecture, and my research specifically focuses on Hardware Acceleration of performance critical applications and Novel Memory Systems

Link to my resume


Experience

Graduate Research Assistant

School Of Computing, University of Utah

Hardware Acceleration of Machine Learning - currently working on developing a novel data representation to reduce bandwidth and computational complexity of Convolutional Neural Networks (CNNs)

High Bandwidth Cross Caching - Developed a novel reconfigurable memristor based memory with high bandwidth efficiency, with capability of large scale parallel search. Demonstrated cache/scratchpad reconfigurability, high lifetime and achieved 50% and 12x improvement over state-of-the-art High Bandwidth memory, over Cache and Hash Table/Stringmatch applications respectively.

Memristive Ranking In Memory - Identified bandwidth bottleneck issues with sorting kernels, and proposed propose a viable hardware/software mechanism for performing large-scale data ranking in ReRAM based memory with a bandwidth complexity of O(1), by reformulating sorting operations as bit-level in-situ operations. Achieved 12.4 - 50.7x throughput gains for high-performance parallel sorting kernels and 2.3 - 43.6x improvements in a set of database applications, with 90% energy reduction. Submitted to HPCA 2021

Reconfigurable Transistors - Did a survey of TIGFET, an emerging reconfigurable nanotechnology and qualified it’s implication for computer architects. Published as blogpost in ACM Sigarch.

August 2018 - Present

Graduate Teaching Mentor

School Of Computing, University of Utah

Teaching Mentor with Prof. Ryan Stutsman for Graduate Level Operating Systems (CS 6460) in Spring 2020

Teaching Mentor with Prof. Mahdi Bojnordi for Undergraduate Level Computer Organization (CS 3810) in Fall 2020

Research Assistant

Indian Institute of Science, Bangalore

Implemented and validated Worst Case Execution Time (WCET) analysis over the REDEFINE hardware for validation of safety-critical application execution.

July 2017 - June 2018

Intern

Analog Devices India, Bangalore

Implemented an Alexnet CNN model for car-parking occupancy detection. The initial model was done using Caffe with optimal hyperparameters, which gave an accuracy of 98.6 with 25 FPS. The whole model was subsequently ported onto Tiny-DNN and then to XNOR-net.

The implementations on Tiny-DNN and Xnor-net use much lesser memory and computation space respectively than the caffe version and suited our primary motive of achieving real-time in portable systems.

January 2017 - June 2017

Intern

Apexplus Technologies, Hyderabad

Configured an FPGA-DAC interface to act as a signal generator. Programmed the FPGA to send in the data at required rate, configured the NCO and mixer to moulate the incoming bistream to required frequency and programmed the PLL to generate the required clocks.

May 2016 - July 2016

Education

University of Utah

Doctorate (PhD), Computer Science

GPA: 3.856/4.00

August 2018 - Present

BITS Pilani, Hyderabad Campus

Bachelor of Engineering (Hons.) Electronics and Communication

GPA: 8.35/10.00

August 2013 - May 2017

Skills

Programming Languages
  • C/C++
  • Python
  • Verilog/Vivado
Relevant Courses
  • Neuromorphic Architecture
  • Computer Architecture
  • Parallel Programming on GPUs
  • Machine Learning
  • Analog and Digital VLSI
  • FPGA Bases System Design
Frameworks
  • ESESC
  • Cacti
  • Tensorflow
  • Caffe

Interests

I have recently taken up hiking as a welcome excuse to get outside during quarantine. The longest hike I have done till now was a gruelling 4.5ft 16 mile hike to the summit of Mount Timpanogos

Apart from working on my PhD Thesis and trying to publish top-notch papers, I am a huge enthusiast of E-Sports, especially Counter Strike: Global Offensive.

When forced indoors, I follow a number of crime-fiction genre movies, television shows and documentaries, or you can probably hear me trying to hone my skills in Classical Singing


Achievements

  • DAC 2020 - Accepted to the DAC 2020 young fellows program
  • de-HPC 2016 - Invited to the de-HPC conference on High performance computing held in IIT-B as part of the team representing BITS, Pilani Hyderabad campus

Articles

Publications

  • Nothing Yet. Optimistically, this section will start filling up soon

Posters Presented