Optical tomography using the SCIRun problem solving environment: Preliminary results for three-dimensional geometries and parallel processing

We present a 3D implementation of the UCL imaging package for absorption and scatter reconstruction from time-resolved data (TOAST), embedded in the SCIRun interactive simulation and visualization package developed at the University of Utah. SCIRun is a scientific programming environment that allows the interactive construction, debugging, and steering of large-scale scientific computations. While the capabilities of SCIRun's interactive approach are not yet fully exploited in the current TOAST implementation, an immediate benefit of the combined TOAST/SCIRun package is the availability of optimized parallel finite element forward solvers, and the use of SCIRun's existing 3D visualisation tools. A reconstruction of a segmented 3D head model is used as an example for demonstrating the capability of TOAST/SCIRun of simulating anatomically shaped meshes

A Classification and Survey of Computer System Performance Evaluation Techniques

Classification and survey of computer system performance evaluation technique

Anytime Algorithms for GPU Architectures

Most algorithms are run-to-completion and provide one answer upon completion and no answer if interrupted before completion. On the other hand, anytime algorithms have a monotonic increasing utility with the length of execution time. Our investigation focuses on the development of time-bounded anytime algorithms on Graphics Processing Units (GPUs) to trade-off the quality of output with execution time. Given a time-varying workload, the algorithm continually measures its progress and the remaining contract time to decide its execution pathway and select system resources required to maximize the quality of the result. To exploit the quality-time tradeoff, the focus is on the construction, instrumentation, on-line measurement and decision making of algorithms capable of efficiently managing GPU resources. We demonstrate this with a Parallel A* routing algorithm on a CUDA-enabled GPU. The algorithm execution time and resource usage is described in terms of CUDA kernels constructed at design-time. At runtime, the algorithm selects a subset of kernels and composes them to maximize the quality for the remaining contract time. We demonstrate the feedback-control between the GPU-CPU to achieve controllable computation tardiness by throttling request admissions and the processing precision. As a case study, we have implemented AutoMatrix, a GPU-based vehicle traffic simulator for real-time congestion management which scales up to 16 million vehicles on a US street map. This is an early effort to enable imprecise and approximate real-time computation on parallel architectures for stream-based timebounded applications such as traffic congestion prediction and route allocation for large transportation networks

Simulation of Efficient Real-Time Scheduling and Power Optimisation

International audienceSophisticated applications turn out to be executed upon more than one CPU for practical and economic reasons. Due to advances in circuit technology and performance limitation, multi-core technology has become the mainstream in CPU designs. However, the most serious limitation of these devices is the battery lifetime since battery technology is not keeping up with the rest of the power-hungry processors and peripherals used in today's mobile devices. As a solution, many investigations have turned toward the algorithms of power management combined with some scheduling policies. They can make significant energy saving while preserving the temporal constraints of these embedded systems. Reducing energy, especially, affect not only the battery lifetime, but also aim to reduce the heat generated by real-time embedded controller in various products or even to decrease the conditions of cooling and the costs, in the large scale, of giant multiprocessor computers. To assess the behavior and performance of the strategy of scheduling a flexible multiprocessor scheduling simulation and evaluation platform is needed. This paper puts forth the claim that the STORM simulator improves application quality both in terms of execution time and energy consumption for a high performance mobile computing embedded system design

An Analytical Solution for Probabilistic Guarantees of Reservation Based Soft Real-Time Systems

We show a methodology for the computation of the probability of deadline miss for a periodic real-time task scheduled by a resource reservation algorithm. We propose a modelling technique for the system that reduces the computation of such a probability to that of the steady state probability of an infinite state Discrete Time Markov Chain with a periodic structure. This structure is exploited to develop an efficient numeric solution where different accuracy/computation time trade-offs can be obtained by operating on the granularity of the model. More importantly we offer a closed form conservative bound for the probability of a deadline miss. Our experiments reveal that the bound remains reasonably close to the experimental probability in one real-time application of practical interest. When this bound is used for the optimisation of the overall Quality of Service for a set of tasks sharing the CPU, it produces a good sub-optimal solution in a small amount of time.Comment: IEEE Transactions on Parallel and Distributed Systems, Volume:27, Issue: 3, March 201