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NICE 2024 - Agenda

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Tuesday, 23 April 2024
08:00
NICE 2024-- day 1

NICE 2024

Registration

For registration, please see the registration options and link to the registration form.

Venue

show a map with the two venues and the hotels.

Hotel with special rates

These hotels offer special rates for the NICE attendants (see the map above for location information, deadline to book is 9 April 2024 or until the room block is filled):

  • La Jolla Shores Hotel (closest to the conference venue with a NICE stroll at the seaside and with nearby restaurants) , 8110 Camino Del Oro, La Jolla, CA 92037: $355.06 / night (inclusive of taxes and fees), does not include parking.
    Reservation link for the La Jolla Shores to get the special rate. To book up to two days prior or after the conference (subject to availability), please call +1 866-976-6659 and refer to the UCSD - NICE 2024
  • Embassy Suites by Hilton San Diego, 4550 La Jolla Village Dr., San Diego, CA 92122, $269.42 / night (inclusive of taxes – resort fees are waived for the reservation), does not include parking.. Depending on room availability it is also possible to extend the booking three days prior or after the conference
    Reservation link for the Hilton to get the special rate
  • Residence Inn by Marriott, 8901 Gilman Dr., La Jolla, CA 92037: $291.70 / night (inclusive of taxes and fees), does not include parking.
    Reservation link for the Marriott to get the special rate.
08:00

NICE 2024 agenda

Times listed are Pacific Daylight Time (PDT), and are subject to change.

It is also possible to show the agenda with other time zones listed, which are relevant for: Africa, America, Australia, China, Europe, India, Japan

08:00‑08:30
(30 min)
 Registration and breakfast
08:30‑08:45
(15+5 min)
 Welcome and opening

.ics

Gert Cauwenberghs, Duygu Kuzum, Tajana Rosing (Institute for Neural Computation and Jacobs School of Engineering, UC San Diego)
Miroslav Krstić (Associate Vice Chancellor for Research, UC San Diego)
08:50‑09:35
(45+5 min)
 Organisers round

.ics

Members of the organising committees
09:40‑10:25
(45+5 min)
 Keynote: Brains and AI

.ics

Terry Sejnowski (Salk Institute for Biological Studies)
10:30‑11:00
(30 min)
 Break
11:00‑11:25
(25+5 min)
 Biological Dynamics Enabling Training of Binary Recurrent Networks

show abstract

.ics

William Chapman (Sandia National Laboratories)
11:30‑11:40
(10+5 min)
 Towards Convergence Intelligence – neuromorphic engineering and engineered organoids for neurotechnology

show abstract

.ics

Dr. Grace Hwang (Program Director, National Institutes of Health (NIH)/National Institute of Neurological Disorders and Stroke (NINDS)/ U.S. BRAIN Initiative)
11:45‑12:10
(25+5 min)
 Invited talk: Learning algorithms for spiking and physical neural networks

show abstract

.ics

Friedemann Zenke (Friedrich Miescher Institute for Biomedical Research & University of Basel)
12:15‑12:30
(15 min)
 Poster teasers

1-min "this is my poster content" teasers

  • Shelah O. Ameli
  • Kanha Batra/ Jiaqi Zhang
  • Mario De Florio and Adar Kahana
  • Michael Furlong
  • David Mascarenas
  • Sonia Mazelot
  • Roy Moyal
  • Zoran Utkovski
  • Alaaddin Goktug Ayar
  • Jason Yik

.ics

12:30‑14:00
(90 min)
 Poster-lunch (posters + finger food)



Maximum possible poster size: landscape, 48 inch x 70 inch.

Posters

  • Shelah O. Ameli: Leveraging Programmable Plasticity on Neuromorphic Hardware
  • Roy Moyal: A Neuromorphic Algorithm for Dynamic Contrast Optimization
  • David Mascarenas: Beating 2 Sides of the Exposure Triangle in Post Processing with Neuromorphic Imager Arrays
  • Mario De Florio and Adar Kahana: Analysis of biologically plausible neuron models for regression with spiking neural networks
  • Zoran Utkovski: Neuromorphic Wireless Device-Edge Co-Inference via the Directed Information Bottleneck
  • Michael Furlong: Sparse fractional power encoding for fixed-point neuromorphic hardware.

