Embedded High Performance Computing (EHPC) and Neuromorphic - - PowerPoint PPT Presentation

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Embedded High Performance Computing (EHPC) and Neuromorphic - - PowerPoint PPT Presentation

May 03, 2023 448 likes •584 views

Embedded High Performance Computing (EHPC) and Neuromorphic Computing November 18, 2014 Mr. Mark Barnell Senior Computer Scientist Information Directorate Integrity Service Excellence Air Force Research Laboratory 1 DISTRIBUTION A.

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DISTRIBUTION A. Approved for public release; distribution unlimited (88ABW-2013-3982, 09 Sep 2013)

Integrity  Service  Excellence

Embedded High Performance Computing (EHPC) and Neuromorphic Computing

November 18, 2014

  • Mr. Mark Barnell

Senior Computer Scientist Information Directorate Air Force Research Laboratory

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DISTRIBUTION A. Approved for public release; distribution unlimited (88ABW-2013-3982, 09 Sep 2013)

Outline

  • Challenges
  • Approaches

– Scalable computing & applications – Exploit 3D integration – New devices and models of computation – Move “C4ISR to the edge” with EHPC

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Challenges in Big Data Analytics

  • Big data limits human performance in analysis and decision

making

  • High-performance information technologies for massive analytics

enables the journey from big data to information, knowledge and wisdom.

  • R&D needed to achieve trusted autonomous systems that are capable
  • f learning, reasoning, inferencing and interacting with human.
  • Advantage in labor power could convert into global

competitive advantages

  • Ability to “do more, do better” with more intelligent power, less

labor power, would be a “force multiplier”

  • Computing hardware technologies reach physical limits in

area, power and performance

  • Three-dimensional integrated circuits and systems with optimized

performance under size, weight and power (SWaP) constraints.

  • RDT&E for nano/quantum/neuro device and system technologies.
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Multi-Tiered Approach to EHPC or HPEC Challenges

FUNDAMENTAL SCIENCE TRUSTED ARCHITECTURES

TECH DEVELOPMENT

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The Condor Cluster

1716 SONY Playstation3s

  • STI Cell Broadband Engine
  • PowerPC PPE
  • 6 SPEs
  • 256 MB RAM

84 head nodes

  • 6 gateway access points
  • 78 compute nodes
  • Intel Xeon X5650 dual-socket hexa-

core

  • (2) NVIDIA Tesla GPGPUs
  • 39 nodes – (78) C2050
  • 39 nodes – (78) C2070/5
  • 48 GB RAM

FY10 DHPI Key design considerations: Price/performance & Performance/Watt

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DISTRIBUTION A. Approved for Public Release [88ABW-2010-6225] Distribution Unlimited

Input: character images Character level: auto- associative neural networks

T e t x i m g a e

Word level: confabulation algorithms based on knowledge base of weighted links among letters Sentence level: confabulation algorithms based on knowledge base of weighted links among words and phrases Output: “Text image”

Hybrid Neuromorphic Model

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RADAR Data Processing for High Resolution Images

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  • R. U. D. I. Cluster

176 Jetson Boards (60T/flops @ 2.1kW)

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3D Integration

3D Integration

Hybrid Memory Cube (HMC Consortium) 3D NAND Flash Memory (Toshiba)

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Input Vectors Config. Output Buffer Training Complemted Training Signal Generation Error Detection ST & Arbiter

R/W Control

Crossbar Array M+

Diff Std Patterns X

(k), k=1...m

Vin

Crossbar Array M-

Summing Amplifier & Comparator V(t+1) V+(t) Vout V-(t) Crossbar-based Computation Core

Neuromorphic Computing Accelerator (NCA) ADC

00101101

Arbiter

NCA

I/O Cfg Buffers

Arbiter

NCA

I/O Cfg Buffers

Arbiter

NCA

I/O Cfg Buffers

Arbiter

NCA

I/O Cfg Buffers

Bridge

ADC

00101101

Bridge

ADC

00101101

General Purpose Processor SRAM I/O

Conventional Processing Neuromorphic Computing Accelerators

Crossbar array of memristors

Bio-Inspired Computing Architecture

Neuromorphic models and algorithms (ANN, Inference, etc.)

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Moving ISR to the Tactical Edge

Versatile Intelligent Sensor

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Summary

  • Future embedded systems are challenged to continue delivering

extreme performance in small space

  • But security places additional challenges for trust, agility and

resilience

  • Powerful technology drivers are still at hand to meet the

challenges

– Computer architecture innovations – Nano and quantum advances – 3D stacking – Algorithm development and mapping to architectures