Redundancy management for efficient fault recovery in NASA's distributed computing system

The management of redundancy in computer systems was studied and guidelines were provided for the development of NASA's fault-tolerant distributed systems. Fault recovery and reconfiguration mechanisms were examined. A theoretical foundation was laid for redundancy management by efficient reconfiguration methods and algorithmic diversity. Algorithms were developed to optimize the resources for embedding of computational graphs of tasks in the system architecture and reconfiguration of these tasks after a failure has occurred. The computational structure represented by a path and the complete binary tree was considered and the mesh and hypercube architectures were targeted for their embeddings. The innovative concept of Hybrid Algorithm Technique was introduced. This new technique provides a mechanism for obtaining fault tolerance while exhibiting improved performance

Fault tolerant clos network

Multistage interconnection networks, or MINs, provide paths between functional modules in multiprocessor systems. The MINs are usually segmented into several stages. Each stage connects inputs to appropriate links of the next stage so that the cumulative effect of all the stages satisfies input-output connection requirements. This thesis deals with a fault tolerant Clos network. The fault tolerance technique involves addition of extra switches per stage to compensate for any switch failure The reliability analysis of both ordinary and fault tolerant Clos networks is presented. The optimal number of extra switches required to get the best reliability results has been analyzed

Wildcard dimensions, coding theory and fault-tolerant meshes and hypercubes

Hypercubes, meshes and tori are well known interconnection networks for parallel computers. The sets of edges in those graphs can be partitioned to dimensions. It is well known that the hypercube can be extended by adding a wildcard dimension resulting in a folded hypercube that has better fault-tolerant and communication capabilities. First we prove that the folded hypercube is optimal in the sense that only a single wildcard dimension can be added to the hypercube. We then investigate the idea of adding wildcard dimensions to d-dimensional meshes and tori. Using techniques from error correcting codes we construct d-dimensional meshes and tori with wildcard dimensions. Finally, we show how these constructions can be used to tolerate edge and node faults in mesh and torus networks

Framework for simulation of fault tolerant heterogeneous multiprocessor system-on-chip

Due to the ever growing requirement in high performance data computation, current Uniprocessor systems fall short of hand to meet critical real-time performance demands in (i) high throughput (ii) faster processing time (iii) low power consumption (iv) design cost and time-to-market factors and more importantly (v) fault tolerant processing. Shifting the design trend to MPSOCs is a work-around to meet these challenges. However, developing efficient fault tolerant task scheduling and mapping techniques requires optimized algorithms that consider the various scenarios in Multiprocessor environments. Several works have been done in the past few years which proposed simulation based frameworks for scheduling and mapping strategies that considered homogenous systems and error avoidance techniques. However, most of these works inadequately describe today\u27s MPSOC trend because they were focused on the network domain and didn\u27t consider heterogeneous systems with fault tolerant capabilities; In order to address these issues, this work proposes (i) a performance driven scheduling algorithm (PD SA) based on simulated annealing technique (ii) an optimized Homogenous-Workload-Distribution (HWD) Multiprocessor task mapping algorithm which considers the dynamic workload on processors and (iii) a dynamic Fault Tolerant (FT) scheduling/mapping algorithm to employ robust application processing system. The implementation was accompanied by a heterogeneous Multiprocessor system simulation framework developed in systemC/C++. The proposed framework reads user data, set the architecture, execute input task graph and finally generate performance variables. This framework alleviates previous work issues with respect to (i) architectural flexibility in number-of-processors, processor types and topology (ii) optimized scheduling and mapping strategies and (iii) fault-tolerant processing capability focusing more on the computational domain; A set of random as well as application specific STG benchmark suites were run on the simulator to evaluate and verify the performance of the proposed algorithms. The simulations were carried out for (i) scheduling policy evaluation (ii) fault tolerant evaluation (iii) topology evaluation (iv) Number of processor evaluation (v) Mapping policy evaluation and (vi) Processor Type evaluation. The results showed that PD scheduling algorithm showed marginally better performance than EDF with respect to utilization, Execution-Time and Power factors. The dynamic Fault Tolerant implementation showed to be a viable and efficient strategy to meet real-time constraints without posing significant system performance degradation. Torus topology gave better performance than Tile with respect to task completion time and power factors. Executing highly heterogeneous Tasks showed higher power consumption and execution time. Finally, increasing the number of processors showed a decrease in average Utilization but improved task completion time and power consumption; Based on the simulation results, the system designer can compare tradeoffs between a various design choices with respect to the performance requirement specifications. In general, designing an optimized Multiprocessor scheduling and mapping strategy with added fault tolerant capability will enable to develop efficient Multiprocessor systems which meet future performance goal requirements. This is the substance of this work

