Browsing by Author "Raravi, Gurulingesh"
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- Assigning real-time tasks on heterogeneous multiprocessors with two unrelated types of processorsPublication . Raravi, Gurulingesh; Andersson, Björn; Bletsas, KonstantinosConsider the problem of partitioned scheduling of an implicit-deadline sporadic task set on heterogeneous multiprocessors to meet all deadlines. Each processor is either of type-1 or type-2. We present a new algorithm, FF-3C, for this problem. FF-3C offers low time-complexity and provably good performance. Specifically, FF-3C offers (i) a time-complexity of O(n⋅max(m,logn)+m⋅logm), where n is the number of tasks and m is the number of processors and (ii) the guarantee that if a task set can be scheduled by an optimal partitioned-scheduling algorithm to meet all deadlines then FF-3C meets all deadlines as well if given processors at most 11−α times as fast (referred to as speed competitive ratio) and tasks are scheduled using EDF; where α is a property of the task set. The parameter α is in the range (0,0.5] and for each task, it holds that its utilization is no greater than α or greater than 1−α on each processor type. Thus, the speed competitive ratio of FF-3C can never exceed 2. We also present several extensions to FF-3C; these offer the same performance guarantee and time-complexity but with improved average-case performance. Via simulations, we compare the performance of our new algorithms and two state-of-the-art algorithms (and variations of the latter). We evaluate algorithms based on (i) running time and (ii) the necessary multiplication factor, i.e., the amount of extra speed of processors that the algorithm needs, for a given task set, so as to succeed, compared to an optimal task assignment algorithm. Overall, we observed that our new algorithms perform significantly better than the state-of-the-art. We also observed that our algorithms perform much better in practice, i.e., the necessary multiplication factor of the algorithms is much smaller than their speed competitive ratio. Finally, we also present a clustered version of the new algorithm.
- Calculating an upper bound on the finishing time of a group of threads executing on a GPU: a preliminary case studyPublication . Raravi, Gurulingesh; Andersson, BjörnGraphics processor units (GPUs) today can be used for computations that go beyond graphics and such use can attain a performance that is orders of magnitude greater than a normal processor. The software executing on a graphics processor is composed of a set of (often thousands of) threads which operate on different parts of the data and thereby jointly compute a result which is delivered to another thread executing on the main processor. Hence the response time of a thread executing on the main processor is dependent on the finishing time of the execution of threads executing on the GPU. Therefore, we present a simple method for calculating an upper bound on the finishing time of threads executing on a GPU, in particular NVIDIA Fermi. Developing such a method is nontrivial because threads executing on a GPU share hardware resources at very fine granularity.
- A conjecture about provably good task assignment on heterogeneous multiprocessor platforms but with a stronger adversaryPublication . Raravi, Gurulingesh; Andersson, Björn; Bletsas, KonstantinosConsider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a heterogeneous multiprocessor platform. We use an algorithm proposed in [1] (we refer to it as LP-EE) from state-of-the-art for assigning tasks to heterogeneous multiprocessor platform and (re-)prove its performance guarantee but for a stronger adversary.We conjecture that if a task set can be scheduled to meet deadlines on a heterogeneous multiprocessor platform by an optimal task assignment scheme that allows task migrations then LP-EE meets deadlines as well with no migrations if given processors twice as fast. We illustrate this with an example.
- Intra-type migrative scheduling of implicit-deadline sporadic tasks on two- type heterogeneous multiprocessorPublication . Raravi, Gurulingesh; Andersson, Björn; Bletsas, KonstantinosConsider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a two-type heterogeneous multiprocessor platform. Each processor is either of type-1 or type-2 with each task having different execution time on each processor type. Jobs can migrate between processors of same type (referred to as intra-type migration) but cannot migrate between processors of different types. We present a new scheduling algorithm namely, LP-Relax(THR) which offers a guarantee that if a task set can be scheduled to meet deadlines by an optimal task assignment scheme that allows intra-type migration then LP-Relax(THR) meets deadlines as well with intra-type migration if given processors 1/THR as fast (referred to as speed competitive ratio) where THR <= 2/3.
