SystemX

SystemX Seminar: On the role of interaction in future mobility systems, from vehicle-centric to system-wide control

Topic: 
On the role of interaction in future mobility systems, from vehicle-centric to system-wide control
Abstract / Description: 

In this talk I will discuss my work on self-driving vehicles, with an emphasis on accounting for interactions with external counterparts at both the vehicle- and system-levels. Specifically, I will first discuss a decision-making framework that enables a self-driving vehicle to proactively interact with humans to infer their intents, and to use such information for safe and efficient driving. I will then turn the discussion to the operational and economic aspects of autonomous mobility-on-demand (AMoD) systems, with an emphasis on the interaction between AMoD and the electric power network.

Date and Time: 
Thursday, April 26, 2018 - 4:30pm
Venue: 
Gates B03

SystemX Seminar: Power Electronics for the Future: Research Trends and Challenges

Topic: 
Power Electronics for the Future: Research Trends and Challenges
Abstract / Description: 

Power electronics can be found in everything from cellphones and laptops to gasoline/electric vehicles, industrial motors and inverters that connect solar panels to the electric grid. With close to 80% of electrical energy consumption in the US expected to flow through a power converter by 2030, innovative solutions are required to tackle key issues related to conversion efficiency, power density and cost. This talk will look at the trends in power electronics across different application spaces, describe the ongoing research efforts and highlight the challenges ahead.

Date and Time: 
Thursday, April 19, 2018 - 4:30pm
Venue: 
Gates B03

SystemX Seminar: Computational Near-Eye Displays (for VR/AR Applications)

Topic: 
Computational Near-Eye Displays (for VR/AR Applications)
Abstract / Description: 

Immersive visual and experiential computing systems, i.e. virtual and augmented reality (VR/AR), are entering the consumer market and have the potential to profoundly impact our society. Applications of these systems range from communication, entertainment, education, collaborative work, simulation and training to telesurgery, phobia treatment, and basic vision research. In every immersive experience, the primary interface between the user and the digital world is the near-eye display. Thus, developing near-eye display systems that provide a high-quality user experience is of the utmost importance. Many characteristics of near-eye displays that define the quality of an experience, such as resolution, refresh rate, contrast, and field of view, have been significantly improved over the last years. However, a significant source of visual discomfort prevails: the vergence-accommodation conflict (VAC). Further, natural focus cues are not supported by any existing near-eye display. In this talk, we discuss frontiers of engineering next-generation opto-computational near-eye display systems to increase visual comfort and provide realistic and effective visual experiences.

Date and Time: 
Thursday, April 12, 2018 - 4:30pm
Venue: 
Gates B03

SystemX Seminar: Modeling and Simulation for neuromorphic applications with focus on RRAM and ferroelectric devices

Topic: 
Modeling and Simulation for neuromorphic applications with focus on RRAM and ferroelectric devices
Abstract / Description: 

Neuromorphic computing has recently emerged as one of the most promising option to reduce power consumption of big data analysis, paving the way for artificial intelligence systems with power efficiencies like the human brain. The key device for neuromorphic computing system is given by artificial two-terminal synapses controlling signal processing and transmission. Their conductivity must be changed in an analog/continuous way depending on neural signal strengths. In addition, synaptic devices must have: symmetric/linear conductivity potentiation and depression; a high number of levels (~32), which depend on applications and algorithm performances; high data retention (>10 years) and cycling (>109); ultra-low power consumption (<10fJ); low variability; high scalability (<10nm) and possibility of 3D integration.

A variety of different device technologies have been explored such as phase change memories, ferroelectric random-access memory and resistive random-access memory (RRAM). In each case matching the desired specs is a complex multivariable problem requiring a deep quantitative understanding of the link between material properties at the atomic scale and electrical device performance. We have used a multiscale modeling platform GINESTRATM to illustrate this for the case of RRAM and Ferroelectric tunnel junctions (FTJ).

In the case of RRAM, modeling of key mechanisms shows that a dielectric stack composed of two appropriately chosen dielectrics provides the best solution, in agreement with experimental data. In the case of FTJ, the hysteretic ferroelectric behavior of dielectric stacks fabricated from the orthorhombic phase of doped HfO2 is nicely captured by the simulations. These show that Fe-HfO2 stack can be easily used for analog switching by simply tuning set/reset voltage amplitudes. An added advantage of the simulations is that they point out ways to improve the performance, variability and endurance of the devices in order to meet industrial requirements.