LOAD DISTRIBUTION AND RESOURCE SHARING

This paper will discuss about the system structure and system design philosophy for the large scale control systems. The design philosophy, the main theme of this article, is "load distribution and resource sharing", but also the following items will be discussed: - three level hierarchy control system philosophy; - coupling and optimal load sharing among SCC/DDC computers; - sharing of the process resources among computers.load distribution

Subcube embeddability and fault tolerance of augmented hypercubes

Hypercube networks have received much attention from both parallel processing and communications areas over the years since they offer a rich interconnection structure with high bandwidth, logarithmic diameter, and high degree of fault tolerance. They are easily partitionable and exhibit a high degree of fault tolerance. Fault-tolerance in hypercube and hypercube-based networks received the attention of several researchers in recent years; The primary idea of this study is to address and analyze the reliability issues in hypercube networks. It is well known that the hypercube can be augmented with one dimension to replace any of the existing dimensions should any dimension fail. In this research, it is shown that it is possible to add i dimensions to the standard hypercube, Qn to tolerate (i - 1) dimension failures, where 0 \u3c i ≤ n. An augmented hypercube, Qn +(n) with n additional dimensions is introduced and compared with two other hypercube networks with the same amount of redundancy. Reliability analysis for the three hypercube networks is done using the combinatorial and Markov modeling. The MTTF values are calculated and compared for all three networks. Comparison between similar size hypercube networks show that the augmented hypercube is more robust than the standard hypercube; As a related problem, we also look at the subcube embeddability. Subcube embeddability of the hypercube can be enhanced by introducing an additional dimension. A set of new dimensions, characterized by the Hamming distance between the pairs of nodes it connects, is introduced using a measure defined as the magnitude of a dimension. An enumeration of subcubes of various sizes is presented for a dimension parameterized by its magnitude. It is shown that the maximum number of subcubes for a Qn can only be attained when the magnitude of dimension is n - 1 or n. It is further shown that the latter two dimensions can optimally increase the number of subcubes among all possible choices

CLEX: Yet Another Supercomputer Architecture?

We propose the CLEX supercomputer topology and routing scheme. We prove that CLEX can utilize a constant fraction of the total bandwidth for point-to-point communication, at delays proportional to the sum of the number of intermediate hops and the maximum physical distance between any two nodes. Moreover, % applying an asymmetric bandwidth assignment to the links, all-to-all communication can be realized $(1+o(1))$-optimally both with regard to bandwidth and delays. This is achieved at node degrees of $n^{\varepsilon}$, for an arbitrary small constant $\varepsilon\in (0,1]$. In contrast, these results are impossible in any network featuring constant or polylogarithmic node degrees. Through simulation, we assess the benefits of an implementation of the proposed communication strategy. Our results indicate that, for a million processors, CLEX can increase bandwidth utilization and reduce average routing path length by at least factors $10$ respectively $5$ in comparison to a torus network. Furthermore, the CLEX communication scheme features several other properties, such as deadlock-freedom, inherent fault-tolerance, and canonical partition into smaller subsystems