1 030320 abk Panel: PED/Reliability Roadmapping Issues u Question #1: More “issue-spotting” than questions s Runtime leakage vs. dynamic power s Impact.

Slides:

Advertisements

Similar presentations

System-level Architectur Modeling for Power Aware Computing Dexin Li.

Advertisements

Use of Kalman filters in time and frequency analysis John Davis 1st May 2011.

GoldSim 2006 User Conference Slide 1 Vancouver, B.C. The Submodel Element.

EvoNet Flying Circus Introduction to Evolutionary Computation Brought to you by (insert your name) The EvoNet Training Committee The EvoNet Flying Circus.

DARPA Assessing Parameter and Model Sensitivities of Cycle-Time Predictions Using GTX u Abstract The GTX (GSRC Technology Extrapolation) system serves.

Building and Testing a Theory Steps Decide on what it is you want to explain or predict. 2. Identify the variables that you believe are important.

1 Part 3 Truncation Errors (Supplement). 2 Error Propagation How errors in numbers can propagate through mathematical functions? That is, what's the effect.

Why Do Stochastic Simulations? Empirical evaluation of statistical tests or methods –Want to know how well t-test performs when have unequal variances.

OCIN Workshop Wrapup Bill Dally. Thanks To Funding –NSF - Timothy Pinkston, Federica Darema, Mike Foster –UC Discovery Program Organization –Jane Klickman,

VADE - Virtual Assembly Design Environment Virtual Reality & Computer Integrated Manufacturing Lab.

University of Michigan Advanced Computer Architecture Lab. March 21, Key PED Challenges David Blaauw University of Michigan

CAD and Design Tools for On- Chip Networks Luca Benini, Mark Hummel, Olav Lysne, Li-Shiuan Peh, Li Shang, Mithuna Thottethodi,

On-Line Adjustable Buffering for Runtime Power Reduction Andrew B. Kahng Ψ Sherief Reda † Puneet Sharma Ψ Ψ University of California, San Diego † Brown.

PED Roadmapping Issues Vijaykrishnan Narayanan Dept. of CSE Penn State University GSRC Workshop, March 20-21, 2003.

 Y. Hu, V. Shih, R. Majumdar and L. He, “Exploiting Symmetries to Speedup SAT-based Boolean Matching for Logic Synthesis of FPGAs”, TCAD  Y. Hu,

Parameters System attributes or variables Example of ASCII parameter grammar #parameter dl_chip #parameter dl_chip #type double #type double #units {m}

ITRS-2001 Design ITWG Plan December 6, 2000 Bill Joyner, SRC/IBM.

NOCS-2009 Chita R. Das National Science Foundation/ Pennsylvania State University.

Research Directions for On-chip Network Microarchitectures Luca Carloni, Steve Keckler, Robert Mullins, Vijay Narayanan, Steve Reinhardt, Michael Taylor.

5 Top PED/Robustness Roadmapping Needs 1.Power and energy reduction achievable with less intrusive and more evolutionary techniques  Ex: dual-Vdd incurs.

Classification and Prediction: Regression Analysis

Design and Analysis of Engineering Experiments

Methodology for Architectural Level Reliability Risk Analysis Lalitha Krothapalli CSC 532.

Ness Shroff Dept. of ECE and CSE The Ohio State University Grand Challenges in Methodologies for Complex Networks.

DSS Modeling Current trends – Multidimensional analysis (modeling) A modeling method that involves data analysis in several dimensions – Influence diagram.

Testing : A Roadmap Mary Jean Harrold Georgia Institute of Technology Presented by : Navpreet Bawa.

1 Design and Analysis of Engineering Experiments Chapter 1: Introduction.

Presented By : LAHSAINI Achraf & MAKARA Felipe.  Introduction  Difficult Challenges : > Difficult Challenges between 2013 – 2020 > Difficult Challenges.

Recommendations for upcoming 1800 PAR SV-DC. Introduction user-defined nettypes (UDNs) & interconnect were added in P The features were intentionally.

Budget-based Control for Interactive Services with Partial Execution 1 Yuxiong He, Zihao Ye, Qiang Fu, Sameh Elnikety Microsoft Research.

Socio-economic scenarios Anand Patwardhan IIT-Bombay.

DARPA GTX: The MARCO GSRC Technology Extrapolation System Abstract Technology extrapolation -- i.e., the calibration and prediction of achievable Technology.

Statistics and the Verification Validation & Testing of Adaptive Systems Roman D. Fresnedo M&CT, Phantom Works The Boeing Company.

Leakage reduction techniques Three major leakage current components 1. Gate leakage ; ~ Vdd 4 2. Subthreshold ; ~ Vdd 3 3. P/N junction.

OPERATING SYSTEMS CS 3530 Summer 2014 Systems and Models Chapter 03.

