Pieter P. Jonker

A system architecture solution for unreliable nanoelectronic devices

The shrinking of electronic devices will inevitably introduce a growing number of defects and even make these devices more sensitive to external influences. It is, therefore, likely that the emerging nanometer-scale devices will eventually suffer from more errors than classical silicon devices in large scale integrated circuits. In order to make systems based on nanometer-scale devices reliable, the design of fault-tolerant architectures will be necessary. Initiated by von Neumann, the NAND multiplexing technique, based on a massive duplication of imperfect devices and randomized imperfect interconnects, had been studied in the past using an extreme high degree of redundancy. In this paper, this NAND multiplexing is extended to a rather low degree of redundancy, and the stochastic Markov nature in the heart of the system is discovered and studied, leading to a comprehensive fault-tolerant theory. A system architecture based on NAND multiplexing is investigated by studying the problem of the random background charges in single electron tunneling (SET) circuits. It might be a system solution for an ultra large integration of highly unreliable nanometer-scale devices.

Socially Assistive Robots in Elderly Care: A Systematic Review into Effects and Effectiveness

The ongoing development of robotics on the one hand and, on the other hand, the foreseen relative growth in number of elderly individuals suffering from dementia, raises the question of which contribution robotics could have to rationalize and maintain, or even improve the quality of care. The objective of this review was to assess the published effects and effectiveness of robot interventions aiming at social assistance in elderly care. We searched, using Medical Subject Headings terms and free words, in the CINAHL, MEDLINE, Cochrane, BIOMED, PUBMED, PsycINFO, and EMBASE databases. Also the IEEE Digital Library was searched. No limitations were applied for the date of publication. Only articles written in English were taken into account. Collected publications went through a selection process. In the first step, publications were collected from major databases using a search query. In the second step, 3 reviewers independently selected publications on their title, using predefined selection criteria. In the third step, publications were judged based on their abstracts by the same reviewers, using the same selection criteria. In the fourth step, one reviewer made the final selection of publications based on complete content. Finally, 41 publications were included in the review, describing 17 studies involving 4 robot systems. Most studies reported positive effects of companion-type robots on (socio)psychological (eg, mood, loneliness, and social connections and communication) and physiological (eg, stress reduction) parameters. The methodological quality of the studies was, mostly, low. Although positive effects were reported, the scientific value of the evidence was limited. The positive results described, however, prompt further effectiveness research in this field.

The distributed ASCI Supercomputer project

The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting of four cluster computers at different locations. DAS has been used for research on communication software, parallel languages and programming systems, schedulers, parallel applications, and distributed applications. The paper gives a preview of the most interesting research results obtained so far in the DAS project.

Toward hardware-redundant, fault-tolerant logic for nanoelectronics

This article provides an overview of several logic redundancy schemes, including von Neumanns multiplexing logic, N-tuple modular redundancy, and interwoven redundant logic. We discuss several important concepts for redundant nanoelectronic system designs based on recent results. First, we use Markov chain models to describe the error-correcting and stationary characteristics of multiple-stage multiplexing systems. Second, we show how to obtain the fundamental error bounds by using bifurcation analysis based on probabilistic models of unreliable gates. Third, we describe the notion of random interwoven redundancy. Finally, we compare the reliabilities of quadded and random interwoven structures by using a simulation-based approach. We observe that the deeper a circuits logical depth, the more fault-tolerant the circuit tends to be for a fixed number of faults. For a constant gate failure rate, a circuits reliability tends to reach a stationary state as its logical depth increases.

A defect- and fault-tolerant architecture for nanocomputers

Both von Neumanns NAND multiplexing, based on a massive duplication of imperfect devices and randomized imperfect interconnects, and reconfigurable architectures have been investigated to come up with solutions for integrations of highly unreliable nanometre-scale devices. In this paper, we review these two techniques, and present a defect- and fault-tolerant architecture in which von Neumanns NAND multiplexing is combined with a massively reconfigurable architecture. The system performance of this architecture is evaluated by studying its reliability, i.e. the probability of system survival. Our evaluation shows that the suggested architecture can tolerate a device error rate of up to 10−2, with multiple redundant components; the structure is efficiently robust against both permanent and transient faults for an ultra-large integration of highly unreliable nanometre-scale devices.

CPR: mixed task and data parallel scheduling for distributed systems

It is well-known that mixing task and data parallelism to solve large computational applications often yields better speedups compared to either applying pure task parallelism or pure data parallelism. Typically, the applications are modeled in terms of a dependence graph of coarse-grain data-parallel tasks, called a data-parallel task graph. In this paper we present a new compile-time heuristic, named Critical Path Reduction (CPR), for scheduling data-parallel task graphs. Experimental results based on graphs derived from real problems as well as synthetic graphs, show that CPR achieves higher speedup compared to other well-known existing scheduling algorithms, at the expense of some higher cost. These results are also confirmed by performance measurements of two real applications (i.e., complex matrix multiplication and Strassen matrix multiplication) running on a cluster of workstations.

Discovery of high-level tasks in the operating room

Recognizing and understanding surgical high-level tasks from sensor readings is important for surgical workflow analysis. Surgical high-level task recognition is also a challenging task in ubiquitous computing because of the inherent uncertainty of sensor data and the complexity of the operating room environment. In this paper, we present a framework for recognizing high-level tasks from low-level noisy sensor data. Specifically, we present a Markov-based approach for inferring high-level tasks from a set of low-level sensor data. We also propose to clean the noisy sensor data using a Bayesian approach. Preliminary results on a noise-free dataset of ten surgical procedures show that it is possible to recognize surgical high-level tasks with detection accuracies up to 90%. Introducing missed and ghost errors to the sensor data results in a significant decrease of the recognition accuracy. This supports our claim to use a cleaning algorithm before the training step. Finally, we highlight exciting research directions in this area.

A data and task parallel image processing environment

The paper presents a data and task parallel low-level image processing environment for distributed memory systems. Image processing operators are parallelized by data decomposition using algorithmic skeletons. Image processing applications are parallelized by task decomposition, based on the image application task graph. In this way, an image processing application can be parallelized both by data and task decomposition, and thus better speed-ups can be obtained. We validate our method on the multi-baseline stereo vision application.

As if being there: mediated reality for crime scene investigation

This paper presents a novel mediated reality system designed to support collaboration between crime scene investigators during a first analysis on a crime scene, remotely supported by expert colleagues. Requirements elicited from interviews and interactive sessions with practicing crime scene investigators, provided the design criteria for a head mounted display capable of real-time map-making for spatial collaboration. The resulting system is evaluated in a staged crime scene experiment in which lay investigators collaboratively solve a spatial problem with remote experts. The results show that our novel approach to remote spatial interaction with the physical scene enables investigators to tackle current issues on site in collaboration with experts at a distance.

Using a controller based on reinforcement learning for a passive dynamic walking robot

One of the difficulties with passive dynamic walking is the stability of walking. In our robot, small uneven or tilted parts of the floor disturb the locomotion and must be dealt with by the feedback controller of the hip actuation mechanism. This paper presents a solution to the problem in the form of controller that is based on reinforcement learning. The control mechanism is studied using a simulation model that is based on a mechanical prototype of passive dynamic walking robot with a conventional feedback controller. The successful walking results of our simulated walking robot with a controller based on reinforcement learning showed that in addition to the prime principle of our mechanical prototype, new possibilities such as optimization towards various goals like maximum speed and minimal cost of transport, and adaptation to unknown situations can be quickly found