The method of mapping tasks to the reconfigurable architecture of the computer system

The method of mapping tasks to the reconfigurable architecture of the computer system and its formalization is proposed. Mapping is based on the task requirements to computing time and on the opportunities of reconfigurable computing system within the constraints defined by the architecture.Предложен метод отображения задач на реконфигурируемую архитектуру вычислительной системы и приведена его формализация. Отображение осуществляется на основании требований задачи ко времени вычисления и возможностей реконфигурируемой вычислительной системы с учетом ограничений, определяемых ее архитектурой

Data-aware workflow scheduling in heterogeneous distributed systems

Data transferring in scientific workflows gradually attracts more attention due to large amounts of data generated by complex scientific workflows will significantly increase the turnaround time of the whole workflow. It is almost impossible to make an optimal or approximate optimal scheduling for the end-to-end workflow without considering the intermediate data movement. In order to reduce the complexity of the workflow-scheduling problem, most researches done so far are constrained by many unrealistic assumptions, which result in non-optimal scheduling in practice. A constraint imposed by most researchers in their algorithms is that a computation site can only start the execution of other tasks after it has completed the execution of the current task and delivered the data generated by this task. We relax this constraint and allow overlap of execution and data movement in order to improve the parallelism of the tasks in the workflow. Furthermore, we generalize the conventional workflow to allow data to be staged in(out) from(to) remote data centers, design and implement an efficient data-aware scheduling strategy. The experimental results show that the turnaround time is reduced significantly in heterogeneous distributed systems by applying our scheduling strategy. To reduce the end-to-end workflow turnaround time, it is crucial to deliver the input, output and intermediate data as fast as possible. However, it is quite often that the throughput is much lower than expected while using single TCP stream to transfer data when the bandwidth of the network is not fully utilized. Multiple TCP streams will benefit the throughput. However, the throughput does not increase monotonically when increasing the number of parallel streams. Based on this observation, we propose to improve the existing throughput prediction models, design and implement a TCP throughput estimation and optimization service in the distributed systems to figure out the optimal configurations of TCP parallel streams. Experimental results show that the proposed estimation and optimization service can predict the throughput dynamically with high accuracy and the throughput can be increased significantly. Throughput optimization along with data-aware workflow scheduling allows us to minimize the end-to-end workflow turnaround time successfully

Monitoring, analysis and optimisation of I/O in parallel applications

High performance computing (HPC) is changing the way science is performed in the 21st Century; experiments that once took enormous amounts of time, were dangerous and often produced inaccurate results can now be performed and refined in a fraction of the time in a simulation environment. Current generation supercomputers are running in excess of 1016 floating point operations per second, and the push towards exascale will see this increase by two orders of magnitude. To achieve this level of performance it is thought that applications may have to scale to potentially billions of simultaneous threads, pushing hardware to its limits and severely impacting failure rates. To reduce the cost of these failures, many applications use checkpointing to periodically save their state to persistent storage, such that, in the event of a failure, computation can be restarted without significant data loss. As computational power has grown by approximately 2x every 18 ? 24 months, persistent storage has lagged behind; checkpointing is fast becoming a bottleneck to performance. Several software and hardware solutions have been presented to solve the current I/O problem being experienced in the HPC community and this thesis examines some of these. Specifically, this thesis presents a tool designed for analysing and optimising the I/O behaviour of scientific applications, as well as a tool designed to allow the rapid analysis of one software solution to the problem of parallel I/O, namely the parallel log-structured file system (PLFS). This thesis ends with an analysis of a modern Lustre file system under contention from multiple applications and multiple compute nodes running the same problem through PLFS. The results and analysis presented outline a framework through which application settings and procurement decisions can be made

Методи та засоби підвищення ефективності обробки інформації в реконфігуровних комп’ютерних системах на базі ПЛІС

У дисертації наведено теоретичне узагальнення і нове вирішення наукової проблеми, що полягає в розвитку теорії організації обробки інформації в комп’ютерних системах на ПЛІС з урахуванням їх функціональних та апаратурних обмежень. Запропоновані методи та засоби включають в себе взаємозв’язані вирішення завдань оптимізації процесу обробки інформації шляхом визначення оптимальної зернистості обчислень, а також зменшення накладних витрат процесу відображення задач на реконфігуровне обчислювальне середовище, що в цілому забезпечує підвищення ефективності обробки інформації в реконфігуровних обчислювальних системах на ПЛІС. Запропоновано нову стратегію взаємної адаптації розв’язуваних задач і обчислювального середовища на ПЛІС, що ґрунтується на варіюванні зернистістю обчислень під час розв’язання задач великої розмірності, та вдосконалено концепцію реалізації локальних розподілених засобів керування відображенням задач на реконфігуровне обчислювальне середовище, що підвищує ефективність врахування фізичних параметрів кристалів ПЛІС на всіх рівнях реалізації реконфігуровних комп’ютерних систем