Copyright © 2010 Houman Homayoun Houman Homayoun National Science Foundation Computing Innovation Fellow Department of Computer Science University of California.

ZEIT4700 – S1, 2015 Mathematical Modeling and Optimization School of Engineering and Information Technology.

Conference on Quality in Space & Defense Industries CQSDI ‘08 Probabilistic Technology Panel: What Is Probabilistic Technology? Mohammad Khalessi, Ph.D.

In-Place Decomposition for Robustness in FPGA Ju-Yueh Lee, Zhe Feng, and Lei He Electrical Engineering Dept., UCLA Presented by Ju-Yueh Lee Address comments.

IPR: In-Place Reconfiguration for FPGA Fault Tolerance Zhe Feng 1, Yu Hu 1, Lei He 1 and Rupak Majumdar 2 1 Electrical Engineering Department 2 Computer.

Computational Sensing = Modeling + Optimization CENS seminar Jan 28, 2005 Miodrag Potkonjak Key Contributors: Bradley Bennet, Alberto.

Environmental Remote Sensing GEOG 2021 Lecture 6 Mathematical Modelling in Geography I.

3.4 Slope and Rate of Change Math, Statistics & Physics 1.

-1- UC San Diego / VLSI CAD Laboratory Optimal Reliability-Constrained Overdrive Frequency Selection in Multicore Systems Andrew B. Kahng and Siddhartha.

// Research needs in statistical modelling for energy system planning Chris Dent Amy Wilson / Meng Xu / Antony Lawson / Edward Williams Stan Zachary /

BlinkDB: Queries with Bounded Errors and Bounded Response Times on Very Large Data Authored by Sameer Agarwal, et. al. Presented by Atul Sandur.

Why is Design so Difficult? Analysis: Focuses on the application domain Design: Focuses on the solution domain –The solution domain is changing very rapidly.

Fault-Tolerant Resynthesis for Dual-Output LUTs Roy Lee 1, Yu Hu 1, Rupak Majumdar 2, Lei He 1 and Minming Li 3 1 Electrical Engineering Dept., UCLA 2.

GRASS: Trimming Stragglers in Approximation Analytics

OPERATING SYSTEMS CS 3502 Fall 2017

Problem and Motivation

Enabling Team Supervisory Control for Teams of Unmanned Vehicles

Prabhat Kumar Saraswat Paul Pop Jan Madsen

Alireza Shafaei, Shuang Chen, Yanzhi Wang, and Massoud Pedram

4 Core Modules to be delivered on themes of:

Challenges in Nanoelectronics: Process Variability

Optimization Techniques for Natural Resources SEFS 540 / ESRM 490 B

Scenario Scoping Process

إستراتيجيات ونماذج التقويم

Mohammad Khalessi, Ph.D. CEO/President PredictionProbe, Inc.

Artificial Intelligence in Manufacturing

InCheck: An In-application Recovery Scheme for Soft Errors

Scenario Scoping Process

The Fuel Cycle Analysis Toolbox

Parsing Unrestricted Text

Methodology for Architectural Level Reliability Risk Analysis

Statistical Thinking and Applications

MECH 3550 : Simulation & Visualization

Applications of GTX Y. Cao, X. Huang, A.B. Kahng, F. Koushanfar, H. Lu, S. Muddu, D. Stroobandt and D. Sylvester Abstract The GTX (GSRC Technology Extrapolation)

Presentation transcript:

abk Panel: PED/Reliability Roadmapping Issues u Question #1: More “issue-spotting” than questions s Runtime leakage vs. dynamic power s Impact of variability (on leakage) s Subcritical operation s Low-power design vs. parametric yield and reliability s Win from multi-Vt, multi-Vdd (either/both, w/sizing) s Power-reliability interactions t Supplies vs. workload, substrate coupling, interconnect reliability/power s Area and power overheads of robustness s Soft errors (e.g., leakage vs. Qcrit vs. functional error rate in SRAM)

abk Panel: PED/Reliability Roadmapping Issues u Question #2: s Foundations / basic understanding t Quality data and inputs t What does the world need? u (Driver and System requirements, …) u Objectives: Reliability, Availability, Robustness t What are new technologies? (high-k, …) u  changes slopes… t Cost constraints and realities t Statistics, stochastic modeling t Faults and malfunctions, i.e., when do we have a problem s Lots of implied heuristic optimizers t How to take advantage of techniques being proposed t Calibration and empirical evaluation vs. analytic modeling s Drive underlying process technology requirements, not the other way around!

abk Panel: PED/Reliability Roadmapping Issues u Question #3: What models from PED and Reliability should be added into the ITRS / “Living Roadmap” ? u Question #4: What are open questions for potential collaboration with Roadmapping / technology extrapolation?