Sparsh Mittal

Assistant Professor (and IEEE senior member)

Department of Electronics and Communications Engineering

Joint faculty at Mehta Family School of Data Science and Artificial Intelligence

Indian Institute of Technology, Roorkee, India.

Email: sparsh0mittal at gmail dot com; sparshfec at (which is an alias of sparsh.mittal at and sparsh.mittal at

Profiles at Google Scholar,, ResearchGate, LinkedIn, PublicationsList and ACM-Library . ORCID: 0000-0002-2908-993X

Webpage of CANDLE research lab

My talks on improving clarity in paper-writing, making technical figures, writing survey papers and making presentations.

Research Interests

Processor architectures for machine learning, neural network accelerators, autonomous driving vehicles, computer architecture (CPUs and GPUs), VLSI, high-performance computing, approximate computing.

Awards and Honors

1.    In the Stanford's list of world's top researchers 2021, in the field of Computer Hardware & Architecture, I am ranked as number 71 (for whole career) and as number 3 (for year 2020). In 2020 list, I was ranked 107 (for whole career) and as number 3 (for year 2019 alone).

2.    My research on mobile-phone usage detection was praised by Education Minister of India (1, 2, 3). It was covered by TOI, HinduBusinessLine, TelanganaToday, Andhrajyothi and many other media platforms.

3.    My research has been covered by several technical news websites, e.g., TheMemoryGuy, InsideHPC (1, 2, 3, 4, 5, 6, 7, 8),Primeur Magazine, StorageSearch 1, StorageSearch 2, StorageSearch 3,, TechEnablement, ScientificComputing, SemiEngineering (semiconductor engineering), ReRAM forum and HPCWire (1, 2, 3, 4, 5).

4.    My opinion-articles in popular media: BusinessWorldEducation, Eduvoice

5.    My application for recruiting a student on Intel PhD fellowship 2018 was approved.

6.     Received Distinguished Contribution rating at ORNL based on 2013-2014 performance appraisal. This rating recognizes the top 10 percent of staff. 

7.     Received Outstanding Contribution rating at ORNL based on 2014-2015 performance appraisal. Also received a performance award.

8.     Gave an invited presentation at Memory for HPC Systems session at ISC, Germany 2016. ISC is a top conference with 3000 attendees and bi-annual Top500 list is announced here.

9.     Best student paper candidate in SC 2014

10.                   ECpE fellowship from Electrical and Computer Engineering Department, Iowa State University, USA of $2500 in 2008.

11.                   Peer Research Award from Iowa State University, USA of $200 in 2013.

12.                   Topper in Electronics batch of year 2008 in ECE department at IIT Roorkee and received Institute Silver Medal for this.

13.                   Institute Silver Medal for Best B.Tech project award in Electronics and Computer Engineering (ECE) Department at IIT Roorkee.

14.                   Sumer Chand Jain Scholarship of INR 10,000 from IIT Roorkee.

15.  Best Student Award from High School (named MHS, Jaipur, Rajasthan, India) in 2004. Topper throughout school


Selected Publications

CORIDOR: Mitigating read-disturbance in STT-RAM: ACM TECS 2021

Multi-level MRAM cells IEEE TED and IOP SST 2021

A pruning technique for CNNs JSA 2021

Side-channel attacks to leak architecture of compact DNN ACM JETC 2020 and leak layer-types of a CNN on CPU AIMLSystems 2021

Modeling data-reuse in DNNs IEEE Trans. on Computers 2020

Deep-learning for detecting mobile usage GOODTECHS 2020

Improving accuracy of object detection algorithms using Multiscale Feature Aggregation Plugins ANNPR 2020

Co-Optimizing Hardware Utilization, and Performance of DNNs on Systolic Accelerator: ISVLSI 2020

Subspace attention module for compact DNNs: WACV 2020

Energy-efficient group convolution in DNNs: VLSID 2020

Approximate Load Value Prediction in GPUs: ICS 2019

Ramifications of making DNNs compact: VLSID 2019

NVM-based Swapping Framework for Guest OSes in VMs: IEEE Access 2017

Designing SOT-RAM based GPU register file: ISVLSI 2017

Addressing read-disturbance issue in STT-RAM cache: CAL 2017 (1)