Date and Time: 
Thursday, April 5, 2018 - 4:30pm
Venue: 
Gates B03

SystemX Alliance hosts Spring 2018 Workshop

Topic: 
SystemX Alliance Spring 2018 Workshop
Abstract / Description: 

Join SystemX laliance for their SPRING Workshop Week: Apr 30-May 3, 2018. 
Details available on SystemX SPRING workshop page.

SystemX Alliance research broadly encompasses ubiquitous sensing, computing, and communications in various application areas. Currently affiliated SystemX faculty are found in departments across Stanford's School of Engineering and in some areas of natural Sciences and Medicine. Their research agenda is continually evolving in accordance with the interests of Stanford faculty and industry affiliates. 

Date and Time: 
Monday, April 30, 2018 (All day) to Thursday, May 3, 2018 (All day)
Venue: 
Li Ka Shing Center for Learning and Knowledge

SystemX Seminar: Toward Managing the Complexity of Molecules: Letting Matter Compute Itself

Topic: 
Toward Managing the Complexity of Molecules: Letting Matter Compute Itself
Abstract / Description: 

Person-millenia are spent each year seeking useful molecules for medicine, food, agriculture and other uses. For biomolecules, the near infinite universe of possibilities is staggering and humbling. As an example, antibodies, which make up the majority of the top-grossing medicines today, are comprised of 1,100 amino acids chosen from the twenty used by living things. The binding part (variable region) that allows the antibody to bind and recognize pathogens, is about 110 amino acids, giving rise to 10143 possible combinations. There are only about 1080 atoms in the universe, illustrating the intractability of exploring the entire space of possibility. This is just one example…

Presently, machine learning (ML), artificial intelligence (AI), quantum computing, and “big data” are often put forth as the solutions to all problems, particularly by pontificating TED presenters and in Sand Hill pitches dripping with hyperbole. Expecting these methods to provide intelligent prediction of molecular structure and function within our lifetimes is unrealistic. For example, a neural network trained on daily weather patterns in Palo Alto cannot develop an internal model for global weather. In a similar way, finite and reasonable molecular training sets will not magically cause a generalizable model of molecular quantum mechanics to arise within a neural network, no matter how many layers it is endowed with.

With that provocative preface, we turn to the notion of letting matter compute itself. Massive combinatorial libraries can now be intelligently and efficiently mined with appropriate molecular readouts (AKA “the question vector”) at ever-increasing throughputs presently surpassing 1012 unique molecules in a few hours. Once “matter-in-the-loop” exploration is embraced, AI, ML and other methods can be brought to bear usefully in closed-loop methods to follow veins of opportunity in molecular space. Several examples of mining massive molecular spaces will be presented, including drug discovery, digital pathology, and AI-guided continuous-flow chemical synthesis – all real, all working today.

Date and Time: 
Thursday, March 15, 2018 - 4:30pm to 5:30pm
Venue: 
Y2E2 Room 111

SystemX BONUS! Seminar: Soft Switching Inverters with Wide-Bandgap Devices

Topic: 
Soft Switching Inverters with Wide-Bandgap Devices
Abstract / Description: 

Soft switching has been successfully applied in switching supplies, single-phase inverter for induction heating etc. However, applications of soft switching to three-phase inverters or converters are not so common up to now. Three-phase converters/inverters are widely used in Data Center, UPS, fast EV chargers, PV/Wind power inverter, and drives. In this presentation soft switching inverters with Zero-Voltage-Switching SVM scheme(ZVS-SVM) is introduced. The ZVS-SVM can be used either three-Phase AC/DC converters or inverters and realize zero voltage switching for all switches including both inverter bridges switches and the auxiliary switch for three-phase inverters. Then impact of SiC device on soft switching inverters is investigated with respect to the power density and conversion efficiency. Finally experimental results of a soft-switching 20 kW SiC MOSFET grid inverter with 300kHz switching frequency is introduced.

