2,859 research outputs found
Partially shared buffers with full or mixed priority
This paper studies a finite-sized discrete-time two-class priority queue. Packets of both classes arrive according to a two-class discrete batch Markovian arrival process (2-DBMAP), taking into account the correlated nature of arrivals in heterogeneous telecommunication networks. The model incorporates time and space priority to provide different types of service to each class. One of both classes receives absolute time priority in order to minimize its delay. Space priority is implemented by the partial buffer sharing acceptance policy and can be provided to the class receiving time priority or to the other class. This choice gives rise to two different queueing models and this paper analyses both these models in a unified manner. Furthermore, the buffer finiteness and the use of space priority raise some issues on the order of arrivals in a slot. This paper does not assume that all arrivals from one class enter the queue before those of the other class. Instead, a string representation for sequences of arriving packets and a probability measure on the set of such strings are introduced. This naturally gives rise to the notion of intra-slot space priority. Performance of these queueing systems is then determined using matrix-analytic techniques. The numerical examples explore the range of service differentiation covered by both models
Bulk Scheduling with the DIANA Scheduler
Results from the research and development of a Data Intensive and Network
Aware (DIANA) scheduling engine, to be used primarily for data intensive
sciences such as physics analysis, are described. In Grid analyses, tasks can
involve thousands of computing, data handling, and network resources. The
central problem in the scheduling of these resources is the coordinated
management of computation and data at multiple locations and not just data
replication or movement. However, this can prove to be a rather costly
operation and efficient sing can be a challenge if compute and data resources
are mapped without considering network costs. We have implemented an adaptive
algorithm within the so-called DIANA Scheduler which takes into account data
location and size, network performance and computation capability in order to
enable efficient global scheduling. DIANA is a performance-aware and
economy-guided Meta Scheduler. It iteratively allocates each job to the site
that is most likely to produce the best performance as well as optimizing the
global queue for any remaining jobs. Therefore it is equally suitable whether a
single job is being submitted or bulk scheduling is being performed. Results
indicate that considerable performance improvements can be gained by adopting
the DIANA scheduling approach.Comment: 12 pages, 11 figures. To be published in the IEEE Transactions in
Nuclear Science, IEEE Press. 200
Configurable Strategies for Work-stealing
Work-stealing systems are typically oblivious to the nature of the tasks they
are scheduling. For instance, they do not know or take into account how long a
task will take to execute or how many subtasks it will spawn. Moreover, the
actual task execution order is typically determined by the underlying task
storage data structure, and cannot be changed. There are thus possibilities for
optimizing task parallel executions by providing information on specific tasks
and their preferred execution order to the scheduling system.
We introduce scheduling strategies to enable applications to dynamically
provide hints to the task-scheduling system on the nature of specific tasks.
Scheduling strategies can be used to independently control both local task
execution order as well as steal order. In contrast to conventional scheduling
policies that are normally global in scope, strategies allow the scheduler to
apply optimizations on individual tasks. This flexibility greatly improves
composability as it allows the scheduler to apply different, specific
scheduling choices for different parts of applications simultaneously. We
present a number of benchmarks that highlight diverse, beneficial effects that
can be achieved with scheduling strategies. Some benchmarks (branch-and-bound,
single-source shortest path) show that prioritization of tasks can reduce the
total amount of work compared to standard work-stealing execution order. For
other benchmarks (triangle strip generation) qualitatively better results can
be achieved in shorter time. Other optimizations, such as dynamic merging of
tasks or stealing of half the work, instead of half the tasks, are also shown
to improve performance. Composability is demonstrated by examples that combine
different strategies, both within the same kernel (prefix sum) as well as when
scheduling multiple kernels (prefix sum and unbalanced tree search)
Flexible Scheduling in Multimedia Kernels: an Overview
Current Hard Real-Time (HRT) kernels have their timely behaviour guaranteed on the cost of a rather restrictive use of the available resources. This makes current HRT scheduling techniques inadequate for use in a multimedia environment where we can make a considerable profit by a better and more flexible use of the resources. We will show that we can improve the flexibility and efficiency of multimedia kernels. Therefore we introduce Real Time Transactions (RTT) with Deadline Inheritance policies for a small class of scheduling algorithms and we will evaluate these algorithms for use in a multimedia environmen
Engineering Parallel String Sorting
We discuss how string sorting algorithms can be parallelized on modern
multi-core shared memory machines. As a synthesis of the best sequential string
sorting algorithms and successful parallel sorting algorithms for atomic
objects, we first propose string sample sort. The algorithm makes effective use
of the memory hierarchy, uses additional word level parallelism, and largely
avoids branch mispredictions. Then we focus on NUMA architectures, and develop
parallel multiway LCP-merge and -mergesort to reduce the number of random
memory accesses to remote nodes. Additionally, we parallelize variants of
multikey quicksort and radix sort that are also useful in certain situations.
Comprehensive experiments on five current multi-core platforms are then
reported and discussed. The experiments show that our implementations scale
very well on real-world inputs and modern machines.Comment: 46 pages, extension of "Parallel String Sample Sort" arXiv:1305.115
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