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Oct 16, 2012

Computing Systems Research in IBM Haifa. Dorit Nuzman, IBM Haifa Research Laboratory (HRL) Contact: dorit@il.ibm.com. Oct 16, 2012. IBM Haifa Research Lab – Facts and Figures. 450 people, including researchers, engineers, and business operations Largest IBM Research facility outside the US

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Oct 16, 2012

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  1. Computing Systems Research in IBM Haifa Dorit Nuzman, IBM Haifa Research Laboratory (HRL) Contact: dorit@il.ibm.com Oct 16, 2012

  2. IBM Haifa Research Lab – Facts and Figures • 450 people, including researchers, engineers, and business operations • Largest IBM Research facility outside the US • Spanning many areas System Optimization System ICT Infrastructure Software Quality Mathematical Optimization Collaboration and Social Networking Analytics Services Healthcare andTelco Electronics Design Automation

  3. Our Mission • Research • Architecture • Implementation • Deployment and Support Mission: Develop advanced computing system technologies and code analysis and optimization tools aimed to help IBM lead with IT products and services. Engagements w/IBM Customers

  4. R A E System Technology and Services Collaborations with European Academic and Industrial Organizations https://www.research.ibm.com/haifa/dept/stt/index.html HiPEAC Steering committee member of the the European Network of Excellence on High Performance and Embedded Architecture and Compilation ERA – Embedded Reconfigurable Architectures Focuses on new methodologies in both tools and hardware design to help design next-generation embedded systems platforms. IOLanes Focuses on I/O performance in modern hardware that employs multicore architectures, by adapting or redesigning the I/O stack. Milepost The first practical attempt to build machine learning enabled open-source self-tuning compiler that can adapt to any architecture using iterative feedback-directed compilation, machine learning and collective optimization. ACOTES - Advanced Compiler Technologies for Embedded Streaming Use efficient compilation techniques and new programming model, to enable a dramatic increase in productivity for application programmers to leverage the benefits of parallel computing and drive down power consumption in mobile devices. ENSURE Aims at ensuring long term usability for the spiraling amounts of data produced or controlled by organizations with commercial interests. Drawing on motivation from use cases in healthcare, finance, and clinical trials, ENSURE will significantly extend the state-of-the-art in digital preservation, which to-date has focused on relatively homogeneous cultural heritage data.

  5. System Technology and Services Collaborations with European Academic and Industrial Organizations Fi-ware Foundation for Future Internet (FI): Provide core platform for FI applications across multiple industries (‘Usage Area’ projects) VISION Introduces a powerful ICT infrastructure for reliable and effective delivery of data-intensive storage services, facilitating the convergence of ICT, media, and telecommunications. This infrastructure will support the setup and deployment of data and storage services on demand, at competitive costs, across disparate administrative domains, while providing QoS and security guarantees Reservoir Advanced technologies for cloud computing management middleware, providing automation of processes in a cloud environment and scalability of infrastructure thru federation FITTEST – Future Internet Testing Aims to attack the problems of testing the Future Internet with search based testing.Future Internet includes complex interconnection of services, applications, content, and media, upon which our society will become increasingly dependent for critical activities such as social services, learning, finance, business, as well as entertainment. GAMES Aims at developing a set of methodologies, software tools and services, and innovative metrics for the energy efficiency design and management of the next generation data centers, which will be expected to operate in a cloud-oriented computing paradigm.

  6. Two h/w threads busy with IO Rest of the threads idle Original Program Optimizer Tool (GCC/XLC/FDPR) Invocations Optimized Programs Runtime Measurement (time/benchmark/embed) Application Adapter (SPEC/script/app/embed) Fitness Values Convergence satisfied ? C, C++, F Search Algorithm: Genetic algorithm WCode Driver Managed Runtime Static Compiler fat executable: ppc binary + wcode wcode No TR Option Sets Dynamic Compiler (TR) Workload Requirements Capacity Planning System Configuration native execution Done Configuration Constraints System Optimization Activities • Provide significant performance improvement for IBM platforms and benchmarks. • Help in determination of performance degradation. • Help in system configuration planning. • Performance tools • Trace Analyzer: Visualization and analysis • Static and dynamic code optimization • Workload optimization with post link binary optimization – FDPR • Accelerate applications written in static languages using static compilation and feedback directed dynamic re-compilation Instrumentation Profile Collection • ESTO - Expert System for Tuning Optimization Customer’sBinary Profile Instrumented Binary 1 2 Optimization 3 Optimized Binary • Capacity planning: Workload optimization

  7. Dynamic Optimization for Cloud and Virtual Environments • Virtual environments feature additional software layers that abstract physical resources • Clouds include additional management layers and provide services by efficiently mapping virtual machines to physical • Clouds today suffer from low CPU utilization and high energy related costs. • Density is key, and is achieved using consolidation and migration • Memory, Networking, I/O bottlenecks becoming more critical Additional software layers abstract information from the optimizer “Service Aware Metric for Energy Efficiency in Green Data Centers (Green IT)”, Satoshi Sekiguchi, Satoshi Itoh (AIST) et al. Can a dynamic, application aware, optimizer assist in better resource utilization in cloud and virtual environments? “Service Aware Metric for Energy Efficiency in Green Data Centers (Green IT)”, Satoshi Sekiguchi, Satoshi Itoh (AIST) et al.

  8. R A E IBM and HiPEAC • IBM has invested heavily in high-performance platforms • IBM has offerings in HPC (RoadRunner, BlueGene, DeepBlue, PureSystems, zOS) • IBM is getting into technical computing • IBMis participating in many European projects, leading major Cloud R&D projects,and involved in study groups and consulting to the European Commission. • Looking forward for R&D collaborations with European partners • Talk to me!

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