Scaling Example  Workload: sum of 10 scalars, and 10 × 10 matrix sum    Single processor: Time = (10 + 100) × tadd 10 processors    Time = 10 × tadd + 100/10 × tadd = 20 × tadd Speedup = 110/20 = 5.5 (55% of potential) 100 processors    Speed up from 10 to 100 processors Time = 10 × tadd + 100/100 × tadd = 11 × tadd Speedup = 110/11 = 10 (10% of potential) Assumes load can be balanced across processors Chapter 6 — Parallel Processors from Client to Cloud — 7
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Scaling Example (cont)      What if matrix size is 100 × 100? Single processor: Time = (10 + 10000) × tadd 10 processors  Time = 10 × tadd + 10000/10 × tadd = 1010 × tadd  Speedup = 10010/1010 = 9.9 (99% of potential) 100 processors  Time = 10 × tadd + 10000/100 × tadd = 110 × tadd  Speedup = 10010/110 = 91 (91% of potential) Assuming load balanced Chapter 6 — Parallel Processors from Client to Cloud — 8
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D A T A B A S E ORDER BY SELECT FROM JOIN WHERE ORDER BY Animal AnimalID Name Category Breed DateBorn Gender columns tables join columns conditions columns (ASC DESC) SELECT Name, Category, Breed FROM Animal ORDER BY Category, Breed; Field Name Category Breed Table Animal Animal Animal Ascending Ascending Sort Criteria Or Name Cathy Category Bird Bird Debbie Bird Bird Terry Bird Bird Charles Bird Curtis Bird Ruby Bird Sandy Bird Hoyt Bird Bird Breed African Grey Canary Cockatiel Cockatiel Lovebird Other Parakeet Parakeet Parakeet Parrot Parrot Parrot 9
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National Publicity for iCons •• C C& & EE News News (July (July 4, 4, 2011) 2011) •• Featuring Featuring iCons iCons Program Program Launch Launch •• Assoc Assoc of of American American Colleges Colleges & & Universities Universities (Feb (Feb 5, 5, 2014) 2014) •• Featuring Featuring iCons iCons Program Program Structure Structure & & Pedagogy Pedagogy •• Boston Boston Business Business Journal Journal (May (May 14, 14, 2014) 2014) •• Featuring Featuring Collaboration Collaboration with with Waters Waters • • C C& & EE News News (May (May 26, 26, 2014) 2014) Corp. Corp. •• Featuring Featuring Benefits Benefits for for Pharma Pharma www.cns.umass.edu/icons-program
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Theme/Theme Rhonda kissed Jason. Who else was kissed by Rhonda? JEREMY was kissed by Rhonda, too. Agent/Theme Evelyn kissed Jeremy. Who else was Jeremy kissed by? JEREMY was kissed by Rhonda, too. Agent/Agent Evelyn kissed Jeremy. Who else was Jeremy kissed by? Jeremy was kissed by RHONDA, too. Theme/Agent Rhonda kissed Jason. Who else was kissed by Rhonda? Jeremy was kissed by RHONDA, too. FocusedAppropriate material is underlined , pitch accented material is in BOLD CAPS, inappropriate (agent/agent) responses are in red, and appropriate responses are in blue. Inappropriate (agent/theme)
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Strong vs Weak Scaling  Strong scaling: problem size fixed   As in example Weak scaling: problem size proportional to number of processors  10 processors, 10 × 10 matrix   100 processors, 32 × 32 matrix   Time = 20 × tadd Time = 10 × tadd + 1000/100 × tadd = 20 × tadd Constant performance in this example Chapter 6 — Parallel Processors from Client to Cloud — 9
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Review of Radars at Supersite HUMIDITY DUAL WAVELENGTH MM-WAVELENGTH •SPolKa (NCAR) S & •ARM mm radar Doppler Air motions •ARM Ka band Ka band •SMART-R C-band •SpolKa Ka band •SPolKa •ARM X & Ka •NOAA S-band? CM-WAVELENGTH Precipitation •SMART-R C-band •SPolKa S-band •ARM/AMIE X-band •NOAA S-band? •NOAA Distrometer? MM-WAVELENGTH Polarimetric Microphysics •SPolKa •ARM X band •ARM mm radar •ARM Ka band •SPolKa Ka band
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