Student InformationGraduate Student
Computer Engineering (Computer Systems)
Ira A Fulton Engineering
Shail Dave is a final-year Ph.D. candidate, majoring in Computer Engineering, at the School of Computing and Augmented Intelligence (SCAI) since 2017. Before joining the doctoral program, he earned a master's at ASU in Computer Engineering in 2016. He is currently affiliated with Compiler Microarchitecture Lab / Make Programming Simple Lab and Center for Embedded Systems, working with Prof. Aviral Shrivastava on "Agile and Sustainable, Accelerated Computing".
Shail's research techniques and infrastructures enable the efficient processing of critical applications such as machine/deep learning on hardware accelerators in an agile and sustainable manner. More specifically, his research develops compilation and mapping optimizations for accelerators, execution cost modeling and bottleneck characterization of accelerators, language for automated accelerator designs, efficient dense/sparse tensor computations, accelerator simulators, and exploration of hardware/software codesigns through systematic heuristics and machine learning. His research is regularly published in and referred by the top ACM/IEEE conferences and journals in these domains (design automation, embedded systems, and computer architecture). His research has also been featured in premier forums (ARM Research Summits, Annual Days of NSF/Intel CAPA Research Center, Future Chips Forum, etc.). Read more about his vision paper on "Accelerator Design 2.0" here (Summary Talk) and a comprehensive literature survey on machine learning accelerator systems here.
Shail's industry experiences include compiler optimizations for wide-scale commodity embedded systems, as well as digital design and verification for FPGA-based accelerators and ASICs. He is also experienced in piloting novel research projects and infrastructures, both in collaboration with expert industry/academic researchers (Intel Labs, ARM Research) and in the industry (through his research internships at MathWorks Research, Space Application Center–ISRO), especially for cutting-edge accelerator design and system stack development.
Shail is a recipient of several competitive honors and awards. He also regularly serves in various professional and community activities, including reviewing for top conferences and journals in his research areas (DAC, ESWEEK, RTSS, IEEE Sensors, ACM TECS, ACM TODAES), the program or organizing committee for these top conferences and workshops (ESWEEK, ASPLOS - LATTE), and various mentorship programs and activities.
- M.S., Computer Engineering, Arizona State University, 2016
- B.E., Electronics and Communication Engineering, L. D. College of Engineering, Ahmedabad 2014
Shail's research develops agile design tools and techniques for efficient accelerator designs, including for dense/sparse tensor computations of Machine/Deep Learning models. These include compilation and mapping optimizations, execution cost modeling and bottleneck characterization, and explorations of hardware/software co-designs, including through systematic heuristics and machine learning. His research is regularly published in and referred by the top ACM/IEEE conferences and journals in these domains (design automation, embedded systems, and computer architecture) and has featured in premier forums (ARM Research Summits, NSF/Intel annual CAPA days, Future Chips Forum, etc.).
Shail's research interests and experience include:
- Programmable Hardware Accelerators
- Hardware/Software Co-Design
- Agile and Sustainable Design Automation
- Computer Architecture
- Deep Learning and DNN Model Compression
- Embedded and Cyber-physical Systems
- Compiler Design and Optimizations
- Execution Modeling and Bottleneck Characterization
- High-Performance, Energy-efficient Computing
- Near-Data Processing
- Distributed, Real-time Edge Computing
- Machine Learning for Systems
Compiler Microarchitecture Lab/ Make Programming Simple Lab Center for Embedded Systems Affiliated with: School of Computing and Augmented Intelligence (SCAI), Ira A. Fulton Schools of Engineering, Arizona State University, Tempe, AZ.
- [VTS] Towards an Agile Design Methodology for Efficient, Secure, and Reliable ML Systems. Shail Dave, Alberto Marchisio, Muhammad Abdullah Hanif, Amira Guesmi, Aviral Shrivastava, Ihsen Alouani, Muhammad Shafique, in Proceedings of the 40th IEEE VLSI Test Symposium (VTS), 2022 (Invited Special Session). [Paper]
- [LATTE @ ASPLOS] Design Space Description Language for Automated and Comprehensive Exploration of Next-Gen Hardware Accelerators. Shail Dave and Aviral Shrivastava, in Workshop on Languages, Tools, and Techniques for Accelerator Design (LATTE), co-located with ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2022. [Paper] [Talk] [Workshop] Key topics: Comprehensive, Reusable, Explainable, and Agile Design Exploration of Architectures.