Talk-Posters

  • William Chapman: "Biological Dynamics Enabling Training of Binary Recurrent Networks"
  • Alaaddin Goktug Ayar: "Brain-Inspired Hypervector Processing at the Edge of Large Language Models"
  • Jason Yik: NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems
  • Kanha Batra/ Jiaqi Zhang: "Neuromodulated Mixture of Experts: A prefrontal cortex inspired architecture for lifelong learning"
  • Sonia Mazelot: "Compositional Factorization of Visual Scenes with Convolutional Sparse Coding and Resonator Networks"
14:00‑14:25
(25+5 min)
 SQUAT: Stateful Quantization-Aware Training in Recurrent Spiking Neural Networks

show abstract

.ics

Sreyes Venkatesh (UC Santa Cruz)
14:30‑14:40
(10+5 min)
 Expressive Dendrites in Spiking Networks

show abstract

.ics

Mark Plagge (Sandia National Laboratories)
14:45‑15:10
(25+5 min)
 Text-to-Events: Synthetic Event Camera Streams from Conditional Text Input

show abstract

.ics

Shih-Chii Liu (Institute of Neuroinformatics, University of Zurich and ETH Zurich)
15:15‑15:45
(30 min)
 Break
15:45‑16:10
(25+5 min)
 Embracing the Hairball: An Investigation of Recurrence in Spiking Neural Networks for Control

show abstract

.ics

Katie Schuman (University of Tennessee)
16:15‑17:00
(45 min)
 Open mic / discussion -- day I speakers

.ics

17:00‑18:00
(60 min)
 Misha Mahowald Prizes
  • Misha Mahowald Recognition of Lifetime Contribution to Neuromorphic Engineering:
    Carver Mead, Gordon and Betty Moore Professor Emeritus of Engineering and Applied Science at the California Institute of Technology

  • 2023 Misha Mahowald Prize:
    James Bradley Aimone, Brian C. Franke, Richard B. Lehoucq, Michael C. Krygier, Aaron J. Hill, Ojas Parekh, Leah E. Reeder, William Severa, and J. Darby Smith, Sandia National Laboratory

.ics

18:00‑19:00
(60 min)
 Reception and celebration of 35+ years of neuromorphic engineering

Wednesday, 24 April 2024
08:00
NICE 2024 - Day II
08:00‑08:30
(30 min)
 Breakfast
08:30‑09:15
(45+5 min)
 Keynote: Hearing with Silicon Cochleas

.ics

Shih-Chii Liu (Institute of Neuroinformatics, University of Zurich and ETH Zurich)
09:20‑09:30
(10+5 min)
 Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning

show abstract

.ics

Shruti R Kulkarni (Oak Ridge National Laboratory)
09:35‑10:00
(25+5 min)
 Invited talk: Hardware Accelerators for Brain-Inspired Computing

.ics

John Arthur (IBM Research)
10:05‑10:30
(25+5 min)
 Hardware-aware Few-shot Learning on a Memristor-based Small-world Architecture

show abstract

.ics

Karthik Charan Raghunathan (Institute of Neuroinformatics, ETH and UZH Zurich)
10:35‑11:05
(30 min)
 Break
11:05‑11:30
(25+5 min)
 Spiking Physics-Informed Neural Networks on Loihi-2

.ics

Brad Theilman (Sandia National Laboratories)
11:35‑11:45
(10+5 min)
 jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic Hardware

show abstract

.ics

Eric Müller (BrainScaleS, Heidelberg University)
11:50‑12:00
(10+5 min)
 Late-breaking-news: Distributed Neural State Machines on Loihi 2

show abstract

.ics

Alpha Renner (Forschungszentrum Jülich, Germany)
12:05‑12:20
(15 min)
 Poster teasers 1-min "this is my poster content" teasers
  • Patrick Abbs
  • Sai Sukruth Bezugam
  • Gwenevere Frank
  • Christopher Kymn
  • Srideep Musuvathy
  • Lars Niedermeier:
  • Joey Randich
  • Nancy Ronquillo
  • Bernard Vogginger
  • Felix Wang
  • Katy Warr

.ics

12:20‑12:30
(10 min)
 Group photo

.ics

12:30‑14:00
(90 min)
 Poster-lunch (posters + finger food)



Maximum possible poster size: landscape, 48 inch x 70 inch.

