Scheduling of Early Quantum Tasks

An Early Quantum Task (EQT) is a Quantum EDF task that has shrunk its first period into one quantum time slot. Its purpose is to be executed as soon as possible, without causing deadline overflow of other tasks. We will derive the conditions under which an EQT can be admitted and can have an immediate start. The advantage of scheduling EQTs is shown by its use in a buffered multi-media server. The EQT is associated with a multimedia stream and it will use its first invocation to fill the buffer, such that a client can start receiving data immediately

Early quantum task scheduling

An Early Quantum Task (EQT) is a Quantum EDF task that has shrunk its first period into one quantum time slot. Its purpose is to be executed as soon as possible, without causing deadline overflow of other tasks. We will derive the conditions under which an EQT can be admitted and can have an immediate start. The advantage of scheduling EQTs is shown by its use in a buffered multi-media server. The EQT is associated with a multimedia stream and it will use its first invocation to fill the buffer, such that a client can start receiving data immediately

A case against periodic jukebox scheduling

This paper presents the jukebox early quantum scheduler (JEQS). JEQS is a periodic jukebox scheduler for a Video-on-Demand system. JEQS uses the jukebox robots in a cyclic way and the time is divided in constant units called quanta. A quantum is the maximum time needed to unload and load all the drives. An RSM is loaded in a drive for a fixed period of time, corresponding to the time needed to switch the media on the other drives. During this time the drive can read data from it. JEQS is based on the scheduling theory on early quantum tasks (EQT). An early quantum task executes its first instance in the next quantum after its arrival and the rest of the instances are scheduled in a normal periodic way with the release time immediately after the first execution. Although JEQS is an efficient periodic scheduler, that can guarantee the execution of most tasks in the next cycle after the requests arrive, we show that using JEQS results in much longer response times than using a-periodic schedulers. Furthermore, we show that the bad performance of JEQS is intrinsic to any periodic jukebox scheduler. The only advantage of using a periodic scheduler is that the scheduling algorithms are less complex. However, the simplicity of the algorithms clearly does not outweigh the unacceptably long response times

Promote-IT: An efficient Real-Time Tertiary-Storage Scheduler

Promote-IT is an efficient heuristic scheduler that provides QoS guarantees for accessing data from tertiary storage. It can deal with a wide variety of requests and jukebox hardware. It provides short response and confirmation times, and makes good use of the jukebox resources. It separates the scheduling and dispatching functionality and effectively uses this separation to dispatch tasks earlier than scheduled, provided that the resource constraints are respected and no task misses its deadline. To prove the efficiency of Promote-IT we implemented alternative schedulers based on different scheduling models and scheduling paradigms. The evaluation shows that Promote-IT performs better than the other heuristic schedulers. Additionally, Promote-IT provides response-times near the optimum in cases where the optimal scheduler can be computed

Scalable Task-Based Algorithm for Multiplication of Block-Rank-Sparse Matrices

A task-based formulation of Scalable Universal Matrix Multiplication Algorithm (SUMMA), a popular algorithm for matrix multiplication (MM), is applied to the multiplication of hierarchy-free, rank-structured matrices that appear in the domain of quantum chemistry (QC). The novel features of our formulation are: (1) concurrent scheduling of multiple SUMMA iterations, and (2) fine-grained task-based composition. These features make it tolerant of the load imbalance due to the irregular matrix structure and eliminate all artifactual sources of global synchronization.Scalability of iterative computation of square-root inverse of block-rank-sparse QC matrices is demonstrated; for full-rank (dense) matrices the performance of our SUMMA formulation usually exceeds that of the state-of-the-art dense MM implementations (ScaLAPACK and Cyclops Tensor Framework).Comment: 8 pages, 6 figures, accepted to IA3 2015. arXiv admin note: text overlap with arXiv:1504.0504