Denis Caromel, CEO Ac.veEon. Orchestrate and Accelerate Applica.ons. Open Source Cloud Solu.ons Hybrid Cloud: Private with Burst Capacity

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1 Cloud computing et Virtualisation : applications au domaine de la Finance Denis Caromel, CEO Ac.veEon Orchestrate and Accelerate Applica.ons Open Source Cloud Solu.ons Hybrid Cloud: Private with Burst Capacity 1 1

2 Company 2 2

3 ActiveEon Overview q ActiveEon, a software company born of INRIA, founded in 2007, HQ in the French scientific park Sophia Antipolis q Co developing with INRIA ProActive Parallel Suite, a Professional Open Source middleware for parallel, distributed, multi-core computing q Core mission: Scale Beyond Limits q Providing a full range of services for ProActive Parallel Suite q Worldwide production customers and users: 3

4 A Wide Range of Services q Training and Certification Accelerate learning process q Consulting Optimize your infrastructure and maximize ROI q Technical Support - Subscription The guarantee of a quick and efficient assistance q Integration-Development Get ActiveEon s products fine tuned to your specific needs q Partnerships With OEMs and ISVs 4

5 Ac)veEon V O S T O K Moscow, Techno Park 5 5

6 ActiveEon accepted in Skolkovo Foundation 6 6

7 ProAc.ve Parallel Suite 7 7

8 HPC Workflow & Paralleliza.on Scheduling & Orchestra.on Cloud & Grid IaaS 8

9 The ProActive PACA Grid Platform Production Platform operated by: Total: q Cores (soon 1 428) q 480 GPU CUDA Cores q 30TB Storage (soon 150 TB) Publically Available Today 9

10 ProAc.ve Parallel Suite 10 10

11 Technology & Solutions HPC Workflow & Paralleliza.on Studio for HPC, Workflow Visualiza)on Na)ve Tasks (MPI, OpenMP, Mul)- thread, GPU) Java APIs for Paralleliza)on & Distribu)on Matlab & Scilab Distributed Compu)ng Orchestra.on & Scheduling Mul)- Applica)on & Mul)- Tenant Portal with Data Management, Remote Visualiza)on APIs (Java, REST, CLI) Integra)on in exis)ng Applica)ons and Web Portals Cloud & Grid IaaS Physical Machines (Servers, Clusters, Desktops) and Virtual (Hyper- V, VMware, KVM, Xen; OpenStack) Dynamic Policies, Full accoun)ng of resource usage Public Cloud Burst (EC2, Azure, Data Centers) 11

12 Workflow Studio 12

13 Orchestration Portal with Graphical Workflow Visu 13

14 Financial Stress Tests 14

15 ProActive Parallel DEXIA, Belfius Run Monte Carlo Simulations to predict losses in credit portfolio value due to evolutions in credit parameters Compute how much value a portfolio loses/gains in each simulation in order to price a portfolio Users need reactivity Speed up simulations Distribute the computations The simulation software runs as a back-end server and exposes itself as a service addressable by a front-end. Deployed on Citrix servers also used for Virtualization of Desktop PCs 15

16 ProActive Parallel DEXIA, Belfius Ø 100% Virtual Infrastructure User Session ProActive Scheduling Virtual Machine VM User Session VM ProActive Resourcing Virtual Machine Computing Nodes 16

17 UC: Acceleration of Financial Valuations C++ library developed by Pricing Partners Pricing solution dedicated to highly complex derivatives, Greek computation 17

18 How Does it Work? Price-it Computing Distribution Price-it Excel Price-it Excel Regular Price-it Excel Interface ProActive Scheduler Automatic execution via job scheduler Pool of shared resources 18

19 Accelerated Price-it Performances q Increased Productivity: Reduces Price-it Execution Time by 6 or more! More than 3 times faster with only 4 nodes! Even 6 times faster with 9 nodes! Use Case: Bermuda Vanilla, Model American MC Test conditions: One computation is split in 130 tasks that are distributed Each task uses 300ko 4 nodes 5 nodes 6 nodes 7 nodes 8 nodes 9 nodes Sequential Distributed 19

20 Algorithmic Trading 20

21 Integration: Scilab and Matlab, Applications Sta.c Policy LSF Timing Policy 12/24 Dynamic Workload Policy Desktops EC2 Dedicated resources Desktops Amazon EC2 21

22 Oasis INRIA Finance Related Activities 22

23 OASIS Team Previous work (Doan, 2010) American/Bermudian basket option pricing in highly distributed & heterogeneous environment (Cloud architecture) Use of Monte Carlo pricing methods Optimal exercise boundary computation (Ibanez & Zapatero) Classification of continuation and exercise values (Picazo) Use of ProActive for simplified deployment and source code independence 23

24 Currently developed (Benguigui, 2012) High performance computing in hybrid architecture (Cloud/GPU) q Optimal exploitation of GPU (SIMT parallelism, fast access memory use, coalesced memory access, dynamic resource allocation,...) q Hybrid GPU/Cloud deployment (problem decomposition for fine/coarse grained parallel approach, dynamically/abstractly resource exploitation,..) q Validation on large-scale parallel platform 24