Posters

  • Bernard Vogginger: Neuromorphic hardware for sustainable AI data centers
  • Gwenevere Frank: HiAER-Spike: Hardware-Software Co-Design for Large-Scale Reconfigurable Event-Driven Neuromorphic Computing
  • Lars Niedermeier: An Integrated Toolbox for Creating Neuromorphic Edge Applications
  • Srideep Musuvathy: A Spiking Neural Algorithm for Markov RewardProcesses
  • Joey Randich: Leaky Integrate-and-Fire Neuron as an Analog-to-Digital Converter
  • Nancy Ronquillo: Exploiting Cognitive State EEG Datasets with Transfer Learning
  • Katy Warr: Optimising Sparse Associative Memory with Neurogenesis for Accuracy and Deployment

Talk-Posters

  • Alpha Renner: "Neuromorphic Hyperdimensional Computing" *- Sai Sukruth Bezugam: "Quantized Context Based LIF Neurons for Recurrent Spiking Neural Networks in 45nm"
  • Patrick Abbs: "One-Shot Auditory Blind Source Separation via Local Learning in a Neuromorphic Network"
  • Sai Sukruth Bezugam: "Quantized Context Based LIF Neurons for Recurrent Spiking Neural Networks in 45nm"
  • Christopher Kymn: "Compositional Factorization of Visual Scenes with Convolutional Sparse Coding and Resonator Networks"
  • Felix Wang: "STACS: Simulation Tool for Asynchronous Cortical Streams"
14:00‑14:10
(10+5 min)
 Quantized Context Based LIF Neurons for Recurrent Spiking Neural Networks in 45nm

show abstract

.ics

Sai Sukruth Bezugam (Department of Electrical and Computer Engineering, University of California Santa Barbara)
14:15‑14:40
(25+5 min)
 Compositional Factorization of Visual Scenes with Convolutional Sparse Coding and Resonator Networks

show abstract

.ics

Chris Kymn (UC Berkeley)
14:45‑14:55
(10+5 min)
 Towards Chip-in-the-loop Spiking Neural Network Training via Metropolis-Hastings Sampling

show abstract

.ics

Ali Safa (imec and KU Leuven)
15:00‑15:30
(30 min)
 Break
15:30‑15:40
(10+5 min)
 Leveraging Sparsity of SRNNs for Reconfigurable and Resource-Efficient Network-on-Chip

show abstract

.ics

Manu Rathore (TENNLab - Neuromorphic Architectures, Learning, Applications (The University of Tennessee, Knoxville))
15:45‑16:10
(25+5 min)
 Invited talk: Towards fractional order dynamics neuromorphic elements

show abstract

.ics

Fidel Santamaria (Department of Neuroscience, Developmental and Regenerative Biology, University of Texas at San Antonio)
16:15‑16:25
(10+5 min)
 Compute-in-Memory with 6T-RRAM Memristive Circuit for Next-Gen Neuromorphic Hardware

show abstract

.ics

Kang Jun Bai (Air Force Research Laboratory)
16:30‑17:30
(60 min)
 Open mic / discussion - day II speakers

.ics

17:30
End of the second day

Thursday, 25 April 2024
08:00
Day III
08:00‑08:30
(30 min)
 Breakfast
08:30‑09:15
(45+5 min)
 Keynote: NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems

show abstract

.ics

Jason Yik (School of Engineering and Applied Sciences, Harvard)
09:20‑10:20
(60 min)
 IEEE EMBS special session: forum on AI for health care

.ics

Metin Akay and Gert Cauwenberghs (IEEE EMBS and University of Houston and UC San Diego)
10:20‑10:50
(30 min)
 Break
10:50‑11:00
(10+5 min)
 One-Shot Auditory Blind Source Separation via Local Learning in a Neuromorphic Network

show abstract

.ics

Patrick Abbs (Cambrya, LLC)
11:05‑11:30
(25+5 min)
 Invited talk: TENN: A highly efficient transformer replacement for edge and event processing.

