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Electronics and Electrical Engineering

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47
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3268
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Research.com Recognitions

  • 2011 - IEEE Fellow For contributions to high performance and low power digital circuits for microprocessors

Overview

Ram Krishnamurthy is affiliated with Intel in the United States, contributing extensively to the fields of engineering and computer science. Their research primarily spans electrical and electronic engineering, with a focus on hardware and architecture as well as several specialized subfields including computer vision and pattern recognition, artificial intelligence, and radiology, nuclear medicine, and imaging.

The scope of their scientific work covers multiple advanced topics, including:

  • Advanced Memory and Neural Computing
  • Low-power high-performance VLSI design
  • Advanced DC-DC Converters
  • Ferroelectric and Negative Capacitance Devices
  • Parallel Computing and Optimization Techniques
  • Multilevel Inverters and Converters
  • VLSI and Analog Circuit Testing

Krishnamurthy has published research in a variety of respected venues, notably:

  • IEEE Journal of Solid-State Circuits
  • IEEE Solid-State Circuits Letters
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
  • 2022 IEEE International Solid-State Circuits Conference (ISSCC)

Some of their recent papers include:

  • "DIMC: 2219TOPS/W 2569F2/b Digital In-Memory Computing Macro in 28nm Based on Approximate Arithmetic Hardware," 2022, 2022 IEEE International Solid-State Circuits Conference (ISSCC)
  • "A 617-TOPS/W All-Digital Binary Neural Network Accelerator in 10-nm FinFET CMOS," 2020, IEEE Journal of Solid-State Circuits
  • "A 4900-μm2 839-Mb/s Side-Channel Attack-Resistant AES-128 in 14-nm CMOS With Heterogeneous Sboxes, Linear Masked MixColumns, and Dual-Rail Key Addition," 2020, IEEE Journal of Solid-State Circuits
  • "An Eight-Core RISC-V Processor With Compute Near Last Level Cache in Intel 4 CMOS," 2022, IEEE Journal of Solid-State Circuits
  • "DIMCA: An Area-Efficient Digital In-Memory Computing Macro Featuring Approximate Arithmetic Hardware in 28 nm," 2023, IEEE Journal of Solid-State Circuits

Throughout their career, Krishnamurthy has collaborated frequently with several coauthors, including Gregory K. Chen, Phil Knag, Amit Agarwal, Mingoo Seok, and Mark Anders. These collaborations reflect a consistent engagement with experts across various subfields relevant to the integrated circuits and VLSI system design domain.

In recognition of their work, Krishnamurthy was named an IEEE Fellow in 2011. The award citation credits contributions to high performance and low power digital circuits designed for microprocessors.

Best Publications

  • Near-threshold voltage (NTV) design: opportunities and challenges

    Himanshu Kaul;Mark Anders;Steven Hsu;Amit Agarwal

  • 16.2 A 0.19pJ/b PVT-variation-tolerant hybrid physically unclonable function circuit for 100% stable secure key generation in 22nm CMOS

    Sanu K. Mathew;Sudhir K. Satpathy;Mark A. Anders;Himanshu Kaul

  • A sub-130-nm conditional keeper technique

    A. Alvandpour;R.K. Krishnamurthy;K. Soumyanath;S.Y. Borkar

  • A 4-GHz 130-nm address generation unit with 32-bit sparse-tree adder core

    S. Mathew;M. Anders;R.K. Krishnamurthy;S. Borkar

  • 2.4 Gbps, 7 mW All-Digital PVT-Variation Tolerant True Random Number Generator for 45 nm CMOS High-Performance Microprocessors

    S. K. Mathew;S. Srinivasan;M. A. Anders;H. Kaul

  • A 4096-Neuron 1M-Synapse 3.8-pJ/SOP Spiking Neural Network With On-Chip STDP Learning and Sparse Weights in 10-nm FinFET CMOS

    Gregory K. Chen;Raghavan Kumar;H. Ekin Sumbul;Phil C. Knag

  • 53 Gbps Native ${ m GF}(2 ^{4}) ^{2}$ Composite-Field AES-Encrypt/Decrypt Accelerator for Content-Protection in 45 nm High-Performance Microprocessors

    S K Mathew;F Sheikh;M Kounavis;S Gueron

  • 340 mV–1.1 V, 289 Gbps/W, 2090-Gate NanoAES Hardware Accelerator With Area-Optimized Encrypt/Decrypt GF(2 4 ) 2 Polynomials in 22 nm Tri-Gate CMOS

    Sanu Mathew;Sudhir Satpathy;Vikram Suresh;Mark Anders

  • Comparison of high-performance VLSI adders in the energy-delay space

    V.G. Oklobdzija;B.R. Zeydel;H.Q. Dao;S. Mathew

  • High-performance and low-power challenges for sub-70 nm microprocessor circuits

    R.K. Krishnarnurthy;A. Alvandpour;V. De;S. Borkar

  • A 320 mV 56 μW 411 GOPS/Watt Ultra-Low Voltage Motion Estimation Accelerator in 65 nm CMOS

    H. Kaul;M.A. Anders;S.K. Mathew;S.K. Hsu

  • A 4-GHz 300-mW 64-bit integer execution ALU with dual supply voltages in 90-nm CMOS

    S.K. Mathew;M.A. Anders;B. Bloechel;Trang Nguyen

  • An improved unified scalable radix-2 Montgomery multiplier

    D. Harris;R. Krishnamurthy;M. Anders;S. Mathew

  • A 4-fJ/b Delay-Hardened Physically Unclonable Function Circuit With Selective Bit Destabilization in 14-nm Trigate CMOS

    Sudhir Satpathy;Sanu K. Mathew;Vikram Suresh;Mark A. Anders

  • $\mu $ RNG: A 300–950 mV, 323 Gbps/W All-Digital Full-Entropy True Random Number Generator in 14 nm FinFET CMOS

    Sanu K. Mathew;David Johnston;Sudhir Satpathy;Vikram Suresh

  • A process variation compensating technique with an on-die leakage current sensor for nanometer scale dynamic circuits

    C.H. Kim;K. Roy;S. Hsu;R. Krishnamurthy

  • A 110 GOPS/W 16-bit multiplier and reconfigurable PLA loop in 90-nm CMOS

    S.K. Hsu;S.K. Mathew;M.A. Anders;B.R. Zeydel

  • Energy-delay estimation technique for high-performance microprocessor VLSI adders

    V.G. Oklobdzija;B.R. Zeydel;H. Dao;S. Mathew

  • A 130-nm 6-GHz 256 /spl times/ 32 bit leakage-tolerant register file

    R.K. Krishnamurthy;A. Alvandpour;G. Balamurugan;N.R. Shanbhag

  • Reconfigurable Computing: Architectures, Tools and Applications

    Andreas Koch;Ram Krishnamurthy;John McAllister;Roger Woods

Frequent Co-Authors

Sanu Mathew
Sanu Mathew Intel (United States)
Mark A. Anders
Mark A. Anders Intel (United States)
Shekhar Borkar
Shekhar Borkar Qualcomm (United States)
Vivek De
Vivek De Intel (United States)
Sasikanth Manipatruni
Sasikanth Manipatruni Intel (United States)
Vojin G. Oklobdzija
Vojin G. Oklobdzija University of California, Davis
Kaushik Roy
Kaushik Roy Purdue University West Lafayette
Dennis Sylvester
Dennis Sylvester University of Michigan–Ann Arbor
Siva G. Narendra
Siva G. Narendra Tyfone, Inc.
Chris H. Kim
Chris H. Kim University of Minnesota

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