5,570 research outputs found
Market-Based Resourse Management for Many-Core Systems
101 σ.Αντικείμενο της διπλωματικής αποτελεί η μελέτη και η ανάπτυξη μιας κλιμακώσιμης και κατανεμημένης πλατφόρμας (framework) διαχείρισης πόρων σε χρόνο εκτέλεσης για συστήματα πολλαπλών πυρήνων. Σε αυτήν την πλατφόρμα η διαχείριση πόρων είναι βασισμένη σε μοντέλα, τα οποία είναι εμπνευσμένα από την οικονομία. Παρουσιάζεται ένας διαχειριστής πόρων, ο οποίος προσφέρει ένα περιβάλλον διαχείρισης πόρων και εφαρμογών καθ ́ όλη τη διάρκεια ζωής τους, στο οποίο η κατανομή και δρομολόγηση των εφαρμογών στους πόρους πραγματοποιείται με αλγόριθμους βασισμένους σε κανόνες αγοράς. Η αποδοτικότητα κάθε μοντέλου αξιολογείται βάσει της πτώσης της αξιοπιστίας των πόρων (μετρική MTTF-Mean Time To Failure).The purpose of this diploma thesis is the design and development of a scalable and distributed run-time resource management framework for Many-core systems. In this framework, resource management is based on economy-inspired models. The presented
resource management framework offers an environment that manages both application tasks and resources at run-time, matches and distributes application tasks across resources with algorithms which are based on market principles. The efficiency of each model is
evaluated with respect to resource reliability degradation (metric MTTF-Mean Time to Failure).Θεμιστοκλής Γ. Μελισσάρη
An Efficient Thread Mapping Strategy for Multiprogramming on Manycore Processors
The emergence of multicore and manycore processors is set to change the
parallel computing world. Applications are shifting towards increased
parallelism in order to utilise these architectures efficiently. This leads to
a situation where every application creates its desirable number of threads,
based on its parallel nature and the system resources allowance. Task
scheduling in such a multithreaded multiprogramming environment is a
significant challenge. In task scheduling, not only the order of the execution,
but also the mapping of threads to the execution resources is of a great
importance. In this paper we state and discuss some fundamental rules based on
results obtained from selected applications of the BOTS benchmarks on the
64-core TILEPro64 processor. We demonstrate how previously efficient mapping
policies such as those of the SMP Linux scheduler become inefficient when the
number of threads and cores grows. We propose a novel, low-overhead technique,
a heuristic based on the amount of time spent by each CPU doing some useful
work, to fairly distribute the workloads amongst the cores in a
multiprogramming environment. Our novel approach could be implemented as a
pragma similar to those in the new task-based OpenMP versions, or can be
incorporated as a distributed thread mapping mechanism in future manycore
programming frameworks. We show that our thread mapping scheme can outperform
the native GNU/Linux thread scheduler in both single-programming and
multiprogramming environments.Comment: ParCo Conference, Munich, Germany, 201
A Recursive Data-Driven Approach to Programming Multicore Systems
In this paper, we propose a method to program divide-and-conquer problems on multicore systems that is based on a data-driven recursive programming model. Data intensive programs are difficult to program on multicore architectures because they require efficient utilization of inter-core communication. Models for programming multicore systems available today generally lack the ability to automatically extract concurrency from a sequential style program and map concurrent tasks to efficiently leverage data and temporal locality. For divide-and-conquer algorithms, a recursive programming model can address both of these problems. Furthermore, since a recursive function has the same behavior patterns at all granularities of a problem, the same recursive model can be used to implement a multicore program at all of its levels: 1. the operations of a single core, 2. how to distribute tasks among several cores, and 3. in what order to schedule tasks on a multicore system when it is not possible to schedule all of the tasks at the same time. We present a novel selective execution technique that can enable automatic parallelization and task mapping of a recursive program onto a multicore system. To verify the practicality of this approach, we perform a case-study of bitonic sort on the Cell BE processor
Accelerating sequential programs using FastFlow and self-offloading
FastFlow is a programming environment specifically targeting cache-coherent
shared-memory multi-cores. FastFlow is implemented as a stack of C++ template
libraries built on top of lock-free (fence-free) synchronization mechanisms. In
this paper we present a further evolution of FastFlow enabling programmers to
offload part of their workload on a dynamically created software accelerator
running on unused CPUs. The offloaded function can be easily derived from
pre-existing sequential code. We emphasize in particular the effective
trade-off between human productivity and execution efficiency of the approach.Comment: 17 pages + cove
Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules
Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In this paper we present an approach that combines a neural embedding model and logic-based modules to accurately divide an input ontology matching task into smaller and more tractable matching (sub)tasks. We have conducted a comprehensive evaluation using the datasets of the Ontology Alignment Evaluation Initiative. The results are encouraging and suggest that the proposed method is adequate in practice and can be integrated within the workflow of systems unable to cope with very large ontologies
- …