Transcript CCNI_Presentation-cont - Rensselaer Polytechnic Institute

Rensselaer
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Computational Center for
Nanotechnology Innovations
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A Computational and Research Center
dedicated to
Computational Nanotechnology Innovations
A University/Industry/State Partnership
Rensselaer Overview
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Rensselaer
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Educates the leaders of tomorrow for
technologically based careers
Schools – Architecture, Engineering,
Humanities and Social Sciences, Management
and Technology, Science
6,200 resident students – 5,000
undergraduate, 1,200 graduate
Private institution founded in 1824
450 faculty, 1400 staff
CCNI Vision - 1
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The Computational Center for Nanotechnology
Innovations (CCNI) will
bring together university and industry researchers
to
address the challenges facing the semiconductor
industry as devices shrink in size to the
nanometer range.
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CCNI Vision - 2
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To account for the interactions of atoms and
molecules up to the behavior of a complete
device, the CCNI must
develop a new generation of computational
methods to
support the virtual design of the next generation
of devices which will
require the massive computing
capabilities of the CCNI.
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CCNI Vision - 3
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The resulting virtual design methods will further
expand New York State’s leadership position in
nanotechnology.
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Industry Needs
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Needs
– Technical and cost constraints are limiting
the growth of the semiconductor industry
and nanotechnology innovations
– Computational nanotechnology is essential
for decreasing the time from concept
creation to commercialization
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CCNI Goals
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Goals
 Provide leadership in the development and
application of computational nanotechnologies
 Establish partnership to create world class
competencies on design-to-manufacturing
research capabilities
 Produce new integrated predictive design tools
for nano-scale materials, devices, and systems
 Spur economic growth in
the Capital district,
NYS & beyond
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Facilities and Capabilities
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Computational Systems
– 100 teraflops of computing
– Heterogeneous computing
environment
Rensselaer Technology Park
– 4300 sq. ft. Machine Room
– Business Offices
– Systems and Operations support
– Scientific Support
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Layout of CCNI
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Partners to Build CCNI
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Design and Engineering
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Partners to Build CCNI
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Architect
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Partners to Build CCNI
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Turner Construction Company
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CCNI Construction
Raised Floor
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CCNI Construction
Cooling Towers
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CCNI Construction
Lobby
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CCNI Installation
Blue Gene Racks and Inter-rack Cables
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CCNI Installation
Blue Gene Racks Without Covers
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CCNI Installation
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Blade Racks, Storage Racks, and Network Cables
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CCNI – Blue Gene/L
Blue Gene/L System
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16 rack IBM Blue Gene/L system
#7 on Top 500 Supercomputer List
32,768 PowerPC 700 MHz processors
12 TB of memory total
Compute Node Kernel
Simple, flat, fixed-size, address space
Single threaded, no paging
Familiar POSIX interface
Basic file I/O operations
– Two modes - coprocessor
or virtual mode
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Blue Gene/L Hardware
Optimized Communications
1) 3D Torus
2) Collective Network
3) Global Barrier/Interrupt
4) Gigabit Ethernet (I/O & connectivity)
5) Control (system boot, debug, monitoring)
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16 Racks
91.7 TF/s (peak)
12 TB
5.7 TF/s (peak)
512 GB or 1 TB
180 GF/s
16 or 32 GB
11.2 GF/s
2 GB
5.6 GF/s
4 MB
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Blue Gene Architecture
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CCNI – Blade Servers
Blade Server Cluster
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462 IBM LS21 blades
1,848 Opteron 2.6 GHz cores
5.5 TB of memory total
4X InfiniBand interconnect
(10 Gbps)
– Red Hat Linux
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CCNI – Large Memory
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AMD and Intel SMP Servers
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40 IBM x3755 servers
– Each with 8 Opteron 2.8 GHz cores and 64 GB of memory
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2 IBM x3755 servers
– Each with 8 Opteron 2.8 Ghz cores and 128 GB of memory
2 IBM x3950 servers
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– One with 64 Xeon 2.8 GHz cores and 128 GB of memory
– One with 32 Xeon 2.8 GHz cores and 256 GB of memory
All with 4X InfiniBand interconnect
 All with Red Hat Linux
Power SMP Server
– IBM p590
– 16 Power 5+ 2.1GHz processors
– 256 GB of memory
– AIX
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CCNI – Disk Storage
File Storage
– Common file system for all hardware
– IBM General Parallel File System,
GPFS
– 832 TB of raw disk storage
– 52 IBM x3655 file server nodes
– 26 IBM DS4200 storage controllers
GPFS
– High performance parallel I/O
– Cache consistent shared access
– Aggressive read ahead, write behind
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CCNI Networking
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State
International
Local fiber:
CCNI/Campus/NYSERNet
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CCNI – Research Areas
– Nanoelectronics modeling
and simulation
– Modeling of material structure
and behavior
– Modeling of complex flows
– Computational biology
– Biomechanical system modeling
– Multiscale methods
– Parallel simulation technologies
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Nanoelectronics Modeling and
Simulation
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– Functionality of new materials and devices
– Fabrication modeling
– Mechanics of nanoelectronic systems
– Application to the design of new devices
carbon nanotube
T-junctions (Nayak)
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submicron to nano (Huang)
Modeling of Material Structure and
Behavior
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– Modeling and design of material systems
– Modeling of energetic materials
– Multiscale modeling of nanostructured polymer rheology
Designed Interfaces
Controlled
Inhomogeneity
Macroscopic Layering
Matrix Compatible Block (MCB)
Property Enhancing Block (PEB)
Multiscale modeling
of polymer rheolgy
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Modeling of Complex Flows
– Hierarchic modeling of turbulent flows
– Modeling of biological systems flows
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Computational Biology
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– Protein structure and interactions with small molecules
– Membranes and membrane protein structure and function
– Modeling cellular processes and communities of cells
dppc
cholesterol
fentanyl
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Biomechanical System Modeling
– Virtual biological flow facility for
patient specific surgical planning
– Distributed digital surgery
– Biomedical imaging via inverse
problem construction
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Multiscale Science and Engineering
– Multiscale mathematics and
modeling
– Adaptive simulation systems
applied to applications
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Parallel Simulation Technologies
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– High-performance network models
– Optimistic parallel approaches
– Multi-level parallel network models
Geometric model
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Partition model
Initial mesh (1,595 tets)
Partitioned mesh
Adapted mesh (23,082,517 tets)
Thus Begins the CCNI Odyssey
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Questions
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