ICRC 2023: THE 8TH IEEE INTERNATIONAL CONFERENCE ON REBOOTING COMPUTING (ICRC) 2023

A
Agarwal, Sapan	Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Agliamzanov, Ramil	Reducing Read Amplification and Re-synthesis in DNA-based Archival Storage
Ahle, Thomas	Thermodynamic Linear Algebra
Aifer, Maxwell	Thermodynamic Linear Algebra
Aimone, James	Synaptic Sampling of Neural Networks Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
Akinaga, Hiro	Beyond CMOS/Emerging Materials Integration with ties to ESHS and Energy Harvesting
Anderson, Jilian	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Angizi, Shaahin	Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator
Arzate, Jared	Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
B
Balbuena, Perla	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Beerel, Peter	Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence
Beltran, Saul Perez	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Bennett, Christopher	Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Besiroglu, Tamay	Limits to the Energy Efficiency of CMOS Microprocessors
Bhattacharyya, Bikrant	Optimal Clifford Initial States for Ising Hamiltonians
Bhattacharyya, Swagat	BuzzSort: A Linear-Time, Event-Driven Data Conversion and Sorting Framework for Approximate Computing Architectures
Bishop, Sean	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Breternitz, Mauricio	Dendrite-inspired Computing to improve Resilience of Neural Networks to Faults in Emerging Memory Technologies
Brown, Timothy D.	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
C
Cady, Nathaniel	Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator
Cardwell, Suma	Enhancing Spiking Deep Learning with Dendrites This Is The Way: Routing Neuroscience to Neuromorphic Applications Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
Chance, Frances	Enhancing Spiking Deep Learning with Dendrites This Is The Way: Routing Neuroscience to Neuromorphic Applications
Chaudhary, Vipin	Accelerating VQE Algorithm via Parameters and Measurement Reuse
Chowdhury, Zamshed	PimCity: A Compute in Memory Substrate featuring both Row and Column Parallel Computing
Cilasun, Husrev	PimCity: A Compute in Memory Substrate featuring both Row and Column Parallel Computing
Coles, Patrick	Thermodynamic AI and the Fluctuation Frontier
Coles, Patrick	Thermodynamic Linear Algebra
Crimmins, Aden	Quantum Array Multiplier
Crooks, Gavin	Thermodynamic Linear Algebra
Crowder, Douglas	Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
D
Daly, John	Design of General Purpose Minimal-Auxiliary Ising Machines
Date, Prasanna	Arithmetic Primitives for Efficient Neuromorphic Computing An FPGA-based Neuromorphic Processor with All-To-All Connectivity
Datta, Gourav	Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence
Di Ventra, Massimiliano	Reconfigurable functionalities for neuromorphic computing
Donatella, Kaelan	Thermodynamic AI and the Fluctuation Frontier Thermodynamic Linear Algebra
Dutra, Diego	Dendrite-inspired Computing to improve Resilience of Neural Networks to Faults in Emerging Memory Technologies
E
Erdil, Ege	Limits to the Energy Efficiency of CMOS Microprocessors
F
Finnegan, Patrick	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Franca, Felipe	Dendrite-inspired Computing to improve Resilience of Neural Networks to Faults in Emerging Memory Technologies
Fuller, Elliot J.	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
G
Gargini, Paolo	Welcome and IRDS Past, Present, and Future The Engine of the Chips Acts Around the World Closing Remarks
Gilbert, Nad	Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Givargis, Tony	RefineHD: Accurate and Efficient Single-Pass Adaptive Learning Using Hyperdimensional Computing
H
Hansen, Ethan	Accelerating VQE Algorithm via Parameters and Measurement Reuse
Hashimoto, Masanori	Performance comparison of memristor crossbar-based analog and FPGA-based digital weight-memory-less neural networks A Proof-of-Concept Prototyping of Reservoir Computing with Quantum Dots and an Image Sensor for Image Classification
Hasler, Jennifer	BuzzSort: A Linear-Time, Event-Driven Data Conversion and Sorting Framework for Approximate Computing Architectures
Hayes, John	Mitigating the Correlation Problem in Multi-Layer Stochastic Circuits
Ho, Anson	Limits to the Energy Efficiency of CMOS Microprocessors
