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QLSE: DESIGN CHOICES

QoS-CONSTRAINED LIST SCHEDULING HEURISTICS FOR PARALLEL APPLICATIONS ON GRIDS R. BARAGLIA, R.FERRINI, N.TONELLOTTO ISTI, CNR, Pisa, Italy L.RICCI DEPARTMENT OF COMPUTER SCIENCE UNIVERSITY OF PISA R. YAHYAPOUR INSTITUTE FOR ROBOTICS RESEARCH, UNIVERSITY OF DORTMUND. QLSE: DESIGN CHOICES.

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QLSE: DESIGN CHOICES

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  1. QoS-CONSTRAINED LIST SCHEDULING HEURISTICS FOR PARALLEL APPLICATIONS ON GRIDSR. BARAGLIA, R.FERRINI, N.TONELLOTTO ISTI, CNR, Pisa, ItalyL.RICCIDEPARTMENT OF COMPUTER SCIENCEUNIVERSITY OF PISAR. YAHYAPOUR INSTITUTE FOR ROBOTICS RESEARCH, UNIVERSITY OF DORTMUND

  2. QLSE: DESIGN CHOICES • QoS-constrained List Scheduling hEuristics for Parallel Applications on Grids: • a launch timealgorithm to map parallel applications on Wide Area Grids • Basic assumption: the user specifies a set of Quality of Service Requirements • Computational power • Communication bandwidth • Algorithm goals • To satisfy user QoS requirements • Fast allocation of tasks to minimize the aging effect • A List Scheduling based solution

  3. APPLICATION MODEL The application is modelled by a Task Interaction Graph (TIG) where • each node corresponds to a task of the application and is associated with the Minimal Computational Request (MCR) • each edge is associated with theMinimal Bandwidth Request (MBR)

  4. GRID MODEL • A set of LANs connected through an unreliable network • Each LAN is characterized by • the number of hostsandthe Computational Power (CP) of each host • the internal Communication Bandwidth (CB) • Two LANs are directly connected in the graph if the communication bandwidth between them is  a predefined threshold (es:1Mb/s)

  5. QLSE: GENERAL STRUCTURE QSLE main goal: map highly communicating tasks on the same LAN or onto a set of LAN connected by high bandwidth links Overall strategy: cluster the grid graph so that the LAN belonging to each cluster are characterized by high communication bandwith try to map the application tasks to the hosts of the same cluster by a list scheduling approach. The mapping must satisfy the QoS specified by the user if no solution is found, try a further clustering characterized by a lower communication bandwidth

  6. QLSE: LIST SCHEDULING List Scheduling is applied to map the application tasks to the LAN of a cluster requires an ordered list of the application tasks and of LANs belonging to the same cluster All application tasks are ordered according to the MCR of the Task the topology of the TIG The LAN available within a cluster are ordered according to the computational power of the LAN’s hosts the bandwidth of the links between LANs directly connected .

  7. TASK ORDERING 1) Assignment of a priority to a taskTi takes into account: • the MCR(Minimal Computational Requirement) of Ti • the sum of the MBRs(Minimal Bandwith Requirement)of the Ti. • a percentage of sum of the MCRs of the tasks interacting with Ti priorityi = MCRi +aijE (MBRijT MCRj) 2)Re-structuring of the TIG into a task hierarchical graph THG rooted at the highest priority task 3) Ordering of the tasks within the same level of the THG according to • the number of communicatingtasks • the value of their priority

  8. TASK HIERARCHICAL GRAPH Tasks 11 and 12 are in the same level because they have a parent in the previous level Application TIG Task 2 and 5 are brothers because they interact Task Hierarchical Graph • Cycle Management: Tasks belonging to a cycle are put in the same cluster

  9. GRID CLUSTERING • Consider the quartiles of the bandwidth distribution in decreasing order • Cluster the grid according to each quartile’s value, and try to map the tasks on the hosts of the same cluster • If no solution is found, consider the next quartile

  10. LAN ORDERING LAN belonging to the same cluster are ordered w.r.t. the priority of the LAN The priority value of a LAN Li is computed as the sum of: • the computational power of the hosts in Li • the sum of the bandwidth of the links between Li and the directly connected LANs. • a percentage of sum of the computationalpower of the LANs connected to Li

  11. LAN SUITABILITY A LAN L is suitable to host a task T iff: • at least a host of L has a computational power ≥than the MCR of T • the sum of the MBRs of the TIG edges between T and the communicating tasks already allocated on L isthan the LAN bandwidth • the sum of the MBRs of the TIG edges between T and the communicating tasks already allocated on another LAN L' is than the link bandwidth between L and L‘ 1) The computational power of the host where T is mapped 2) the internal bandwidth of L 3) the bandwidth between L and L' are decreased according to the corresponding values of the TIG

  12. QSLE: THE ALGORITHM • Compute the priority of each task • Build the hierarchical structure of the TIG eliminating cyclic paths • Build the Task Allocation List (TAL) • Compute the quartile of the grid graphs • For each quartile • cluster the grid graph • rank the cluster by summing the priorities of the LANs inside the cluster and build the cluster allocation list (CAL) • for each cluster in CAL • order the LAN in the clusters according to their priority • select the first task T from TAL and the first LAN, from the LAN list, which is suitable for T • if such a LAN exists, allocate the task on the LAN, then consider next task, else consider the next cluster • if no allocation has been found examine next quartile

  13. AVERAGE PERCENTAGE OF FAILURES • QLSE has been evaluated through a set of simulations • Greedy Scheduling: • tasks are ordered w.r.t MCR and LAN are ordered w.r.t aggregate computational power,the host of a LAN ordered w.r.t computational power • best fit heuristics

  14. AVERAGE LAN HIT RATIOS • LAN hit ratio • ratio between the sum of the TIG's MBRs of communicating tasks • allocated on the same LAN and the TIG's MBR sum • measures the percentage of communications allocated on the • same LAN

  15. AVERAGE TASK-MACHINE COMPUTATIONAL RATIO • Task-Machine Computational Ratio • ratio between the computational power of the achine where a • task is mapped and the MCR of the task • measueres how powerful machines are exploited to run the tasks • of the TIG

  16. CONCLUSIONS • QLSE: a mapping heuristics based on both application computational and • communication requirements (QoS) • Experimental results demonstrates that QLSE is able to carry out a valid solution in almost 100% of the simulated test cases • Future work: • A deeper evaluation of QLSE • An evaluation of QLSE through real applications and Grid testbeds

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