.ics

M Anthony Lewis, Yan Ru Pei and Olivier Coenen (BrainChip)
11:35‑11:45
(10+5 min)
 A Recurrent Dynamic Model for Efficient Bayesian Optimization

show abstract

.ics

P. Michael Furlong (Centre for Theoretical Neuroscience/Systems Design Engineering, University of Waterloo)
11:50‑12:15
(25+5 min)
 Invited talk: Strategic & Large-Scale Considerations of Neuromorphic Computing

show abstract

.ics

Craig Vineyard (Sandia National Laboratory)
12:20‑12:30
(10+5 min)
 GPU-RANC: A CUDA Accelerated Simulation Framework for Neuromorphic Architectures

show abstract

.ics

Joshua Mack (Department of Electrical & Computer Engineering, University of Arizona)
12:35‑13:35
(60 min)
 Lunch
13:35‑13:45
(10+5 min)
 Late-breaking-news: Neuromodulated mixture of experts: A prefrontal cortex inspired architecture for lifelong learning

show abstract

.ics

Clara Yi (Salk Institute for Biological Studies)
13:50‑14:15
(25+5 min)
 Energy Efficient Implementation of MVM Operations Using Filament-free Bulk RRAM Arrays

show abstract

.ics

Dr. Ashwani Kumar (Electrical and Computer Engineering, UC San Diego)
14:20‑14:30
(10+5 min)
 TickTockTokens: a minimal building block for event-driven systems

.ics

Johannes Leugering (Institute for Neural Computation, Bioengineering Dept., UC San Diego)
14:35‑14:45
(10+5 min)
 Late-breaking-news: Brain-Inspired Hypervector Processing at the Edge of Large Language Models

.ics

Alaaddin Goktug Ayar (University of Louisiana at Lafayette)
14:50‑15:20
(30 min)
 Coffee break
15:20‑15:30
(10+5 min)
 Spiking Neural Network-based Flight Controller

show abstract

.ics

Diego Chavez Arana (New Mexico State University)
15:35‑16:00
(25+5 min)
 PETNet– Coincident Particle Event Detection using Spiking Neural Networks

show abstract

.ics

Jan Debus (ETH Zurich)
16:05‑16:15
(10+5 min)
 NeRTCAM: CAM-Based CMOS Implementation of Reference Frames for Neuromorphic Processors

show abstract

.ics

Harideep Nair (Carnegie Mellon University.)
16:20‑17:20
(60 min)
 Open mic / discussion - day III speakers

.ics

17:20‑17:30
(10 min)
 Final words -- invitation to NICE 2025

.ics

17:30
End of day 3 and of the talk-days of NICE 2024

Friday, 26 April 2024
08:30
Tutorial day

Venue

The tutorial day takes place at the San Diego Supercomputer Center SDSC (SDSC visitor information page)

Tutorials are in the SDSC Auditorium. The auditorium will be partitioned into three sections so there can be three parallel tutorials in each time slot.

Tutorials

These 9 tutorial suggestions have been selected.

  • Hands-on tutorial: BrainScaleS neuromorphic compute system (via the EBRAINS Research Infrastructure )
  • An Introduction to Design and Simulation using SNS-Toolbox and SNSTorch
  • Simulation Tool for Asynchronous Cortical Streams (STACS)
  • N2A – neural programming language and workbench
  • SANA-FE: Simulating Advanced Neuromorphic Architectures for Fast Exploration
  • An Integrated Toolbox for Creating Neuromorphic Edge Applications
  • CrossSim: A Hardware/Software Co-Design Tool for Analog In-Memory Computing
  • Neuromorphic Intermediate Representation
  • Building Scalable, Composable Spiking Neural Algorithms with Fugu (An Introduction)
08:30‑10:30
(120 min)
Tutorial slot I

Three tutorials in parallel

show abstract

Simulation Tool for Asynchronous Cortical Streams (STACS)Hands-on tutorial: BrainScaleS neuromorphic compute system An Integrated Toolbox for Creating Neuromorphic Edge Applications
Felix Wang (Sandia National Laboratories)

Tutorial abstract

Eric Müller (Heidelberg University)

(via the EBRAINS Research Infrastructure. Please ideally create your EBRAINS account before the tutorial)

Tutorial abstract

Lars Niedermeier (Niedermeier Consulting), Jeff Krichmar (UC Irvine)

