Reliability-aware performance model for optimal GPU-enabled cluster environment

Failures are normal rather than exceptional in cloud computing environments, high fault tolerance issue is one of the major obstacles for opening up a new era of high serviceability cloud computing as fault tolerance plays a key role in ensuring cloud serviceability. Fault tolerant service is an essential part of Service Level Objectives (SLOs) in clouds. To achieve high level of cloud serviceability and to meet high level of cloud SLOs, a foolproof fault tolerance strategy is needed. In this paper, the definitions of fault, error, and failure in a cloud are given, and the principles for high fault tolerance objectives are systematically analyzed by referring to the fault tolerance theories suitable for large-scale distributed computing environments. Based on the principles and semantics of cloud fault tolerance, a dynamic adaptive fault tolerance strategy DAFT is put forward. It includes: (i) analyzing the mathematical relationship between different failure rates and two different fault tolerance strategies, which are checkpointing fault tolerance strategy and data replication fault tolerance strategy; (ii) building a dynamic adaptive checkpointing fault tolerance model and a dynamic adaptive replication fault tolerance model by combining the two fault tolerance models together to maximize the serviceability and meet the SLOs; and (iii) evaluating the dynamic adaptive fault tolerance strategy under various conditions in large-scale cloud data centers and consider different system centric parameters, such as fault tolerance degree, fault tolerance overhead, response time, etc. Theoretical as well as experimental results conclusively demonstrate that the dynamic adaptive fault tolerance strategy DAFT has high potential as it provides efficient fault tolerance enhancements, significant cloud serviceability improvement, and great SLOs satisfaction. It efficiently and effectively achieves a trade-off for fault tolerance objectives in cloud computing environments.

Currently, using commercial off-the-shelf (COTS) components and constructing parallel system becomes the main way to improve satellite system performance remarkably. System reliability relying on its structure rather than devices makes system fault-tolerant architecture and strategy increasingly important. As centralized fault-tolerant solution has the inherent drawback of single point of failure (SPOF), it can not guarantee system reliability well. Distributed fault- tolerant method, due to its complexity and large overhead, has not been maturely used. In this paper, we propose a new distributed fault-tolerant scheme with high reliability and flexibility, in which an equal symmetric distributed fault- tolerant (ESDFt) architecture is constructed. Based on the structure, functional module framework of system nodes and autonomous fault-tolerant strategy are designed. The ESDFt scheme creates favorable conditions for flexible implementation of system fault tolerance. It utilizes the master election mechanism, which eliminates the risks of SPOF and chooses master node intelligently based on user's configuration, making fault-tolerant complexity and processing overhead flexibly adjustable. The verification and evaluation of ESDFt scheme has been performed on a prototype system. The experiment results prove that ESDFt scheme not only ensures system reliability well, but also enhances system flexibility and practicality at the same time.

This paper develops a modulation based fault-tolerant (FT) strategy for restoring the operation of three-phase modular multilevel converters (MMCs) with faulty switches. This FT strategy is based on a proposed modified space vector modulation (SVM) technique that generates balanced line-to-line (line) voltages even in the case of a fault occurrence. In the postfault operation, the proposed strategy is able to restore the fundamental amplitude of the line to the neutral (load) voltages to that of the normal operation condition with a slightly increased voltage stress over the switches in the faulty phase. In this paper, first a brief background about MMCs and SVM technique is provided. Then, the proposed FT strategy and the modified SVM technique are presented. Finally, several simulation and experimental results are provided to validate operation of the proposed strategy.

Graphics processing units (GPUs) are increasingly critical for general-purpose parallel processing performance. GPU hardware is composed of many streaming multiprocessors, each of which employs the single-instruction multiple-data (SIMD) execution style. This massively parallel architecture allows GPUs to execute tens of thousands of threads in parallel. Thus, GPU architectures efficiently execute heavily data-parallel applications. However, due to this SIMD execution style, resource utilization and thus overall performance can be significantly affected if computation threads must take diverging control paths. Control flow divergence in GPUs is a well-known problem: prior approaches have attempted to reduce control flow divergence through code transformations, memory access indirection, and input data reorganization. However, as we will demonstrate, the utility of these transformations is seriously affected by the lack of a guiding metric that properly estimates how control flow divergence affects application performance. In this paper, we introduce a metric that simply and accurately estimates performance of computation-bound GPU kernels with control flow divergence, and use the metric as a value function for thread re-grouping algorithms. We measure the performance on NVIDIA GTS250 GPU. For the tested set of applications, our experiments demonstrate that the proposed metric correlates well with actual GPU application performance. Through thread re-grouping guided by our metric, control flow divergence optimization can improve application performance by up to 3.19X.

