Seminars by CECS

Name: Ting-Shuo Chou

Date: May 21, 2015

Time: 3:00pm – 5:00pm

Location: Social & Behavioral Sciences Gateway 2200 Conference Room

Committee Chair: Jeffrey Krichmar (Chair), Nikil Dutt, Alexandru Nicolau

Abstract:

Neurodevelopmental disorders, such as Attention-Deficit–Hyperactivity
Disorder (ADHD) and Autism Spectrum Disorder (ASD), have core clinical
symptoms of inattention, hyperactivity, and impulsivity (often hyper-
and hypo- responsiveness. These symptoms are often accompanied by
reduced motor coordination and impaired sensory processing. We introduce
a Socially Assistive Robot (SAR) with the goal of automating therapy for
children with neurodevelopmental disorders. The novel robot, which is
called Cognitive Anteater Robotics Laboratory – Spiking Judgment Robot
(CARL-SJR), is designed for therapy and diagnosis. CARL-SJR is
autonomous and capable of tactile sensing and interaction. A spiking
neural network model and neurally inspired algorithms controls
CARL-SJR’s behavior. By providing a large tactile sensing surface that
encourages touching with hand movements, CARL-SJR especially addresses
impairments in tactile sensitivity and social interaction observed in
children with neurodevelopmental disorders. Using CARL-SJR, we conducted
a pilot study where children with different neurodevelopment disorders
show different behavioral metrics and tactile movements. The results
suggest CARL-SJR might serve as a diagnose tool for developmental
disorders. Second, we showed that the information carried by temporal
coding is higher than the traditional rate coding when decoding spike
trains in response to tactile movements. Third, we implemented online
learning capabilities on CARL-SJR, where the robot could associate a
user’s preferred color pattern displayed on the robot with the user’s
hand sweep across the robot’s body. The emerged behaviors and neural
activities in the SNN are consistent with biological recordings. The
underlying neural mechanism in the SNN also serves as an alternative
explanation of how brains encode timing and associate (or learning) two
temporal separated events.

Name: Volkan Gunes

Date: May 27, 2015

Time: 11:00AM – 12:00PM

Location: Donald Bren Hall 3013 Conference Room

Committee: Tony Givargis (Chair), Alexandru Nicolau, Ian Harris, Steffen Peter

Abstract:

The cyber-physical system (CPS) is a term describing a broad range of
complex, multi-disciplinary, physically-aware next generation engineered
systems that integrate embedded computing technologies (cyber part) into
the physical world. Sensors play an important role in this integration
because they provide the data extracted from the physical world for the
cyber systems to fulfill the decision making process. However, this
process is likely to be misled by incorrect data due to sensor fault
occurrences.

In this dissertation, the main focus is on sensor fault mitigation and
achieving high reliability in CPS operations. One of the challenges we
ponder is timely event (e.g., motion as a phenomenon) detection in CPS
under possible faulty sensor conditions. In this regard, our
demonstrative example of CPS is the falling ball example (FBE) using
binary event detectors (i.e., motion sensors), a controller, and a
camera for timely motion detection of a falling ball. Another challenge
we ponder is satisfying thermal comfort and energy efficiency under
certain faulty sensor conditions in a multi-room building incorporating
temperature sensors, controllers, and heating, ventilation, and air
conditioning (HVAC) systems as a CPS application. For both cases, we
adopt a model-based design (MBD) methodology to analyze the effect of
sensor faults on the desired system outcome. We specify well-defined
fault semantics for the event detectors and temperature sensors to make
the problem definition more clear. We provide a MATLAB/Simulink
simulation framework for our CPS examples. Besides having the
traditional CPS model that comprises the cyber, interface (e.g. sensors
and actuators) and physical models, we develop fault models and a system
evaluation model in Simulink and incorporate them into the CPS model.

We explore various techniques for fault mitigation in a holistic design
perspective. Therefore, the approaches presented in this study
contributes to the design of fault-tolerant CPSs. Furthermore,
considering compute demands of large scale CPSs, we introduce the XGRID
embedded many-core system-on-chip architecture. XGRID makes use of a
novel, FPGA-like, programmable interconnect infrastructure, offering
scalability and deterministic communication using hardware supported
message passing among cores. We provide a conceptual mapping of control
algorithms for the automation of a multi-room building onto target XGRID
architecture.

Our findings regarding reliable CPS design show that the physical system
attributes (e.g., sensor placement and environmental effects) can be a
more dominant factor than the cyber system attributes on the system
outcome. In addition, sensor faults may lead to unsatisfactory system
outcome in CPSs since CPSs heavily rely on sensor readings for decision
making. Therefore, the analysis of temporal and spatial correlations
between sensor readings helps mitigate certain types of sensor faults
and enable CPSs to utilize sensors’ data more efficiently for decision
making.

Name: Jun Yong Shin

Date: May 18th, 2015

Time: 2:00PM

Location: EH2430, Harut colloquia room

Committee Chair: Nikil Dutt

Abstract:

Over the last few decades, chip performance has increased steadily due to continuous and aggressive technology scaling. However, it leaves chips quite vulnerable to several issues at the same time; high power densities in some particular areas spread across a chip might result in hotspots and thermal gradients, and these can lead to permanent damage to the chip and also can reduce the reliability of the entire system using the chip. As a result, a large number of dynamic thermal management solutions have been proposed in recent years for use in multi-core architectures, and the accurate temperature information over the entire chip area has become indispensable especially for fine-grain dynamic thermal management solutions. Naturally, on-chip thermal sensors came to play an important role in providing the accurate information on the temperature distribution of a chip, but there still remain some issues regarding the allocation of on-chip thermal sensors; due to power, area and routing issues, it is preferable to limit the number of on-chip thermal sensors on a die, and their placement needs to be considered carefully in order to increase the accuracy of full-chip thermal profile reconstruction especially when just a small number of sensors can be implemented; due to the limited reading accuracy of low-power, small-sized on-chip thermal sensors, it would be better to have some way to improve their reading accuracy.