- [Proceedings of the IEEE] Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights. Shail Dave, Riyadh Baghdadi, Tony Nowatzki, Sasikanth Avancha, Aviral Shrivastava, Baoxin Li. arXiv:2007.00864, 2020. [Paper] [summary tweet-thread] Key topics: Sources of sparsity in tensors; accelerator-aware pruning of deep learning models; implications of irregular or structured sparsity on hardware acceleration; analysis on sparsity-encoding schemes on storage; the impact of varying sparsity and tensor shapes of different DNN operations on data reuse; techniques for data extraction and load balancing of effectual (non-zero) computations; sparsity-aware dataflows; leveraging value similarity in tensors of computer vision and speech processing applications; trends and directions for accelerator/model codesigns.
- [TACO] SPX64: A Scratchpad Memory for General-Purpose Microprocessors. Abhishek Singh, Shail Dave, PanteA Zardoshti, Robert Brotzman, Chao Zhang, Xiaochen Guo, Aviral Shrivastava, Gang Tan, Michael Spear, in ACM Transactions on Architecture and Code Optimization (TACO), Vol. 18, No. 1, 2021 [Paper] [Talk @ HiPEAC '21]
- [ICASSP] dMazeRunner: Optimizing Convolutions on Dataflow Accelerators. Shail Dave, Youngbin Kim, Sasikanth Avancha, Kyoungwoo Lee, Aviral Shrivastava, in 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020). [Paper] [Slides] [Code] [Talk]
- [CODES+ISSS @ ESWEEK, TECS] dMazeRunner: Executing Perfectly Nested Loops on Dataflow Accelerators. Shail Dave, Youngbin Kim, Sasikanth Avancha, Kyoungwoo Lee, Aviral Shrivastava, in ACM Transactions on Embedded Computing Systems (TECS), Vol. 18, No. 5s, 2019 [Special Issue on ESWEEK 2019 - ACM/IEEE International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS)] [Paper] [Slides with Demo] [Slides] [Poster] [Code] Key topics: Defining comprehensive hardware/software design space for loop nests; Accelerator cost model for evaluating execution metrics for variations in hardware architecture, dataflows, model layers, Search-space reduction techniques for getting efficient mappings in a few seconds; Generic algorithms for obtaining all unique data reuse scenarios for loop-orderings.
- [DAC] RAMP: resource-aware mapping for CGRAs. Shail Dave, Mahesh Balasubramanian, and Aviral Shrivastava. In 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC), pp. 1-6. IEEE, 2018. [Paper] [Slides] [Poster] (Mapping Optimizations for Accelerating Loops of General-Purpose Computing).
- [Demonstrations @ DATE, DAC] CCF: CGRA Compilation and Simulation Framework. Shail Dave, Aviral Shrivastava, in University Booth Demonstration at the 21st International Conference on Design Automation and Test in Europe (DATE), 2018 [Paper] [Infrastructure]
- [DATE] URECA: A Compiler Solution to Manage Unified Register File for CGRAs. Shail Dave, Mahesh Balasubramanian, and Aviral Shrivastava.. In Design, Automation & Test in Europe Conference & Exhibition (DATE), 2018, pp. 1081-1086. IEEE, 2018. [Paper] [Slides]
- [DATE] LASER: A hardware/software approach to accelerate complicated loops on CGRAs. Mahesh Balasubramanian, Shail Dave, Aviral Shrivastava, and Reiley Jeyapaul. In Design, Automation & Test in Europe Conference & Exhibition (DATE), 2018, pp. 1069-1074. IEEE, 2018. [Paper] [Slides]
|Course Number||Course Title|
|CSE 420||Computer Architecture I|
|Course Number||Course Title|
|CSE 420||Computer Architecture I|
- Guest Lectures and Tutorials on "working with Gem5 architectural simulator" and "implementations of microarchitecture components in Gem5 simulator", CSE 420: Computer Architecture I, Fall 2021 [class size: 57]
- Guest Lecture on " Energy-efficient Acceleration of Residual Neural Nets onto Dataflow Accelerators", CSE 420: Computer Architecture I, Fall 2018 [class size: 115]
- Guest Lecture on "Dataflow Accelerators", ASU 101: The ASU Experience, Fall 2018 [class size: 19]
- Invited Talk on "Exploring Career Opportunities and Skill Enhancement" at sessions in International Student Orientation, ASU, Fall 2016 [total attendees: about 250]
- Invited Talk and Panel Discussion on "Leadership and Involvement Opportunities and Skill Enhancement", organized by Graduate and Professional Students Association (GPSA) during International Student Orientation, Spring 2016 [attendees: about 20]
Other lectures/recitations during Teaching Assistantship (Fall 2016 – Spring 2018)
- CSE 100: Principles of Programming with C++
- CSE 330: Operating Systems
- CSE 420/520: Computer Architecture (Outstanding TA Award)
- Completion Fellowship, Graduate College, Arizona State University – 2022
- Doctoral Fellowship, School of Computing, Informatics, Decisions, and Systems Engineering (CIDSE) – 2019
- Outstanding Research Award, Graduate and Professional Students Association (GPSA), ASU – 2021-2022
- Engineering Grad Fellowship, Ira A. Fulton Schools of Engineering, ASU – 2018, 2019, 2020
- A. Richard Newton Young Student Fellowship – 53rd Annual Design Automation Conference (DAC), June 2016
- Outstanding Computer Engineering TA Award, School of Computing, Informatics, Decisions and Systems Engineering (CIDSE), ASU – 2018
- Student lead, ASU team, NSF/Intel joint research center for Computer Assisted Programming for Heterogeneous Architectures (CAPA). (Our group was among the total three hubs supported nationwide.)