Due to modern technology trends such as decreasing feature sizes and lower voltage levels, fault tolerance (FT) is becoming increasingly important in computing systems. Several schemes have been proposed to enable a user to configure the FT at the application level, thereby enabling the user to trade stronger FT for performance or vice versa. In this paper, we propose supporting instruction-level rather than application-level configurability of FT, since different parts of some applications (e.g., multimedia) can have different reliability requirements. Weak or no FT will be applied to less critical parts, resulting in time and/or resource gains. These gains can be used to apply stronger FT techniques to the more critical parts; hence increasing the overall reliability. The paper shows how some existing FT techniques can be adapted to support instruction-level FT configurability, how a programmer can specify the desired FT level of the instructions, and how the compiler can manage it automatically. A comparison between the existing FT scheme EDDI (which duplicates all instructions) and the proposed approach is performed both at the kernel and at full application levels. The simulation results show that both the performance and the energy consumption are significantly improved (up to 50% at the kernel and up to 16% at full application level), while the fault coverage depends on the application. For the full application (JPEG encoder), our approach is only applied to one kernel in order to avoid increasing the programming effort significantly.

In this paper, we develop a fault tolerant job scheduling strategy in order to tolerate faults gracefully in an economy based grid environment. We propose a novel adaptive task checkpointing based fault tolerant job scheduling strategy for an economy based grid. The proposed strategy maintains a fault index of grid resources. It dynamically updates the fault index based on successful or unsuccessful completion of an assigned task. Whenever a grid resource broker has tasks to schedule on grid resources, it makes use of the fault index from the fault tolerant schedule manager in addition to using a time optimization heuristic. While scheduling a grid job on a grid resource, the resource broker uses fault index to apply different intensity of task checkpointing (inserting checkpoints in a task at different intervals). To simulate and evaluate the performance of the proposed strategy, this paper enhances the GridSim Toolkit-4.0 to exhibit fault tolerance related behavior. We also compare "checkpointing fault tolerant job scheduling strategy" with the well-known time optimization heuristic in an economy based grid environment. From the measured results, we conclude that even in the presence of faults, the proposed strategy effectively schedules grid jobs tolerating faults gracefully and executes more jobs successfully within the specified deadline and allotted budget. It also improves the overall execution time and minimizes the execution cost of grid jobs.

Failure of a safety critical system can lead to big losses. Very high software reliability is required for automating the working of systems such as aircraft controller and nuclear reactor controller software systems. Fault-tolerant softwares are used to increase the overall reliability of software systems. Fault tolerance is achieved using the fault-tolerant schemes such as fault recovery (recovery block scheme), fault masking (N-version programming (NVP)) or a combination of both (Hybrid scheme). These softwares incorporate the ability of system survival even on a failure. Many researchers in the field of software engineering have done excellent work to study the reliability of fault-tolerant systems. Most of them consider the stable system reliability. Few attempts have been made in reliability modeling to study the reliability growth for an NVP system. Recently, a model was proposed to analyze the reliability growth of an NVP system incorporating the effect of fault removal efficiency. In this model, a proportion of the number of failures is assumed to be a measure of fault generation while an appropriate measure of fault generation should be the proportion of faults removed. In this paper, we first propose a testing efficiency model incorporating the effect of imperfect fault debugging and error generation. Using this model, a software reliability growth model (SRGM) is developed to model the reliability growth of an NVP system. The proposed model is useful for practical applications and can provide the measures of debugging effectiveness and additional workload or skilled professional required. It is very important for a developer to determine the optimal release time of the software to improve its performance in terms of competition and cost. In this paper, we also formulate the optimal software release time problem for a 3VP system under fuzzy environment and discuss a the fuzzy optimization technique for solving the problem with a numerical illustration.

This paper focuses on insufficient perception in blind scenes and the failures of the actuator and sensor of vehicle suspension. The safe speed is designed and the fault-tolerant strategy based on the observer is designed when the actuator and sensor fail simultaneously. A speed planning strategy to ensure that vehicles operate at a safe speed is proposed. The Markov suspension fault jump model considering the suspension sensor and actuator faults is established. Based on the fault estimation obtained by the fault observer, a fault tolerance control strategy of sensor signal reconstruction and actuator fault compensation is adopted. The measurement index for evaluating fault tolerance effectiveness has been established, and an exploration of fault tolerance control is conducted across various fault levels, to identify the preferred fault tolerance strategies corresponding to different levels of fault tolerance. The simulation results show that the designed speed control strategy can improve vehicle safety by decelerating in advance, the fault observer is capable of accurately estimating the true values of actuator and sensor faults. The simulation and vehicle test results demonstrate that similar suspension performance has been obtained by fault-tolerant control strategy and preferred fault tolerance under different fault tolerance levels compared with normal fault tolerance.

