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Employing Task Parallelism to Facilitate Dynamic Comparison of Model Output Ha nna h Aize nma n (CUNY Gra d ua te Ce nte r, NOAA-CRE ST a t CCNY) Me nto rs: Da ve Bro wn, Ma ry Ha le y (NCAR-CISL / VE T S) Co ntrib uto rs: She ri Mic


  1. Employing Task Parallelism to Facilitate Dynamic Comparison of Model Output Ha nna h Aize nma n (CUNY Gra d ua te Ce nte r, NOAA-CRE ST a t CCNY) Me nto rs: Da ve Bro wn, Ma ry Ha le y (NCAR-CISL / VE T S) Co ntrib uto rs: She ri Mic ke lso n (ANL ), Susa n Ba te s, Go kha n Da na b a so g lu (NCAR-CGD)

  2. OMWG POP Diagnostics

  3. Swift POP Diagnostics Pa ra lle lize s e xe c utio n o f NCL sc ripts • 3X spe e d up o ve r No n-Swift ve rsio n •

  4. Only supported on DASG machines

  5. Even on DASG…

  6. NCAR’s mission is “to support, enhance, and extend the capabilities of the university community and the broader scientific community, nationally and internationally” - http://ncar.ucar.edu/about-ncar

  7. Service Oriented Architecture

  8. Why SOA? Se rvic e s sta y inde pe nde nt • Dia g no stic s c a n b e a dde d inde pe nde nt o f o the r se rvic e s o Ne w se rvic e s c a n use o ld o ne s witho ut c ha ng ing the o lds o ne s o Multiple c lie nts c a n ta lk to the sa me se rve r • CL I , mo b ile , de skto p, … o Ca n ke e p o ld UI up while ro lling o ut ne w o ne o Clie nts a nd se rvic e s do no t ne e d to b e o n the sa me • ma c hine Slo w se rvic e s (the dia g no stic s) do no t inte rfe re with • fa st o ne s (da ta , o b se rva tio ns)

  9. RESTful SOA

  10. Start a run

  11. Get the results

  12. URL->File

  13. Why pydiag?

  14. Automate running the diagnostics T urn use r de fine d se tting s into inputs • c a se / run, o b se rva tio ns, ye a rs, a nd plo ts o I nputs a re pytho n dic tio na rie s o Ge ne ra te Swift c o nfig ura tio n file s • site s.xml c ha ng e s with e ve ry ne w o utput dire c to ry o site s.xml a nd tc .da ta a re ma c hine de pe nde nt o Co nfig s a re dic tio na rie s a nd lists o f dic ts o F ile s g e ne ra te xml, tsv, c dm, a nd c o nfig ura tio n • I so la te de pe nde nc ie s • T urn it into a n impo rta b le lib ra ry •

  15. CSH->Python

  16. Deployment Re q uire s a ny lib ra rie s use d b y the dia g no stic s • Se lf-c o nta ine d e nviro nme nt • I so la te d thro ug h use o f virtua le nv o All the pa c ka g e s a re in PyPi o Only o the r de pe nde nc ie s o lib e ve nt a nd a c c e ss to the da ta se rve rs (g la de , hpss) • Wo rks b e tte r o n c luste r o Ma inte na nc e a nd e xte nsib ility: • Mo dula r a rc hite c ture o Unit, inte g ra tio n, a nd func tio na l re g re ssio n te sts o Do c ume nta tio n c a n b e c o mpile d into we b pa g e s, b o o ks, e tc o pydia g , whic h is sta nd-a lo ne , is c o mpa tib le with • Pytho n2.4 thro ug h Pytho n2.7

  17. Server Side mik.ucar.edu Use any of the documented/sample urls

  18. Client Side

  19. Acknowledgments Da ve Bro wn a nd Ma ry Ha ly (NCAR/ CI SL ) • She ri Mic ke lso n (ANL ) • Susa n Ba te s a nd Go kha n Da na b a so g lu • (NCAR/ CGD) Pa ul Go o dma n a nd Na tha n Wilhe lmi (NCAR-CI SL ) • We i Hua ng a nd Ric k Bro wnrig g (NCAR/ CI SL ) •

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