Addressing write-disturbance issue in PCM memory: CAL 2017 (2)

Improving soft-error reliability of GPU register file: VLSID 2017

Inductive charge pump for 3D stacked PCM: GLSVLSI 2017

Write overhead management in NVM caches and main memory: HPDC 2016, IEEE TVLSI 2016, IEEE CAL 2015, IEEE MASCOTS 2015, GLSVLSI 2014, ISVLSI 2014, USENIX INFLOW 2014

Power management in SRAM and eDRAM caches: HPDC 2014, IEEE TVLSI 2013, ICCD 2013, VLSID 2013

Improving soft-error reliability of SRAM caches: GLSVLSI 2016

Application resiliency modeling and metric: SC 2014

Survey papers:

Machine learning/deep learning

Approximate computing and storage (summary PPT)

Deep learning for vehicle detection from UAV images

FPGA-based accelerators for CNNs, Deep learning accelerators on NVIDIA Jetson, FPGA/GPU/ASIC accelerators for RNNs, Accelerators for 3D CNNs, Hardware accelerators for GANs (generative adversarial networks)

Deep Learning on GPUs , Reliability of deep-learning algorithms and accelerators

Deep Learning on CPUs, Hardware security of DNN models and accelerators

Memristor (ReRAM) based and Spintronic-based architectures for Processing-in-memory and Neural networks (summary PPT)


On CPU-GPU heterogeneous computing

On big.LITTLE-style asymmetric multicore processors (for example, Samsung's Exynos 5 Octa) (summary PPT)

On Intelís Xeon Phi

On Micronís Automata Processor

On intermittent computing systems

On comparison between energy efficiency of GPUs, FPGAs and CPUs

Networking and architectural techniques for mobile web browsing

System component-level: architectural techniques for

GPU register file (summary PPT) and GPU caches

CPU register file

TLBs (translation lookaside buffer) (summary PPT)

Branch predictors

Value prediction and value locality

Architectural Management Techniques For

Cache partitioning in multicore processors (summary PPT)

Power management of GPUs, data centers, embedded systems, SRAM caches, DRAM main memory and PCM main memory

Near-threshold computing (summary PPT)

Data compression in cache and main memory (summary PPT)

Soft-error resilience for CPUs and GPUs (summary PPT)

Managing process variation in CPUs and GPUs (summary PPT)

Addressing soft-error issues in non-volatile memories (summary PPT)

Reliability techniques for DRAM

Encoding techniques for reducing data-movement energy

Cache prefetching in CPUs

Cache bypassing in CPUs, GPUs and CPU-GPU systems and SRAM, NVM and stacked-DRAM caches (summary PPT)

Cache locking

On security techniques for:

Non-volatile memories and GPUs

On memory technologies:

Stacked-DRAM caches (summary PPT), eDRAM and NVM caches, domain wall memory (racetrack memory) (summary PPT)

NVMs (e.g. Flash) for storage systems and main memory

SLC/MLC/TLC Hybrid Flash Memory based SSDs

On question answering systems (natural language processing)


See for full publication list and download links.

The PowerPoint slides of a few conference presentations are available here. Summaries of survey papers can be obtained by clicking on summary PPT above.

Funded Proposals

2017/04: SERB early career research (ECR) award, title: Secure and Reliable Non-volatile Memories for Ultra-low Power Applications

2018/08: SRC USA, title: Designing efficient hardware-accelerators for Autonomous Driving Vehicles

Open-source software released

1.    DESTINY: DESTINY is an acronym for 3D design-space exploration tool for SRAM, eDRAM and non-volatile memory. DESTINY can model:

* (2D/3D) SRAM and eDRAM


* (2D, SLC/MLC) SOT-RAM, Flash, DWM

In its purpose, DESTINY is similar to CACTI, CACTI-3DD or NVSim. Here are manual and the JLPEA 2017 journal paper. Source-code is available here. See its news coverage on ReRAM forum.

