1 / 9

Zhanpeng Jin Allen C. Cheng zhj6@pitt acc33@pitt

Engineering Next-generation Self-healing And Self-optimizing Neural Network Based Medical Platforms. Zhanpeng Jin Allen C. Cheng zhj6@pitt.edu acc33@pitt.edu. ASPLOS 2010, The Wild and Crazy Session VIII. Artificial Neural Network.

lot
Download Presentation

Zhanpeng Jin Allen C. Cheng zhj6@pitt acc33@pitt

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Engineering Next-generation Self-healing And Self-optimizing Neural Network Based Medical Platforms Zhanpeng Jin Allen C. Cheng zhj6@pitt.eduacc33@pitt.edu ASPLOS 2010, The Wild and Crazy Session VIII

  2. Artificial Neural Network (Source: "Anatomy and Physiology" by the US National Cancer Institute's Surveillance, Epidemiology and End Results (SEER) Program.) (Source: CapitalISM BI)

  3. Emerging Neural Hardware Neural chip (384 neurons + 100,000 synapses) @ FACET Project Microchip of a neural network @ RIEC, Tohoku University The China-Brain Project (10,000 – 15,000 neural nets) @ Hugo de Garis 3-D neural chip for better visualization @ CalTech

  4. Bio-inspired Autonomously Reconfigurable Mechanism Autonomous Reconfigurability Topology Adaptation Redundancy (Picture Source: “Brain Injury: Recovery” in Psychology Wiki)

  5. Autonomously Reconfigurable ANN µController Run-Time Reconfiguration Controller Flash Memory Coarse-grained Reconfiguration Bitstream Database Error Scale and Location Mask-Based Topology Adaption New topology Error Detection Request Coarse-/Fine-Grained Hybrid Reconfiguration Request Current ANN Configuration Fine-grained Reconfiguration Bitstream Coarse-grained Reconfiguration Bitstream Data Traffic Select/Merge Bitstreams New Configuration Inputs Sensors/ Database Autonomously Reconfigurable ANN (ARANN) Based Medical Processing Platforms Outputs Diagnosis/ Controllers

  6. Virtual-physical Neuron Mapping Neural Topology Physical Neurons Virtual-to-Physical (V2P) Neuron Mapping Connectionism Evolvement (Fine-grained) = Topology Adaptation (Coarse-grained) + Autonomous ANN

  7. Mask-based Topology Adaptation

  8. WACI Conclusion • Systems are increasingly vulnerable to unexpected faults and defects, especially for emerging biomedical systems. • Non-invasive autonomous reconfigurability is promising, particularly for ANN-based biomedical platforms. • Autonomously adapting ANN’s behaviors and structures, both algorithmically and microarchitecturally. • Neuron Virtualizationhelps to decouple the fault scale and reduce the reconfiguration latency (idle time). • Mask-based Topology Adaptation can achieve significant reduction of design complexity and spatial overhead.

  9. Thanks for Listening Questions? (This work is supported by NSF No. 0832990)

More Related