Hoffend, Owen	Mitigating the Correlation Problem in Multi-Layer Stochastic Circuits
Hovland, Paul	Accelerating VQE Algorithm via Parameters and Measurement Reuse
Hunter Gordon, Max	Thermodynamic Linear Algebra
Hylton, Todd	A Crisis in Computing
I
Ievlev, Anton	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Ilov, Alex	High-Speed Compilation of Large-Scale Stochastic Circuits
Imani, Mohsen	Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator
Incorvia, Jean Anne	Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
J
Jacob, Ajey	Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence
Jacobs-Gedrim, Robin	Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Jaiswal, Akhilesh	Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence
John, Eugene B.	Dendrite-inspired Computing to improve Resilience of Neural Networks to Faults in Emerging Memory Technologies
John, Lizy K.	Dendrite-inspired Computing to improve Resilience of Neural Networks to Faults in Emerging Memory Technologies
K
Kaiser, Md	Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence
Karpuzcu, Ulya	PimCity: A Compute in Memory Substrate featuring both Row and Column Parallel Computing
Kate, Sagar	Quantum Array Multiplier
Kawa, Jamil	Low Temperature Hybrid Electronics for Next Generation Computing
Kawano, Chinamu	Performance comparison of memristor crossbar-based analog and FPGA-based digital weight-memory-less neural networks
Khare, Rishabh	A Memcomputing Approach to Prime Factorization
Kim, Jungsang	Prospect for Practical Applications using Quantum Computers
Klein, Matthew	Quantum Array Multiplier
Krebs, Matthew	Quantum Array Multiplier
Kulkarni, Shruti R.	Arithmetic Primitives for Efficient Neuromorphic Computing An FPGA-based Neuromorphic Processor with All-To-All Connectivity
Kumar, Suhas	Memristor-Based Dual Conditional In-Memory Computing
Kumar, Suhas	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Kwon, Jaesuk	Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
Kyrillidis, Anastasios	Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat
L
Li, Xinpeng	Accelerating VQE Algorithm via Parameters and Measurement Reuse
Liehr, Maximilian	Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator
Lima, Priscila	Dendrite-inspired Computing to improve Resilience of Neural Networks to Faults in Emerging Memory Technologies
Liu, Ji	Accelerating VQE Algorithm via Parameters and Measurement Reuse
Lopez Alarcon, Sonia	Quantum Array Multiplier
M
Maan, Arshpreet	Testing the Accuracy of Surface Code Decoders
Maheshwari, Disha	An FPGA-based Neuromorphic Processor with All-To-All Connectivity
Maicke, Andrew	Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
Marinella, Matthew	Beyond CMOS Technology Issues and Critical Considerations Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Martin, Isaac	Design of General Purpose Minimal-Auxiliary Ising Machines
Martinez, Antonio	Thermodynamic AI and the Fluctuation Frontier
Matsumoto, Takuto	A Proof-of-Concept Prototyping of Reservoir Computing with Quantum Dots and an Image Sensor for Image Classification
Melanson, Denis	Thermodynamic AI and the Fluctuation Frontier
Meyer, Jess	Design of General Purpose Minimal-Auxiliary Ising Machines
Miniskar, Narasinga Rao	An FPGA-based Neuromorphic Processor with All-To-All Connectivity
Miranda, Igor	Dendrite-inspired Computing to improve Resilience of Neural Networks to Faults in Emerging Memory Technologies
Mitra, Subhasish	Dendrite-inspired Computing to improve Resilience of Neural Networks to Faults in Emerging Memory Technologies
Moflic, Ioana	Cost Explosion for Efficient Reinforcement Learning Optimisation of Quantum Circuits
Moore, Andrew	Design of General Purpose Minimal-Auxiliary Ising Machines
Morsali, Mehrdad	Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator
N
Nicolau, Alexandru	RefineHD: Accurate and Efficient Single-Pass Adaptive Learning Using Hyperdimensional Computing
O
Oh, Sangheon	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
P
Paler, Alexandru	Cost Explosion for Efficient Reinforcement Learning Optimisation of Quantum Circuits High-Speed Compilation of Large-Scale Stochastic Circuits Testing the Accuracy of Surface Code Decoders
Patel, Karan	Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
Pederson, Erick	A Memcomputing Approach to Prime Factorization