- Certificate of Appreciation (for outstanding service as social media chair), 17th ACM/IEEE Embedded Systems Week – 2021
- Research Spotlight, IEEE Eta Kappa Nu (HKN) – 2022 [Coverage: IEEE Bridge Volume 118]
- Invited for Inaugural Google Systems Innovation Summit – 2021 (Invitations limited to top global PhD students in computing systems.)
- Research works regularly invited and featured in several premier events (ARM Research Summits, NSF/Intel CAPA Annual Days, Future Chips Forum, etc.)
Competitive Travel Grant Awards from:
- School of Computing, Informatics, Decisions and Systems Engineering (CIDSE), ASU – 2018, 2019
- Computer Engineering, ASU – Spring 2018
- Graduate and Professional Student Association (GPSA), ASU – Summer 2016, Spring 2018, Fall 2019
- Graduate College, ASU – 2019
- ACM SIGDA and SIGBED – 2018, 2019
- IEEE Computer Society Technical Committee on Parallel Processing (TCPP) – 2022
- Association for Computing Machinery (ACM)
- Institute of Electrical and Electronics Engineers (IEEE)
- New York Academy of Sciences
- IEEE Computer Society
- IEEE Eta Kappa Nu Honors Society
- ACM Special Interest Group on Computer Architecture (SIGARCH)
- ACM Special Interest Group on Embedded Systems (SIGBED)
- IEEE Council on Design Automation (CEDA)
- IEEE Technical Committee on Computer Architecture (TCCA)
- Computer Architecture Student Association (CASA) (supported by: ACM SIGARCH / IEEE TCCA)
External and/or Expert Conference Reviewer:
- ACM Design Automation Conference (DAC) – 2018, 2019, 2020, 2022
- IEEE International Conference on Design Automation and Test in Europe (DATE) – 2016, 2017
- IEEE/ACM/IFIP International Conference on Hardware-Software Codesign and System Synthesis (CODES+ISSS) – 2016, 2017
- International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES) – 2019
- IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM) – 2019
- IEEE Real-Time Systems Symposium (RTSS) – 2019
- IEEE Asia and South Pacific Design Automation Conference (ASP-DAC) – 2022
- IEEE International Conference on Computer Design (ICCD) – 2019
- International Conference on VLSI Design and Embedded Systems (VLSID & ES) – 2017, 2018
Program Committee Member:
- Workshop on Languages, Tools, and Techniques for Accelerator Design (LATTE), co-located with ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) – 2022
- IEEE Sensors – 2022
- ACM Transactions on Embedded Computing Systems (TECS) – 2017, 2019, 2020
- ACM Transactions on Design Automation of Electronic Systems (TODAES) – 2020
- IEEE Transactions on Multi-Scale Computing Systems (TMSCS) – 2016, 2017
- International Journal on Design Automation for Embedded Systems, Springer – 2017
Select Voluntary, Organization, and Outreach Activities:
- Social Media Chair, ACM/IEEE Embedded Systems Week – 2021, 2022. [LinkedIn] [Twitter]
- Vice Chair, IEEE Eta Kappa Nu (HKN), ASU Chapter (2016–2017)
- Invited Speaker, International Student Orientation, ASU – 2016, 2017
- Webmaster, Compiler Microarchitecture Lab, 2017–Present
- Invited Panelist on Early Career Panel, ASU 101: The ASU Experience, Fall 2018
- Logistics management, Distinguished Speaker Invited Talks, CIDSE, ASU - 2017, 2018
- Mentor, Meet a Senior Architect (MaSA), Computer Architecture Student Association (CASA) – 2022
- Software Engineer (Intern), The Mathworks, Natick, MA (Summer 2018) Research Group: Code Efficiency, Embedded Coder Project: Loop Optimizations for Target-Aware Code Generation.
- ASIC Verification Engineer Intern, SanDisk Corporation, Milpitas, CA (Summer 2015) Project: Module-level verification of enterprise solid state drive controller ASIC.
- Research Intern, Space Application Center, Indian Space Research Organization, India (Spring 2014) Project: End-to-end System Development for Precise Temperature Control of Cryogenic Cooler Systems of Next Generation Geostationary Satellites.