The proverb goes, write your own destiny. Hence, we have written our own [tool named] DESTINY. J

2.    Code and trained model of our WACV-2020 paper ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks

3.    Code and trained model of our VLSID-2020 paper E2GC: Energy-efficient Group Convolution in Deep Neural Networks

4.    Dataset and trained models of our GOODTECHS-2020 paper Detecting Usage of Mobile Phones using Deep Learning Technique

5.    Both serial and parallel versions of code of red-black SOR (successive over-relaxation) method in three state-of-the-art languages, viz. Chapel (from Cray Inc.), D (also called dlang, from Digital Mars) and Go (also called golang, from Google) can be downloaded for academic use from this link. They were used in this paper. Chapel version of the code has been incorporated in Chapel performance test suite/examples.


Invited Presentations/Seminars

* Xilinx, Hyderabad, 2019/07

* Intel India Research Colloquium 2017/10 (Bangalore)

* VelTech University, Chennai, India 2017

* PARCOMPTECH, Bangalore, India 2017 (organized by CDAC and DeitY)

* ISC Conference, Germany, 2016/06 (link)

* University of Michigan, 2015/11

* New York University 2016/02

Professional Background

Postdoctoral research associate at Oak Ridge National Lab, USA (2013-2016)

PhD from Iowa State University (ISU), Ames, Iowa, USA (2008-2013).

BTech from Indian Institute of Technology (IIT) Roorkee, Uttarakhand, India (2004-2008).


2018-03-08: A TLC workshop on Computer Organization, held at Anurag Group of Institutions, Ghatkesar

2017-11-10: On Advanced Computer Architecture, held at MITAOE (Pune, India)

2017-08-11: A TLC workshop on Computer Architecture, held at Anurag Group of Institutions, Ghatkesar

2017-03-04: A TLC workshop on Advanced Memory System Architecture, held at IIT Hyderabad

Professional Activity

Associate editor of Journal of Systems Architecture

Reviewer for:

Reviewed proposals for three European research-funding agencies.

TPC member of: VLSID 2020

ACM: Computing Surveys (3 times), TACO (2 times), TECS (2 times)

IEEE: TNNLS 2021, TAI 2020, TETC 2018, DATE 2018, DFT 2016, CAL (3 times), Intelligent Systems, ISVLSI, JETCAS, Trans. on Computers (2 times), Trans. On VLSI Systems, TCAD (2 times), DFT, HiPC student research symposium

Springer: Cluster Computing, J. of Supercomputing, Springer book High Performance Computing in Power and Energy Systems

Elsevier: a book

IET CDT, MDPI Sustainability, Concurrency and Computation (2 times), Frontiers in Marine Science


2019 Fall: CS2323 Computer architecture (100 students)

2019 Spring: CS6490 Hardware architectures for deep learning, , CS3523 Operating system (with 1 faculty) and Network security (with 2 faculty)

2018 Fall: CS2323 Computer architecture (121 students)

2018 Spring: Advanced computer architecture, CS3523 Operating system (with 1 faculty) and Network security (with 2 faculty)

2017 Fall: CS2323 (Computer Architecture)

2017 Spring: CS5360 Advanced computer architecture and CS3523 Operating system (with S. Peri)

2016 Fall: CS2323 Computer Architecture (with A. Franklin) and CS5410 Advanced memory system architecture

Student Mentoring

Graduate students:

Rujia Wang, University of Pittsburgh, USA 2016/05-2016/07

Seonglyong Gong, University of Texas, Austin, USA, 2016/05-2016/08

Matthew (Matt) Poremba, Penn State University, USA, 2014/06-2014/09

Undergraduate students:

Sai Susmita (NIT, Trichy), Madhuri Gupta (NIT, Sikkim), Alina Bhutia (NIT, Sikkim), Suparno Ghoshal (Heritage Inst of Tech.)

Technical Skills

Programming Languages/tools: C, C++, CUDA, Go (from Google), X10 (from IBM), Matlab, Simulink, System Generator (Xilinx), python, LaTeX, Gnuplot.

Architectural Simulators: Simplescalar, GEMS, Gem5, Sniper, MARSS, GPGPUSim.

Office Address

S-303, ECE Building, IIT Roorkee, Roorkee, Uttarakhand 247667