Grid vs. Cloud Computing

Transcription

1 Grid vs. Cloud Computing The similarities and differences between Cloud Computing and Extreme-Scale Computation on Demand 2008 Parabon Inc. All rights reserved Parabon 1 Computation, Inc. All rights reserved.

2 Virtualized Data Center Virtualization brings new capabilities to the data center.

3 Virtualized Data Center Virtualization brings new capabilities to the data center. Grid computing and cloud computing are two types of services that benefit from virtualization.

4 Cloud Computing: IT on Demand Cloud computing enables self-service provisioning of virtual machines.

5 Cloud Computing: IT on Demand Cloud computing enables self-service provisioning of virtual machines.

6 Cloud Computing: IT on Demand Cloud computing enables self-service provisioning of virtual machines. Goal: Simplify deployment of Operating Systems and app servers.

7 Cloud Computing: IT on Demand Cloud computing enables self-service provisioning of virtual machines. Goal: Simplify deployment of Operating Systems and app servers. Characteristics: Small numbers of VM allocations held for long periods of time (days/months).

8 Cloud Computing: IT on Demand Cloud computing enables self-service provisioning of virtual machines. Goal: Simplify deployment of Operating Systems and app servers. Characteristics: Small numbers of VM allocations held for long periods of time (days/months).

9 Cloud Computing: IT on Demand Most servers have utilization rates of just 5-20%; the other 80-95% is wasted capacity. 1 Cloud provisioning tools and virtualization greatly improve utilization rates. Even so, most data centers have massive amounts of capacity that goes unused. UNUSED [1] Taurus - A Taxonomy of the Actual Utilization of Real UNIX and Windows Servers, David G Heap, Principal IT Consultant, IBM Enterprise Server Group, January ibm.com/servers/library/pdf/taurus.pdf

10 Grid: Extreme-Scale Computation on Demand Grid computing solutions enable parallel processing of computational tasks, often using idle vs. dedicated capacity.

11 Grid: Extreme-Scale Computation on Demand Grid computing solutions enable parallel processing of computational tasks, often using idle vs. dedicated capacity. Goals: Accelerate throughput from decades to days or from months to minutes.

12 Grid: Extreme-Scale Computation on Demand Grid computing solutions enable parallel processing of computational tasks, often using idle vs. dedicated capacity. Goals: Accelerate throughput from decades to days or from months to minutes. Enable deep computations that are otherwise intractable.

13 Grid: Extreme-Scale Computation on Demand Grid computing solutions enable parallel processing of computational tasks, often using idle vs. dedicated capacity. Goals: Accelerate throughput from decades to days or from months to minutes. Enable deep computations that are otherwise intractable. Characteristics: Large numbers of work requests run for short periods of time (minutes / hours).

14 The Frontier Grid Platform can share resources with cloud solutions to provide a highperformance compute service using otherwise wasted capacity.

15 The Frontier Grid Platform can share resources with cloud solutions to provide a highperformance compute service using otherwise wasted capacity. The Frontier Grid Server manages execution of largescale computational jobs across hundreds or thousands of compute nodes.

16 The Frontier Compute Engine can be deployed as a small, unobtrusive virtual appliance across the entire data center.

17 The Frontier Compute Engine can be deployed as a small, unobtrusive virtual appliance across the entire data center. Frontier uses resources only when its host has excess capacity. And, it is designed to back off when higher priority processes are present.

18 Computational Work Units Next, we ll watch how Frontier executes a large-scale job in the presence of other VM allocations.

19 Computational Work Units A large job comprised of many tasks is launched against the Frontier Grid Service.

20 Computational Work Units The Frontier Grid Server assigns tasks to compute engines on the grid.

21 Computational Work Units The Frontier Grid Server assigns tasks to compute engines on the grid.

22 Computational Work Units Frontier Compute Engines on hosts with excess capacity begin executing tasks in turn, and results are returned back to the server.

23 Computational Work Units Capacity utilization in the data center increases and the job finishes quickly thanks to mass parallelization.

24 Computational Work Units Capacity utilization in the data center increases and the job finishes quickly thanks to mass parallelization.

25 Computational Work Units Because Frontier runs at low priority, other operations, such as cloud provisioning of new VMs, can proceed as normal.

26 Computational Work Units Because Frontier runs at low priority, other operations, such as cloud provisioning of new VMs, can proceed as normal.

27 Computational Work Units As the job completes, capacity is freed for use by other jobs.

28 Computational Work Units Our job, which would take weeks or months on a single computer, finishes in minutes or hours.

29 Conclusion: Grids Clouds Grid and Cloud computing share some common goals: Deliver computation as a utility Virtualize use of computing resources Eliminate need for dedicated computing resources Dramatically improve computational price-performance But, the services they provide are fundamentally different: Cloud Information Technology (IT) on Demand Grid Extreme-Scale Computation on Demand