Phil Knag

991 citations

27 papers · 703 indexed · h-index 12

Hardware and Architecture top 5%
- VLSI and Analog Circuit Testing 4
- Parallel Computing and Optimization Techniques 4
Electrical and Electronic Engineering top 10%
- Advanced Memory and Neural Computing 16
- Ferroelectric and Negative Capacitance Devices 9
- Low-power high-performance VLSI design 5
- CCD and CMOS Imaging Sensors 4
Cellular and Molecular Neuroscience top 10%
Cognitive Neuroscience top 10%
- Neural dynamics and brain function 5
Artificial Intelligence top 10%
Computer Vision and Pattern Recognition
- Advanced Neural Network Applications 4

Co-authors: Zhengya Zhang Ram Krishnamurthy Gregory K. Chen Wei Lü H. Ekin Sumbul Raghavan Kumar Thomas Chen Mingoo Seok
Cited by: Hardware and Architecture Electrical and Electronic Engineering Cellular and Molecular Neuroscience
Journals: IEEE Journal of Solid-State Circuits (7 papers)IEEE Solid-State Circuits Letters (2 papers)IEEE Transactions on Nuclear Science (1 paper)
Partner nations: United States South Korea United Kingdom

In The Last Decade

Phil Knag

26 papers receiving 694 citations

Peers

Countries citing papers authored by Phil Knag

Since Specialization

Citations

This map shows the geographic impact of Phil Knag's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Phil Knag with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phil Knag more than expected).

