5,568 research outputs found
SIRENA: A CAD environment for behavioural modelling and simulation of VLSI cellular neural network chips
This paper presents SIRENA, a CAD environment for the simulation and modelling of mixed-signal VLSI parallel processing chips based on cellular neural networks. SIRENA includes capabilities for: (a) the description of nominal and non-ideal operation of CNN analogue circuitry at the behavioural level; (b) performing realistic simulations of the transient evolution of physical CNNs including deviations due to second-order effects of the hardware; and, (c) evaluating sensitivity figures, and realize noise and Monte Carlo simulations in the time domain. These capabilities portray SIRENA as better suited for CNN chip development than algorithmic simulation packages (such as OpenSimulator, Sesame) or conventional neural networks simulators (RCS, GENESIS, SFINX), which are not oriented to the evaluation of hardware non-idealities. As compared to conventional electrical simulators (such as HSPICE or ELDO-FAS), SIRENA provides easier modelling of the hardware parasitics, a significant reduction in computation time, and similar accuracy levels. Consequently, iteration during the design procedure becomes possible, supporting decision making regarding design strategies and dimensioning. SIRENA has been developed using object-oriented programming techniques in C, and currently runs under the UNIX operating system and X-Windows framework. It employs a dedicated high-level hardware description language: DECEL, fitted to the description of non-idealities arising in CNN hardware. This language has been developed aiming generality, in the sense of making no restrictions on the network models that can be implemented. SIRENA is highly modular and composed of independent tools. This simplifies future expansions and improvements.Comisión Interministerial de Ciencia y Tecnología TIC96-1392-C02-0
Efficient Simulation of Structural Faults for the Reliability Evaluation at System-Level
In recent technology nodes, reliability is considered a part of the standard design ¿ow at all levels of embedded system design. While techniques that use only low-level models at gate- and register transfer-level offer high accuracy, they are too inefficient to consider the overall application of the embedded system. Multi-level models with high abstraction are essential to efficiently evaluate the impact of physical defects on the system. This paper provides a methodology that leverages state-of-the-art techniques for efficient fault simulation of structural faults together with transaction-level modeling. This way it is possible to accurately evaluate the impact of the faults on the entire hardware/software system. A case study of a system consisting of hardware and software for image compression and data encryption is presented and the method is compared to a standard gate/RT mixed-level approac
Architecture and Design of Medical Processor Units for Medical Networks
This paper introduces analogical and deductive methodologies for the design
medical processor units (MPUs). From the study of evolution of numerous earlier
processors, we derive the basis for the architecture of MPUs. These specialized
processors perform unique medical functions encoded as medical operational
codes (mopcs). From a pragmatic perspective, MPUs function very close to CPUs.
Both processors have unique operation codes that command the hardware to
perform a distinct chain of subprocesses upon operands and generate a specific
result unique to the opcode and the operand(s). In medical environments, MPU
decodes the mopcs and executes a series of medical sub-processes and sends out
secondary commands to the medical machine. Whereas operands in a typical
computer system are numerical and logical entities, the operands in medical
machine are objects such as such as patients, blood samples, tissues, operating
rooms, medical staff, medical bills, patient payments, etc. We follow the
functional overlap between the two processes and evolve the design of medical
computer systems and networks.Comment: 17 page
A Novel Optical/digital Processing System for Pattern Recognition
This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from objects embedded in video imagery. We show that the internal amplitude structure of objects is recovered by the Radon transform, which is a well-known result, but, in addition, we show simulation results that calculate angular correlation, a simple but unique algorithm that extracts object boundaries from suitably threshold images from which length, width, area, aspect ratio, and orientation can be derived. In addition to circumventing scale and rotation distortions, these simulations indicate that the features derived from the angular correlation algorithm are relatively insensitive to tracking shifts and image noise. Some optical architecture concepts, including one based on micro-optical lenslet arrays, have been developed to implement these algorithms. Simulation test and evaluation using simple synthetic object data will be described, including results of a study that uses object boundaries (derivable from angular correlation) to classify simple objects using a neural network
Parallel processing and expert systems
Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 1990s cannot enjoy an increased level of autonomy without the efficient implementation of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real-time demands are met for larger systems. Speedup via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial laboratories in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems is surveyed. The survey discusses multiprocessors for expert systems, parallel languages for symbolic computations, and mapping expert systems to multiprocessors. Results to date indicate that the parallelism achieved for these systems is small. The main reasons are (1) the body of knowledge applicable in any given situation and the amount of computation executed by each rule firing are small, (2) dividing the problem solving process into relatively independent partitions is difficult, and (3) implementation decisions that enable expert systems to be incrementally refined hamper compile-time optimization. In order to obtain greater speedups, data parallelism and application parallelism must be exploited
Agent-based resource management for grid computing
A computational grid is a hardware and software infrastructure that provides
dependable, consistent, pervasive, and inexpensive access to high-end
computational capability. An ideal grid environment should provide access to the
available resources in a seamless manner. Resource management is an important
infrastructural component of a grid computing environment. The overall aim of
resource management is to efficiently schedule applications that need to utilise the
available resources in the grid environment. Such goals within the high
performance community will rely on accurate performance prediction capabilities.
An existing toolkit, known as PACE (Performance Analysis and Characterisation
Environment), is used to provide quantitative data concerning the performance of
sophisticated applications running on high performance resources. In this thesis an
ASCI (Accelerated Strategic Computing Initiative) kernel application, Sweep3D,
is used to illustrate the PACE performance prediction capabilities. The validation
results show that a reasonable accuracy can be obtained, cross-platform
comparisons can be easily undertaken, and the process benefits from a rapid
evaluation time. While extremely well-suited for managing a locally distributed
multi-computer, the PACE functions do not map well onto a wide-area
environment, where heterogeneity, multiple administrative domains, and communication irregularities dramatically complicate the job of resource
management. Scalability and adaptability are two key challenges that must be
addressed.
In this thesis, an A4 (Agile Architecture and Autonomous Agents) methodology is
introduced for the development of large-scale distributed software systems with
highly dynamic behaviours. An agent is considered to be both a service provider
and a service requestor. Agents are organised into a hierarchy with service
advertisement and discovery capabilities. There are four main performance
metrics for an A4 system: service discovery speed, agent system efficiency,
workload balancing, and discovery success rate.
Coupling the A4 methodology with PACE functions, results in an Agent-based
Resource Management System (ARMS), which is implemented for grid
computing. The PACE functions supply accurate performance information (e. g.
execution time) as input to a local resource scheduler on the fly. At a meta-level,
agents advertise their service information and cooperate with each other to
discover available resources for grid-enabled applications. A Performance
Monitor and Advisor (PMA) is also developed in ARMS to optimise the
performance of the agent behaviours.
The PMA is capable of performance modelling and simulation about the agents in
ARMS and can be used to improve overall system performance. The PMA can
monitor agent behaviours in ARMS and reconfigure them with optimised
strategies, which include the use of ACTs (Agent Capability Tables), limited
service lifetime, limited scope for service advertisement and discovery, agent
mobility and service distribution, etc.
The main contribution of this work is that it provides a methodology and
prototype implementation of a grid Resource Management System (RMS). The
system includes a number of original features that cannot be found in existing
research solutions
- …