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Hello! Welcome to my website. I am an optimistic, diligent and strategic person by nature, who likes to explore challenges related to computer/system architectures and digital design. Currently, I am a graduate student in Computer Engineering at SCIDSEArizona State University (ASU) beginning Spring 2017. Prior joining the doctoral program, I earned my master's at ASU in Computer Engineering in 2016. My coursework and interest lie in VLSI and Architecture area. In specific, I am interested in exploring compilers and architectures for accelerators. My current thesis targets researching Coarse-Grained Reconfigurable Arrays (CGRAs) which are energy-efficient accelerators that can speed-up even non-vectorizable performance-critical loops. My research at Compiler Micro-architecture Lab (CML), ASU is guided by Prof. Aviral Shrivastava and it targets automated acceleration of general-purpose applications through CGRAsTo boost CGRA research, there is a strong need of an efficient and common platform where accelerations of various applications can be verified. Taking on this challenge, I am developing an open-source CPU-CGRA compiler-simulator infrastructure. This enables the acceleration of compute-intensive applications featuring performance-critical yet non-vectorizable loops! Simultaneously, I strive to determine better architectural choices through my work e.g. data memory bottleneck, an efficient communication interface between multi-cores and accelerator etc. I am also a recipient of the A. Richard Newton Young Student Fellowship (2016). My past industry experiences are in the field of RTL Design and Verification for ASIC/FPGA and I possess strong coursework in these areas. 

I am always fascinated towards development in electronics and computing industry. I am interested in exploring computer architectures and challenges in the efficient system design. My research interests include, but are not limited to:
  • Hardware Accelerators including Coarse-Grained Re-configurable Arrays (CGRAs)
  • Embedded System
  • Compilers
  • High-Performance Computing (HPC)