High Performance Applications over the Cloud: Gains and Losses

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1 High Performance Applications over the Cloud: Gains and Losses Dr. Leila Ismail Faculty of Information Technology United Arab Emirates University Ankabut Users Meeting January 2012 Collaboration: Nimrod-G Project 1

2 Introduction Agenda What is cloud computing? Benefits of cloud computing What is HPC? Cloud computing challenges Go to market: experimentations with Amazon cloud Conclusions 2

3 NIST SP September 2011 Cloud Computing Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics, three service models, and four deployment models. 3

4 Cloud Computing Characteristics 1. On-demand self-service 2. Broad network access 3. Resource pooling 4. Rapid elasticity 5. Measured service 4

5 Cloud Computing Service Models Infrastructure as a Service (IaaS) (provisioning of processing, storage and network to deploy OSs and users applications) Platform as a Service (PaaS) (means of deploying users applications: programming languages, libraries, tools, etc.) Software as a Service (SaaS) (providers applications) Middleware (automatic scheduling, resource allocation, provisioning, virtualization, metering, billing, data storage management, etc.) Physical Layer/hardware resources (server, storage and network) 5

6 Cloud Computing Types 1) Private cloud Exclusive use by a single company 2) Community cloud Exclusive use by a specific group of consumers/companies of common interest 3) Public cloud Used by the public 4) Hybrid cloud Any combination of above types 6

7 Cloud Computing Challenges Fast allocation of instances Performance of dynamic allocation, provisioning, virtualization, etc. Scalable infrastructure Monitoring Dynamic construction of loosely coupled architectures Usability and user trust in pricing Security models 7

8 8 Where is HPC used? Today, HPC directly impacts our lives in ways we seldom recognize. Product packaging, golf balls, and even diapers are all better because of HPC.

9 Advancements in HPC HPC is Now Everywhere FINANCE Portfolio risk analysis and optimization, derivatives pricing, fraud detection... ENGINEERING Simulate mechanical and electronic systems before building costly prototypes RESEARCH / DEVELOPMENT Simulate the effects and prognosis of chemotherapy, radiation, and surgery ENTERTAINMENT Render photo-realistic scenes, customer materials, product illustrations and videos WEATHER AND CLIMATE Weather and climate forecasting OIL AND GAS Analyze seismic data to find oil and gas and determine how to extract it in the most efficient way 9

10 A serial problem Cache 4 10

11 A Semi-Parallel Execution Cache 4 11

12 Parallel Task Cache 4 12

13 Flavors of Parallel Architectures Shared Memory SMP Easy to Program (Shmem/OpenMP) Easy to Administer Difficult to Scale ~64p NUMA Easy to Program (Shmem/OpenMP/MPI) Easy to Administer Proprietary/Expensive Scales Well ~1024p Cluster Distributed Memory Difficult to Program (MPI) Less Flexible to Administer Price Competitive Highly Scalable ~4096p 13

14 HPC in the Region Oil and Gas is the largest segment that uses HPC in this region Followed by Education 22.4% of TOP500 HPC systems are used by Researchers 15% of TOP500 HPC systems are used by Academia 57.6% of TOP500 HPC systems are used by Industry Ankabut Users' Meeting January

15 HPC Cloud Components Ankabut Users' Meeting January

16 Integration and Testing System Management HPC Cloud Software Components Cloud API Operating System File System Compilers Libraries Cluster Management Runtime Tools Application Software Backup and Archiving Visualization Ankabut Users' Meeting January

17 Today s Limitations of the HPC Memory Bandwidth Commodity memory interfaces [SDRAM, RDRAM, DDRAM] Up to 85% CPU Cycles Waiting for Memory Communications fabric/cpu/memory Integration Limits bandwidth and latency and communication semantics Node and system packaging density Commodity components and cooling technologies limit densities Applications Has little functionality of checkpointing Don t survive multiple failure Are not many-core efficient but departmental and single applications clusters are highly successful 17

18 Cloud computing in 2012 $900 million investment in datacenters in USA and Ireland by Microsoft $600 million datacenter in Oklahoma by Google $100 million in Ireland, Singapore, Taiwan and Hong Kong by Google $450 million datacenter in North Calorina by facebook to support image sharing and SaaS cloud computing Article by Oleg Komissarov, VP of Entreprise Solutions, New York, 15 December

19 Amazon Cloud Computing Amazon Elastic Compute Cloud (EC2) Use web service API to create, start, and terminate instances Choose instances type(s) and OS Standard (small, medium, large) Micro High-memory (extra-large, double extra-large, quadruple extra-large) High-CPU (medium, extra-large) Cluster compute (quadruple extra-large, eight extra-large) Cluster GPU (quadruple extra-large) Computing Unit GHz 2007 Opteron or 2007 Xeon or early GHz Xeon CPU Attach persistent storage to instances Pay for the resources as you use per hour 19

20 Experimental Environment Amazon Elastic Compute Cloud (EC2) (16 virtual cores) 20

21 Cost per Use Platform Type Price/hour ($) per Node Number of Machines Uses Amazon Standard Large Amazon High-CPU Extra Large Amazon Cluster Large

22 Conclusions Cost increases with communication needs Reduce cost when executions are very well planned and predictable (e.g. production phase) Research challenges in optimization of Cloud middleware 22

23 Thank you! 23

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