Date and Time: 
Tuesday, February 20, 2018 - 4:30pm
Venue: 
Packard 204

SystemX Seminar: Coherent Ising machines for combinatorial optimization - Optical neural networks operating at the quantum limit

Topic: 
Coherent Ising machines for combinatorial optimization - Optical neural networks operating at the quantum limit
Abstract / Description: 

Optimization problems with discrete and continuous variables are ubiquitous in numerous important areas, including operations and scheduling, drug discovery, wireless communications, finance, integrated circuit design, compressed sensing and machine learning. Despite rapid advances in both algorithm and digital computing technology, even modest sized optimization problems that arise in practice may be very difficult to solve on modern digital computers. One alternative of current interest is the adiabatic quantum computing (AQC) or quantum annealing (QA). Sophisticated AQC/QA devices are already under development, but providing dense connectivity between qubits remains a major challenge with serious implications for the efficiency of AQC/QA approaches. In this talk, we will introduce a novel computing system, coherent Ising machine, and describe its theoretical and experimental performance. We start with the physics of quantum-to-classical crossover as a computational mechanism and how to construct such physical devices as quantum neurons and synapses. We show the performance comparison against various classical neural network models implemented in CPU and supercomputers as algorithms. We end the talk by introducing the portal of the QNNCloud service system based on the coherent Ising machines.

Date and Time: 
Monday, January 29, 2018 - 2:00pm
Venue: 
Packard 204

SystemX Seminar: Hardware architectures for computational imaging and vision

Topic: 
Hardware architectures for computational imaging and vision
Abstract / Description: 

85% of images today are taken by cell phones. These images are not merely projections of light from the scene onto the camera sensor but result from a deep calculation. This calculation involves a number of computational imaging algorithms such as high dynamic range (HDR) imaging, panorama stitching, image deblurring and low-light imaging that compensate for camera limitations, and a number of deep learning based vision algorithms such as face recognition, object recognition and scene understanding that make inference on these images for a variety of emerging applications. However, because of their high computational complexity, mobile CPU or GPU based implementations of these algorithms do not achieve real-time performance. Moreover, offloading these algorithms to the cloud is not a viable solution because wirelessly transmitting large amounts of image data results in long latency and high energy consumption, making them unsuitable for mobile devices.

My approach to solving this problem has to been to design energy-efficient hardware accelerators targeted at these applications. In this talk, I will present my work on the architecture design and implementation of three complete computational imaging systems for energy-constrained mobile environments: (1) an energy-scalable accelerator for blind image deblurring, (2) a reconfigurable bilateral filtering processor for computational photography applications such as HDR imaging, low-light imaging and glare reduction, and (3) a low-power processor for real-time motion magnification in videos. Each of these accelerator-based systems achieves 2 to 3 orders of magnitude improvement in runtime and 3 to 4 orders of magnitude improvement in energy compared to existing implementations on CPU or GPU platforms. In my talk, I will present the energy minimization techniques that I employed in my designs to obtain these improvements. In addition, I will talk about how these systems achieve energy scalability by trading off accuracy with execution time. This is essential in real-life applications where one might still want to run a complex algorithm in a low-battery scenario but might be willing to sacrifice some visual quality.

I will conclude my talk by giving my vision for how such accelerator-based systems will enable energy-efficient integration of computational imaging and deep learning based vision algorithms into mobile and wearable devices for emerging applications such as autonomous driving, micro-robotics, assistive technology, medical imaging and augmented and virtual reality.

Date and Time: 
Thursday, March 8, 2018 - 4:30pm
Venue: 
Y2E2 111

SystemX Seminar: Beyond inspiration: Three lessons from biology on building intelligent machines

Topic: 
Beyond inspiration: Three lessons from biology on building intelligent machines
Abstract / Description: 

The only known systems that exhibit truly intelligent, autonomous behavior are biological. If we wish to build machines capable of such behavior, then it makes sense to learn as much as we can about how these systems work. Inspiration is a good start, but real progress will require gaining a more solid understanding of the principles of information processing at work in nervous systems. Here I will focus on three areas of investigation that I believe will be especially fruitful: 1) the study of perception-action loops, in particular how sensory information is actively acquired via motor commands, 2) developing good computational models of nonlinear signal integration in dendritic trees, and 3) elucidating the computational role of feedback in neural systems.

Date and Time: 
Thursday, February 22, 2018 - 4:30pm
Venue: 
Y2E2 111

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