6.2 Special Session: 3D Sensor - Hardware to Application

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Date: Wednesday, March 27, 2019
Time: 11:00 - 12:30
Location / Room: Room 2

Organisers:
Saibal Mukhopadhyay, Georgia Institute of Technology, US
Pascal Vivet, CEA-Leti, FR

Chair:
Fabien Clermidy, CEA-Leti, FR

Co-Chair:
Pascal Vivet, CEA-Leti, FR

The 3D integration has emerged as a key enabler to continue performance growth of Moore's law. An application where 3D has already shown potential for tremendous benefit is the design of high-throughput and/or energy-efficient sensors. The ability to stack heterogeneous components in a small volumne coupled with potential for highly parallel access between sensing and processing has fueled new generation of senor platforms. Moreover, close proximity of processing and sensing has also lead to innovations in designing smart systems with in-built intelligence. This session will present four talks illustrating how 3D integration creates a platform for designing innovative sensors for applications ranging from high-performance imaging to ultra-low-power IoT platforms to bio-sensing. The first two talks will focus on application of 3D integration to high-performance and smart imaging. The first will present a detailed overview of recent advancements in 3D image sensor design, while the second talk will discuss the feasibility of embedding machine learning based feedback control within a 3D image sensor to create highly intelligent cameras. The third talk will present the concept of mm-scale sensors through 3D die stacking for ultra-low-power applications. Finally, the fourth talk will discuss design of innovative biosensors using fine-grain 3D integration.

TimeLabelPresentation Title
Authors
11:006.2.1ADVANCED 3D TECHNOLOGIES AND ARCHITECTURES FOR 3D SMART IMAGE SENSORS
Author:
Pascal Vivet, CEA-Leti, FR
Abstract
Image Sensors will get more and more pervasive into their environment. In the context of Automotive and IoT, low cost image sensors, with high quality pixels, will embed more and more smart functions, such as the regular low level image processing but also object recognition, movement detection, light detection, etc. 3D technology is a key enabler technology to integrate into a single device the pixel layer and associated acquisition layer, but also the smart computing features and the required amount of memory to process all the acquired data. More computing and memory within the 3D Smart Image Sensors will bring new features and reduce the overall system power consumption. Advanced 3D technology with ultra-fine pitch vertical interconnect density will pave the way towards new architectures for 3D Smart Image Sensors, allowing local vertical communication between pixels, and the associated computing and memory structures. The presentation will give an overview of recent 3D technologies solutions, such as Hybrid Bonding technology and the Monolithic 3D CoolCubeTM technology, with respective 3D interconnect pitch in the order of 1┬Ám and 100nm. Recent 3D Image Sensors will be presented, showing the capability of 3D technology to implement fine grain pixel acquisition and processing providing ultra-high speed image acquisition and tile-based processing. Finally, as further perspectives, multi-layer 3D image sensor architecture based on events and spiking will further reduce power consumption with new detection and learning processing capabilities.
11:226.2.2A CAMERA WITH BRAIN - EMBEDDING MACHINE LEARNING IN 3D
Author:
Saibal Mukhopadhyay, Georgia Institute of Technology, US
Abstract
The cameras today are designed to capture signals with highest possible accuracy to most faithfully represent what it sees. However, many mission-critical autonomous applications ranging from traffic monitoring to disaster recovery to defense requires quality of information, where 'useful information' depends on the tasks and is defined using complex features, rather than only changes in captured signal. Such applications require cameras that capture 'useful information' from a scene with highest quality while meeting system constraints such as power, performance, and bandwidth. This talk will discuss the feasibility of a camera that learns how to capture 'task-dependent information' with highest quality, paving the pathway to design a camera with brain. The talk will first discuss that 3D integration of digital pixel sensors with massively parallel computing platform for machine learning creates a hardware architecture for such a camera. Next, the talk will discuss embedded machine learning algorithms that can run on such platform to enhance quality of useful information by real-time control of the sensor parameters. The talk will conclude by identifying critical challenges as well as opportunities for hardware and algorithmic innovations to enable machine learning in the feedback loop of a 3D image sensor based camera.
11:446.2.3IOT2 - THE INTERNET OF TINY THINGS: REALIZING MM-SCALE SENSORS THROUGH 3D DIE STACKING
Author:
David Blaauw, University of Michigan, US
Abstract
The internet of things (IoT) is a rapidly evolving application space. One of the fascinating new fields in the IoT research is mm-scale sensors, or the internet of tiny things (IoT^2) that are poised to open up a myriad of new application domains. Enabled by the unique characteristics of cyberphysical system and recent advances in low power design and bare-die 3D chip stacking, mm-scale sensors are rapidly becoming a reality. In this paper, we will survey the challenges and solutions to 3D stacked mm-scale design, highlighting particularly low power circuit issues ranging from low power SRAM and miniature neural network accelerators, to radio communication protocols and analog interfaces. We will discuss system level challenges and illustrate several complete systems and their merging application spaces.
12:066.2.43D INTERCONNECTS AND INTEGRATION TECHNOLOGIES FOR BIOSENSOR SYSTEMS
Author:
Muhammad Bakir, Georgia Institute of Technology,
Abstract
tbd
12:30End of session
Lunch Break in Lunch Area



Coffee Breaks in the Exhibition Area

On all conference days (Tuesday to Thursday), coffee and tea will be served during the coffee breaks at the below-mentioned times in the exhibition area.

Lunch Breaks (Lunch Area)

On all conference days (Tuesday to Thursday), a seated lunch (lunch buffet) will be offered in the ""Lunch Area"" to fully registered conference delegates only. There will be badge control at the entrance to the lunch break area.

Tuesday, March 26, 2019

  • Coffee Break 10:30 - 11:30
  • Lunch Break 13:00 - 14:30
  • Awards Presentation and Keynote Lecture in ""TBD"" 13:50 - 14:20
  • Coffee Break 16:00 - 17:00

Wednesday, March 27, 2019

  • Coffee Break 10:00 - 11:00
  • Lunch Break 12:30 - 14:30
  • Awards Presentation and Keynote Lecture in ""TBD"" 13:30 - 14:20
  • Coffee Break 16:00 - 17:00

Thursday, March 28, 2019

  • Coffee Break 10:00 - 11:00
  • Lunch Break 12:30 - 14:00
  • Keynote Lecture in ""TBD"" 13:20 - 13:50
  • Coffee Break 15:30 - 16:00