Fault tolerance is an important requirement for long-running parallel programs. This paper presents a different approach to fault-tolerance support in message-passing parallel programs based on their structural and behavioral characteristics, commonly known as patterns. A classification of these patterns and their applicable fault-tolerance strategies is aimed to facilitate an application developer to incorporate appropriate fault-tolerance strategies to an application. Fault-tolerance strategies for two of the patterns are discussed, and one specific strategy is elaborated and analyzed. The presented strategies have been incorporated into a fault-tolerance support framework called FT-PAS. One objective of the framework is to separate the fault tolerance related details from an application developer's main objectives (separation-of-concerns). The paper presents the additional key features of the framework, and concludes with a discussion on current and future research directions.

User-directed means the process of carrying out fault tolerance is dynamic and the fault tolerance mode is chosen by users based on application requirements. In this paper, we introduce a general scheme based on standard MPI to provide the user directed support for application level algorithmic fault tolerance. The user-directed fault tolerance plays the role as a connection between applications and algorithmic fault tolerance. As a case study, our scheme has been incorporated to HPL combined with a non-blocking ABFT technique. We have tested the functional availability of our scheme for fault tolerance in real circumstance. We also evaluated that when there is no failure occurring, our support only brings 2.5 percent overhead. When failure occurs, with our scheme, the scalability of algorithmic fault tolerance maintains well.

Due to the poor accessibility, poor operating conditions, high failure rate, long maintenance time, and difficult maintenance of wind hybrid generators, the economic loss is huge once the failure stops. To this end, the fault adaptive fault-tolerant control of distributed wind and wind hybrid generators is studied, the historical operation data of offshore wind and wind hybrid generators and onshore wind and wind hybrid generators are counted and compared, and the fault characteristics of key components of offshore wind and wind hybrid generators are analyzed. The generator sets are summarized, and the common electrical faults of wind turbines and their impacts on the system are analyzed. This paper summarizes the current research status of fault-tolerant operation of existing offshore wind and wind complementary generators in terms of software fault tolerance and hardware fault tolerance, summarizes the current fault tolerance schemes for offshore wind and wind complementary generators, and analyzes the application feasibility of existing fault tolerance schemes. In addition, the main problems of fault-tolerant offshore wind and solar complementary generator sets are pointed out, and future research hotspots are foreseen.

Fault tolerant system based on non-integers order observers: Application in a heat exchanger

With more and more multiprocessor computers coming to the market and applications, system reliability is becoming a key issue of multiprocessor systems. As there is an inherent characteristic of redundancy existing in multiprocessor systems, the way to increase the reliability is aimed at software strategy rather than hardware redundancy. Aiming at realizing fault tolerance and making better utilization of system resources, this paper presents a fault tolerant strategy to increase reliability for multiprocessor systems, which utilizes a common class of operating system algorithm referred to as Self-Scheduling (SS). Simulation results have been analyzed to show the feasibility of the proposed fault tolerant policy.

The power consumption models of mobile application processors have emerged as key objects of interest following the tremendous growth in mobile device production given that such consumption is an important factor in the graphics performance of mobile technologies. Conventionally, the performance of the graphics processing units (GPUs) depends critically on texture mapping units, which is why the number of such GPU components and texture fill rates value prominently whenever the GPU performance is evaluated. Our previous work has established a model to predict maximum performance based on unified shaders. By extending the work, this paper developed a practically applicable GPU performance prediction model on the basis of texture mapping performance. The effects of increased texture mapping units on unified shader performance and GPU efficiency were examined, and a performance prediction model based on the number of frames per second (FPS) was constructed. For these purposes, a benchmark related to texture mapping units was formulated and the experiments were conducted to determine utilization factors that are relevant to GPU performance and efficiency. The final stage in model construction involved establishing a relationship between the previously investigated utilization factors and relevant resources that are consumed during graphics processing. The experimental results showed that the proposed prediction model produced an average error rate of 5.77%.

A survey of approaches to fault tolerant design of VOD servers: Techniques, analysis and comparison