Tutorial abstract

.ics

10:30‑11:00
(30 min)
Coffee break
11:00‑13:00
(120 min)
Tutorial slot II

Three tutorials in parallel

show abstract

Neuromorphic Intermediate RepresentationAn Introduction to Design and Simulation using SNS-Toolbox and SNSTorchBuilding Scalable, Composable Spiking Neural Algorithms with Fugu (An Introduction)
Bernhard Vogginger (TU Dresden), Jason Eshraghian (UC Santa Cruz)

Tutorial abstract

Will Nourse (Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland OH)



Tutorial abstract

Srideep Musuvathy (Sandia National Laboratories)

Tutorial abstract

.ics

13:00‑14:00
(60 min)
Lunch
14:00‑16:00
(120 min)
Tutorial slot III

Three tutorials in parallel

CrossSim: A Hardware/Software Co-Design Tool for Analog In-Memory Computing

We present [CrossSim(https://cross-sim.sandia.gov) , an open-source, GPU-accelerated, and experimentally validated simulation tool for the deployment of algorithms on analog in-memory computing (IMC) accelerators. CrossSim simulates how analog errors originating from devices and circuits affect the accuracy of the algorithm accuracy. It can be used as a hardware/software co-design tool for analog IMC, enabling a comprehensive exploration of the design space from the device technology, circuits, system architecture, to the application algorithm to ensure accurate analog computation. This tutorial will feature live code examples to emulate analog IMC using different device technologies on several exemplar applications, such as Fourier transforms and spiking neural network inference.

N2A -- neural programming language and workbench

Neuromorphic device makers are moving away from simple LIF dynamics toward programmable neuron models. The challenge is to support this while maintaining cross-platform portability. Remarkably, these are complementary goals. With an appropriate level of abstraction, it is possible to “write once, run anywhere”.

N2A allows the user to specify the dynamics for each class of neuron by simply listing its equations. The tool then compiles these for a given target platform. The structure of the network and interactions between neurons are specified in the same equation language. Network structures can be arbitrarily deep and complex. The language supports component creation, extension, and reuse. Components can be shared via built-in Git integration.

This tutorial will introduce the user to the N2A programming language and its associated IDE. Upon completion, the user will be able to create new neuron types, new applications, and run them on their local machine.

Preparations: This will be a hands-on tutorial. N2A may be downloaded from https://github.com/sandialabs/n2a and run on your personal laptop.

SANA-FE: Simulating Advanced Neuromorphic Architectures for Fast Exploration

Architecting new neuromorphic chips involves several design decisions that can affect power performance. Performance models can be used to estimate the impact of different approaches and inform these decisions. SANA-FE (Simulating Advanced Neuromorphic Architectures for Fast Exploration) is an open-source tool developed in a collaboration between UT Austin and Sandia National Laboratories to rapidly and accurately model and simulate the energy and performance of different neuromorphic hardware platforms. The simulator takes a description of a hardware platform and a spiking neural network (SNN) mapped onto the hardware to model execution of the SNN and predict power and performance. SANA-FE’s rapid and accurate predictions enable hardware-aware algorithm development and design-space exploration for algorithm/architecture codesign.

This tutorial will demonstrate SANA-FE and its capabilities to the neuromorphic community. We propose a 2-hour tutorial as a hands-on introduction to SANA-FE. While we have demonstrated SANA-FE on multiple architectures, for this tutorial we will focus on simulating Loihi (v1). We will show how to represent Loihi in SANA-FE, and specify SNNs for different neuromorphic applications. Finally, we will demonstrate how to use SANA-FE to optimize the energy and performance of a hypothetical Loihi-based architecture, performing a design-space sweep and finding the most power efficient design for both applications.

CrossSim: A Hardware/Software Co-Design Tool for Analog In-Memory ComputingN2A – neural programming language and workbenchSANA-FE: Simulating Advanced Neuromorphic Architectures for Fast Exploration
William Chapman (Sandia National Labs)

Tutorial abstract

Fred Rothganger (Sandia National Labs)

Tutorial abstract

James Boyle (The University of Texas at Austin)

Tutorial abstract

.ics

16:00
End of NICE 2024
Contact: bjoern.kindler@kip.uni-heidelberg.de