In this work, an issue will be firstly addressed regarding how to improve the reading accuracy of a low-power, small-sized on-chip thermal sensor such as Ring-Oscillator (RO) based sensors at runtime on a software level. Secondly, a question of how to allocate a proper number of sensors on a die in order to get the accurate full-chip scale thermal information on the run is addressed. Additionally, a temperature-aware routing for global interconnects to minimize the delay and also to reduce the probability of chip failure due to electromigration is presented at the end.

Final Defense – Abbas Banaiyanmofrad

May 20, 2015
3pm – 5pm
Donald Bren Hall 3011 Conference Room

Committee:
Nikil Dutt (Chair), Alex Nicolau, Alex Veidenbaum

Title:
Resilient On-Chip Memory Design in the Nano Era

Abstract:
Aggressive technology scaling in the nano-scale regime makes chips more susceptible to failures. This causes multiple reliability challenges in the design of modern chips, including manufacturing defects, wear-out, and parametric variations. By increasing the number, amount, and hierarchy of on-chip memory blocks in emerging computing systems, the reliability of the memory sub-system becomes an increasingly challenging design issue. Existing resilient memory design schemes are unable to effectively address the key features of scalability, interconnect-awareness, and cost-effectiveness for these platforms. In this thesis, we propose different approaches to address resilient on-chip memory design in computing systems ranging from traditional single-core processors to emerging many-core platforms. We classify our proposed approaches in five main categories: 1) Flexible and low-cost approaches to protect cache memories in single-core processors against permanent faults and transient errors, 2) Scalable fault-tolerant approaches to protect last-level caches with non-uniform cache access in chip multiprocessors, 3) Interconnect-aware cache protection schemes in network-on-chip architectures, 4) Application-aware memory resiliency for approximate computing era, and 5) System-level design space exploration, analysis, and optimization for redundancy-aware on-chip memory resiliency in many-core platforms. ​ 

Name: Yong hun Eom
Date: April 15, 2015
Time: 10:00am
Location: EH 2430
Committee Chair: Professor Demsky
Committee members: Prof. Pai Chou and Prof. Rainer Doemer

Title: Self-stabilizing Java: Tool Support for Building Robust Software

Abstract:
Developing robust software systems remains an open research problem. The
current approaches for improving software reliability mainly focus on
minimizing the number of software bugs through formal verification or
extensive testing. Despite such efforts, it is common that unexpected
software bugs corrupt a program’s state and cause systems to fail.

The motivation for this research is to embrace the fact that it is
difficult to guarantee that software is error-free. We present
Self-stabilizing Java (SJava) that instead checks that a program
self-stabilizes. Self-stabilizing programs automatically recover to the
correct state from the corrupted state caused by software bugs and other
sources. A number of applications are inherently self-stabilizing—such
programs typically overwrite all non-constant data with new input data.

We have developed a type system and static analyses that together check
whether program executions eventually transition from incorrect states
to the correct state. We combine this with a code-generation strategy
that ensures that a program continues executing long enough to
self-stabilize. Furthermore, in order to lower the burden of type
annotations, we present an annotation inference algorithm that
automatically derives an initial set of annotations.

Our experience using SJava indicates that our system successfully
checked that several benchmarks were self-stabilizing and effectively
inferred annotations for our benchmarks.

Name:  Che-Wei Chang

Date/Time:  Wednesday, January 28,2015, 9:00am

Location:  EH 3404

Committee Chair: Rainer Doemer

Committee Member: Daniel Gajski

Committee Member: Pai Chou

Abstract:

Title:  Self-Interference Cancellation in Full-duplex Wireless Systems

Speaker:  Elsayed Ahmed

Date/Time:  August 28, 2014, 10:00AM

Location:  Engineering Hall 4106

Committee Members:
Ahmed Eltawil (Chair)
Ender Ayanoglu
A. Lee Wsindlehurst

Abstract: Due to the tremendous increase in wireless data traffic, one of the major challenges for future wireless systems is the utilization of the available spectrum to achieve better data rates over limited spectrum. Currently, systems operate in what is termed “Half Duplex Mode,” where they are either transmitting or receiving, but never both using the same temporal and spectral resources. Full-duplex transmission promises to double the spectral efficiency where bidirectional communications is carried out over the same temporal and spectral resources. The main limitation impacting full-duplex transmission is managing the strong self-interference signal imposed by the transmit antenna on the receive antenna within the same transceiver. Several recent publications have demonstrated that the key challenge in practical full-duplex systems is un-cancelled self-interference power caused by a combination of hardware imperfections, especially Radio Frequency (RF) circuits’ impairments. In this thesis, we consider the problem of self-interference cancellation in full-duplex systems. The ultimate goal of this work is to design and build a complete, real-time, full-duplex system that is capable of achieving wireless full-duplex transmission using practical hardware platforms. Since RF circuits’ impairments are shown to have significant impact on the self-interference cancellation performance, first, we present a thorough analysis of the effect of RF impairments on the cancellation performance, with the aim of identifying the main performance limiting factors and bottlenecks. Second, the thesis proposes several impairments mitigation techniques to improve the overall self-interference cancellation capability by mitigating most of the transceiver RF impairments. In addition to impairments mitigation, two novel full-duplex transceiver architectures that achieve significant self-interference cancellation performance are proposed. The performance of the proposed techniques is analytically and experimentally investigated in practical wireless environments. Finally, the proposed self-interference cancellation techniques are used to build a complete full-duplex system with a 90% experimentally proven full-duplex rate improvement compared to half-duplex systems.

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