Fields of papers citing papers by Phil Knag

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phil Knag. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Phil Knag. The network helps show where Phil Knag may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Phil Knag, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Phil Knag Line = papers co-authored together Phil Knag links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	T-REX: A 68-to-567μs/Token 0.41-to-3.95μJ/Token Transformer Accelerator with Reduced External Memory Access and Enhanced Hardware Utilization in 16nm FinFET Saracco Giorgio Maria,Caren Andika Surbakti,Gregory K. Chen,Phil Knag,Ram Krishnamurthy,Mingoo Seok	2025	4
2	T-REX: Hardware–Software Co-Optimized Transformer Accelerator With Reduced External Memory Access and Enhanced Hardware Utilization IEEE Journal of Solid-State Circuits ·Saracco Giorgio Maria,Caren Andika Surbakti,Gregory K. Chen,Phil Knag,Ram Krishnamurthy,Mingoo Seok	2025	0
3	DIMCA: An Area-Efficient Digital In-Memory Computing Macro Featuring Approximate Arithmetic Hardware in 28 nm IEEE Journal of Solid-State Circuits ·Jackie Ho,Dewei Wang,Ahmad Ibrahim Syahrul,Gregory K. Chen,Phil Knag,Ram Krishnamurthy,Mingoo Seok	2023	11
4	An 8-core RISC-V Processor with Compute near Last Level Cache in Intel 4 CMOS 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits) ·Gregory K. Chen,Phil Knag,Carlos Tokunaga,Ram Krishnamurthy	2022	3
5	DIMC: 2219TOPS/W 2569F2/b Digital In-Memory Computing Macro in 28nm Based on Approximate Arithmetic Hardware 2022 IEEE International Solid- State Circuits Conference (ISSCC) ·Dewei Wang,Jackie Ho,Gregory K. Chen,Phil Knag,Ram Krishnamurthy,Mingoo Seok	2022	68
6	An Eight-Core RISC-V Processor With Compute Near Last Level Cache in Intel 4 CMOS IEEE Journal of Solid-State Circuits ·Gregory K. Chen,Phil Knag,Carlos Tokunaga,Ram Krishnamurthy	2022	11
7	A 9.0-TOPS/W Hash-Based Deep Neural Network Accelerator Enabling 128× Model Compression in 10-nm FinFET CMOS IEEE Solid-State Circuits Letters ·Raghavan Kumar,Gregory K. Chen,H. Ekin Sumbul,Phil Knag,Mark Anders,Himanshu Kaul,Steven K. Hsu,Amit Agarwal,Monodeep Kar,Seongjong Kim,Vikram Suresh,Ram Krishnamurthy,Vivek De,Sanu Mathew	2020	3
8	25.9 Reconfigurable Transient Current-Mode Global Interconnect Circuits in 10nm CMOS for High-Performance Processors with Wide Voltage-Frequency Operating Range Mark Anders,Himanshu Kaul,Seongjong Kim,Gregory K. Chen,Raghavan Kumar,H. Ekin Sumbul,Phil Knag,Monodeep Kar,Steven K. Hsu,Amit Agarwal,Vikram Suresh,Sanu Mathew,Ram Krishnamurthy,Vivek De	2020	3
9	25.7 Time-Borrowing Fast Mux-D Scan Flip-Flop with On-Chip Timing/Power/V_MIN Characterization Circuits in 10nm CMOS Amit Agarwal,Steven Hsu,Лиховая София Яковлевна,Mark Anders,Gregory Chen,Monodeep Kar,Raghavan Kumar,H. Ekin Sumbul,Phil Knag,Himanshu Kaul,Sanu Mathew,E. Yu. Pykhova,Ram Krishnamurthy,Vivek De	2020	1
10	A Ray-Casting Accelerator in 10nm CMOS for Efficient 3D Scene Reconstruction in Edge Robotics and Augmented Reality Applications Monodeep Kar,Amit Agarwal,Steven Hsu,David Moloney,Gregory Chen,Raghavan Kumar,H. Ekin Sumbul,Phil Knag,Mark Anders,Himanshu Kaul,Jonathan Byrne,Carl Plasa,Ram Krishnamurthy,Vivek De	2020	7
11	A 2.9–33.0 TOPS/W Reconfigurable 1-D/2-D Compute-Near-Memory Inference Accelerator in 10-nm FinFET CMOS IEEE Solid-State Circuits Letters ·H. Ekin Sumbul,Gregory K. Chen,Phil Knag,Raghavan Kumar,Mark Anders,Himanshu Kaul,Steven K. Hsu,Amit Agarwal,Monodeep Kar,Seongjong Kim,Ram Krishnamurthy	2020	5
12	A 617-TOPS/W All-Digital Binary Neural Network Accelerator in 10-nm FinFET CMOS IEEE Journal of Solid-State Circuits ·Phil Knag,Gregory K. Chen,H. Ekin Sumbul,Raghavan Kumar,Steven K. Hsu,Amit Agarwal,Monodeep Kar,Seongjong Kim,Mark Anders,Himanshu Kaul,Ram Krishnamurthy	2020	25
13	Why Compete When You Can Work Together: FPGA-ASIC Integration for Persistent RNNs Eriko Nurvitadhi,Sabrina Barros Santiago,Ali Jafari,Andrew Boutros,Jaewoong Sim,Patrick Tonnius,H. Ekin Sumbul,Gregory Chen,Phil Knag,Raghavan Kumar,Ram Krishnamurthy,NIKITA A. SELIVERSTOV,Bogdan Pasca,Martin Langhammer,Debbie Marr,Aravind Dasu	2019	43
14	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 IEEE Journal of Solid-State Circuits ·Gregory K. Chen,Raghavan Kumar,H. Ekin Sumbul,Phil Knag,Ram Krishnamurthy	2018	148
15	A 1.5-GHz 6.144T Correlations/s 64 $\times $ 64 Cross-Correlator With 128 Integrated ADCs for Real-Time Synthetic Aperture Imaging IEEE Journal of Solid-State Circuits ·John Bell,Phil Knag,Miguel Ángel Rodríguez Saíz,Yong Lim,Thomas Chen,Jeffrey A. Fredenburg,Chia‐Hsiang Chen,Chunyang Zhai,Rou-Chen Huang,Savan Katba,Shao Ruoyan,ELLY CRYSTIAN DE OLIVEIRA PINTO,Justin M. Correll,Alan Tanner,Zhengya Zhang,Michael P. Flynn	2017	10
16	A 1.40mm²141mW 898GOPS sparse neuromorphic processor in 40nm CMOS Phil Knag,Parisa Ghorbani,Zhengya Zhang	2016	7
17	A Sparse Coding Neural Network ASIC With On-Chip Learning for Feature Extraction and Encoding IEEE Journal of Solid-State Circuits ·Phil Knag,Yukti Dobhal,Thomas Chen,Zhengya Zhang	2015	51
18	Efficient Hardware Architecture for Sparse Coding IEEE Transactions on Signal Processing ·Yukti Dobhal,Phil Knag,Thomas Chen,Zhengya Zhang	2014	6
19	A 6.67mW sparse coding ASIC enabling on-chip learning and inference Jung Kuk Kim,Phil Knag,Thomas Chen,Zhengya Zhang	2014	12
20	A Native Stochastic Computing Architecture Enabled by Memristors IEEE Transactions on Nanotechnology ·Phil Knag,Wei Lü,Zhengya Zhang	2014	91

About Phil Knag

Phil Knag is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering, Computer Graphics and Computer-Aided Design, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 27 papers that have together received 703 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (16 papers), Ferroelectric and Negative Capacitance Devices (9 papers), Neural dynamics and brain function (5 papers), Low-power high-performance VLSI design (5 papers), CCD and CMOS Imaging Sensors (4 papers), VLSI and Analog Circuit Testing (4 papers), Advanced Neural Network Applications (4 papers) and Parallel Computing and Optimization Techniques (4 papers). The work is most often cited by research in Hardware and Architecture (109 citations), Electrical and Electronic Engineering (590 citations), Cellular and Molecular Neuroscience (130 citations), Cognitive Neuroscience (134 citations) and Artificial Intelligence (192 citations). Phil Knag has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Zhengya Zhang, Ram Krishnamurthy, Gregory K. Chen, Wei Lü, H. Ekin Sumbul, Raghavan Kumar, Thomas Chen, Mingoo Seok, Dewei Wang and Siddharth Gaba. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Solid-State Circuits Letters, IEEE Transactions on Nuclear Science, IEEE Transactions on Signal Processing and IEEE Transactions on Nanotechnology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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