Plagge, Mark	Enhancing Spiking Deep Learning with Dendrites
Premaratne, Shavindra	Intel Quantum SDK: Hybrid Quantum-Classical Programming Tools
Q
Qiu, Erbin	Reconfigurable functionalities for neuromorphic computing
Quiroga, David A.	Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat
R
Ranadive, Teresa	Design of General Purpose Minimal-Auxiliary Ising Machines
Rasch, Kevin	Intel Quantum SDK: Hybrid Quantum-Classical Programming Tools
Ravi, Gokul Subramanian	Optimal Clifford Initial States for Ising Hamiltonians
Resch, Salonik	PimCity: A Compute in Memory Substrate featuring both Row and Column Parallel Computing
Roohi, Arman	Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator
S
Sapatnekar, Sachin S.	PimCity: A Compute in Memory Substrate featuring both Row and Column Parallel Computing
Sbahi, Faris	Thermodynamic AI and the Fluctuation Frontier
Schuller, Ivan K	Reconfigurable functionalities for neuromorphic computing
Schuman, Catherine	Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
Seay, Rebecca	Arithmetic Primitives for Efficient Neuromorphic Computing
Severa, William	Synaptic Sampling of Neural Networks
Sharp, Tristan	A Memcomputing Approach to Prime Factorization
Shirai, Ryo	A Proof-of-Concept Prototyping of Reservoir Computing with Quantum Dots and an Image Sensor for Image Classification
Short, Jesse	Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Simpson, Daniel	Thermodynamic Linear Algebra
Smith, J. Darby	Synaptic Sampling of Neural Networks Device Discovery for Magnetic Tunnel Junctions using Reinforcement Learning
Spear, Matthew	Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Sugar, Joshua	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Susskind, Zachary	Dendrite-inspired Computing to improve Resilience of Neural Networks to Faults in Emerging Memory Technologies
Szczepanski, Collin	Thermodynamic AI and the Fluctuation Frontier
T
Tabrizchi, Sepehr	Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator
Talin, A. Alec	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Teuscher, Christof	Unconventional Computing's False Promises?
Traversa, Fabio	A Memcomputing Approach to Prime Factorization
Tuck, James M.	Reducing Read Amplification and Re-synthesis in DNA-based Archival Storage
U
Ushijima-Mwesigwa, Hayato	Clustering Vehicle Routing Problems on Specialized Hardware
V
Vergés, Pere	RefineHD: Accurate and Efficient Single-Pass Adaptive Learning Using Hyperdimensional Computing
Vetter, Jeffrey	Deep Codesign in the Post-Exascale Computing Era Arithmetic Primitives for Efficient Neuromorphic Computing
W
Wahby, William	Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Wang, Jian-Ping	PimCity: A Compute in Memory Substrate featuring both Row and Column Parallel Computing
Whiteley, Stephen	Low Temperature Hybrid Electronics for Next Generation Computing
Williams, R. Stanley	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing
Williams, R. Stanley	Memristor-Based Dual Conditional In-Memory Computing
Wilson, Donald	Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Witherspoon, Brett	An FPGA-based Neuromorphic Processor with All-To-All Connectivity
Woo, Kyung Seok	Memristor-Based Dual Conditional In-Memory Computing
Wu, Xin-Chuan	Intel Quantum SDK: Hybrid Quantum-Classical Programming Tools
Wurm, Ahna	Arithmetic Primitives for Efficient Neuromorphic Computing
X
Xiao, Tianyao	Statistical Characterization of ReRAM Arrays for Analog In-Memory Computing
Xu, Hanjing	Clustering Vehicle Routing Problems on Specialized Hardware
Xu, Shuai	Accelerating VQE Algorithm via Parameters and Measurement Reuse
Y
Yang, Linhao	BuzzSort: A Linear-Time, Event-Driven Data Conversion and Sorting Framework for Approximate Computing Architectures
Yin, Zihan	Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence
Young, Aaron	Arithmetic Primitives for Efficient Neuromorphic Computing An FPGA-based Neuromorphic Processor with All-To-All Connectivity
Z
Zabihi, Masoud	PimCity: A Compute in Memory Substrate featuring both Row and Column Parallel Computing
Zhang, Yuan-Hang	Reconfigurable functionalities for neuromorphic computing
Zhao, Zhengyang	PimCity: A Compute in Memory Substrate featuring both Row and Column Parallel Computing
Zutter, Brian	Dynamically Reconfigurable Electrochemical Random Access Memory Device for Neuromorphic Computing

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