- A Multi-DAG Model for Real-Time Parallel Applications with Conditional ExecutionPublication . Fonseca, José; Nélis, Vincent; Raravi, Gurulingesh; Pinho, Luís MiguelOwing to the current trends for higher performance and the ever growing availability of multiprocessors in the embedded computing (EC) domain, there is nowadays a strong push towards the parallelization of modern embedded applications. Several real-time task models have recently been proposed to capture different forms of parallelism. However, they do not deal explicitly with control flow information as they assume that all the threads of a parallel task must execute every time the task is activated. In contrast, in this paper, we present a multi-DAG model where each task is characterized by a set of execution flows, each of which represents a different execution path throughout the task code and is modeled as a DAG of sub-tasks. We propose a two-step solution that computes a single synchronous DAG of servers for a task modeled by a multi-DAG and show that these servers are able to supply every execution flow of that task with the required cpu-budget so that the task can execute entirely, irrespective of the execution flow taken at run-time, while satisfying its precedence constraints. As a result, each task can be modeled by its single DAG of servers, which facilitates in leveraging the existing single-DAG schedulability analyses techniques for analyzing the schedulability of parallel tasks with multiple execution flows.
- Partitioned scheduling of multimode systems on multiprocessor platforms: when to do the mode transition?Publication . Marinho, José; Raravi, Gurulingesh; Nélis, Vincent; Petters, Stefan M.Systems composed of distinct operational modes are a common necessity for embedded applications with strict timing requirements. With the emergence of multi-core platforms protocols to handle these systems are required in order to provide this basic functionality.In this work a description on the problems of creating an effective mode-transition protocol are presented and it is proven that in some cases previous single-core protocols can not be extended to handle the mode-transition in multi-core.
- Provably good scheduling of sporadic tasks with resource sharing on a two-type heterogeneous multiprocessor platformPublication . Raravi, Gurulingesh; Andersson, Björn; Bletsas, KonstantinosConsider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a two-type heterogeneous multiprocessor platform where a task may request at most one of |R| shared resources. There are m1 processors of type-1 and m2 processors of type-2. Tasks may migrate only when requesting or releasing resources. We present a new algorithm, FF-3C-vpr, which offers a guarantee that if a task set is schedulable to meet deadlines by an optimal task assignment scheme that only allows tasks to migrate when requesting or releasing a resource, then FF-3Cvpr also meets deadlines if given processors 4+6*ceil(|R|/min(m1,m2)) times as fast. As far as we know, it is the first result for resource sharing on heterogeneous platforms with provable performance.
- Provably Good Task Assignment for Two-Type Heterogeneous Multiprocessors Using Cutting PlanesPublication . Andersson, Björn; Raravi, GurulingeshConsider scheduling of real-time tasks on a multiprocessor where migration is forbidden. Specifically, consider the problem of determining a task-to-processor assignment for a given collection of implicit-deadline sporadic tasks upon a multiprocessor platform in which there are two distinct types of processors. For this problem, we propose a new algorithm, LPC (task assignment based on solving a Linear Program with Cutting planes). The algorithm offers the following guarantee: for a given task set and a platform, if there exists a feasible task-to-processor assignment, then LPC succeeds in finding such a feasible task-to-processor assignment as well but on a platform in which each processor is 1.5 × faster and has three additional processors. For systems with a large number of processors, LPC has a better approximation ratio than state-of-the-art algorithms. To the best of our knowledge, this is the first work that develops a provably good real-time task assignment algorithm using cutting planes.
- Provably good task assignment on heterogeneous multiprocessor platforms for a restricted case but with a stronger adversaryPublication . Raravi, Gurulingesh; Andersson, Björn; Bletsas, KonstantinosConsider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a heterogeneous multiprocessor platform. We consider a restricted case where the maximum utilization of any task on any processor in the system is no greater than one. We use an algorithm proposed in [1] (we refer to it as LP-EE) from state-of-the-art for assigning tasks to heterogeneous multiprocessor platform and (re-)prove its performance guarantee for this restricted case but for a stronger adversary. We show that if a task set can be scheduled to meet deadlines on a heterogeneous multiprocessor platform by an optimal task assignment scheme that allows task migrations then LP-EE meets deadlines as well with no migrations if given processors twice as fast.
- A PTAS for assigning sporadic tasks on two-type heterogeneous multiprocessorsPublication . Raravi, Gurulingesh; Nélis, VincentConsider the problem of determining a task-toprocessor assignment for a given collection of implicit-deadline sporadic tasks upon a multiprocessor platform in which there are two distinct kinds of processors. We propose a polynomialtime approximation scheme (PTAS) for this problem. It offers the following guarantee: for a given task set and a given platform, if there exists a feasible task-to-processor assignment, then given an input parameter, ϵ, our PTAS succeeds, in polynomial time, in finding such a feasible task-to-processor assignment on a platform in which each processor is 1+3ϵ times faster. In the simulations, our PTAS outperforms the state-of-the-art PTAS [1] and also for the vast majority of task sets, it requires significantly smaller processor speedup than (its upper bound of) 1+3ϵ for successfully determining a feasible task-to-processor assignment.