Prajyot's Homepage

Biography

I'm a Graduate Student at the University of Wisconsin-Madison in Department of Electrical & Computer Engineering Department.

I'm currently pursuing my summer'22 internship at NVIDIA as a Systems Architect Intern with my work focusing on Reliability, Availability and Serviceability (RAS) Architectures for NVIDIA's latest Grace CPUs.

Previously, I did a co-op at Advanced Micro Devices Inc., in the Radeon Technology SoC Architecture Group. My work focused on designing simulator infrastructure and performance modeling of AMD's Instinct™ accelerators and Radeon™ RX Graphics Cards to propel HPC & AI workload analysis.

I'm a Research Assistant at UW STACS lab, under Professor Joshua San Miguel. My research focuses on building low-power computer systems using approximate computing. I'm currently working on designing a tightly-coupled hardware accelerator that offloads the predicate computation onto a reconfigurable fabric for Hard-to-Predict (H2P) branches.

I was recently awarded the DAC Young Researcher Fellowship for the 58th Design Automation Conference 2021, San Francisco. I will be a Graduate Teaching Assistant in ECE353: Introduction to Microprocessor Systems @ UW Madison!

I completed my Bachelor's from BITS Pilani, Pilani Campus, 2017 in Electrical & Electronics Engineering with a Bachelor's Thesis on Approximate Computing under Professor Akash Kumar, Chair for Processor Design, TU Dresden, Germany. Post my bachelor's, I worked with Qualcomm Snapdragon Systems team for 3.5 years on multiprocessor concurrency and system coherency; being directly involved in the tape-out of 12 Snapdragon chipsets.

Prajyot_Resume_UW_Madison-no-contact-info.pdf

Prajyot's Resume

A brief history of my previous work.

DAC_Poster_Prajyot_Gupta.pdf

DAC'21 Poster Presentation

Dynamic Predication for Hard-to-Predict Branches Poster, presented in 58th Design & Automation Conference, San Francisco.

Prajyot Gupta Thesis Presentation.pdf

Bachelor's Thesis Presentation

Impact of approximate adders on QRS Peak detection algorithm.

Relevant Courses Completed

  • Computer Architecture

  • Advanced Computer Architecture

  • High Performance Computing with CUDA & OpenMP

  • Operating Systems

  • Embedded Systems Design

  • Reconfigurable Computing

  • Microprocessor Design

  • Digital System Design