I am a fourth year Ph.D student at MIT CSAIL working in computer architecture and advised by Prof. Daniel Sanchez. I am broadly interested in techniques that leverage application-level information to reduce data movement in future hardware architectures. I have worked on cache performance of graph analytics, distributed multicore cache hierarchies and locality-aware parallel runtimes. As a summer intern at Nvidia Research, I worked on hardware architectures for deep learning.

Before coming to MIT, I graduated with Bachelors in Electrical Engineering from Indian Institute of Technology Bombay in 2014, where my research focused on multicore architectures and VLSI Design. While at IIT Bombay, I did summer internships at Cornell University and University of Toronto.


A Hybrid Cache Partitioning-Sharing Technique for Commodity Multicores

Nosayba El-Sayed, Anurag Mukkara, Po-An Tsai, Harshad Kasture, Xiaosong Ma, Daniel Sanchez

The 24th IEEE International Symposium on High Performance Computer Architecture (HPCA-24), February 2018, Vienna, Austria. Acceptance Rate: 21%

Cache-Guided Scheduling: Exploiting Caches to Maximize Locality in Graph Processing

Anurag Mukkara, Nathan Beckmann, Daniel Sanchez

The 1st International Workshop on Architecture for Graph Processing (AGP-17, co-located with ISCA-44), June 2017, Toronto, Ontario, Canada

Paper Talk Bibtex

SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks

Angshuman Parashar, Minsoo Rhu, Anurag Mukkara, Antonio Puglielli, Rangharajan Venkatesan, Brucek Khailany, Joel Emer, Stephen W. Keckler, William J. Dally

The 44th IEEE/ACM International Symposium on Computer Architecture (ISCA-44), June 2017, Toronto, Ontario, Canada. Acceptance Rate: 17%

Paper Talk Bibtex

Whirlpool: Improving Dynamic Cache Management with Static Data Classification

Anurag Mukkara, Nathan Beckmann, Daniel Sanchez

The 21st IEEE International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-21), April 2016, Atlanta, Georgia, USA. Acceptance Rate: 22%

Paper Talk Bibtex Code

  • Address

    G742, 32 Vassar Street
    Cambridge, MA 02139
    United States
  • Email

    anurag_m AT csail DOT mit DOT edu