The Morning Paper: foundations & frontiers

Talk from Craft-Conf 2017

1. The Morning Paper: foundations and frontiers Adrian Colyer @adriancolyer
2. blog.acolyer.org 550 Foundations Frontiers
3. Brain storm 01 02 05 04 rainstorm 03 5 Reasons to <3 Papers Thinking tools Raise Expectations Applied Lessons Order of magnitude breakthroughs Heads-up 3
4. 4 01 02 03 04 05 Software development Distributed Systems & Big Data Infrastructure implications Security ML & DL
5. Software Development 5
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20. Distributed Systems and Big Data 20
21. Frank McSherry Scalability - but at what COST? 21
23. But you have BIG Data! 23 Zipf Distribution ³:RUNLQJVHWVDUH =LSIGLVWULEXWHG:HFDQ WKHUHIRUHVWRUHLQPHPRU\DOO EXWWKHYHU\ODUJHVW GDWDVHWV´
24. Musketeer 24 One for all?
25. Approx Hadoop 25 32x!
26. HopFS - FAST’17 26
27. Redundancy does not imply fault tolerance - FAST’17 27 ŸRdZ_X]VWZ]VdjdeV^WRf]eTR_ Z_UfTVTReRdec`aYZT`feT`^VdZ_ ^`de^`UVc_UZdecZSfeVUde`cRXV djdeV^dUReR]`ddT`ccfaeZ`_ f_RgRZ]RSZ]ZejR_UZ_d`^V TRdVdeYVdacVRU`WT`ccfaeZ`_ e``eYVcZ_eRTecVa]ZTRdŹ
28. Infrastructure implications 28
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30. Computing on a Human Scale 30 10ns 70ns 10ms 10s 1:10s 116d 5HJLVWHUV // )LOHRQ GHVN 0DLQ PHPRU\ 2IILFHILOLQJ FDELQHW +'' 7ULSWRWKH ZDUHKRXVH
31. Compute HTM Persistent Memory NI FPGA GPUs Memory NVDIMMs Persistent Memory Networking 100GbE RDMA Storage NVMe Next-gen NVM Next Generation Hardware All Change Please 31
32. 2-10m Computing on a Human Scale 32 10s 1:10s 116d File on desk Office filing cabinet Trip to the warehouse 4x capacity fireproof local filing cabinets 23-40m Phone another office (RDMA) 3h20m Next-gen warehouse
33. The New ~Numbers Everyone Should Know 33 Latency Bandwidth Capacity/IOPS Register 0.25ns L1 cache 1ns L2 cache 3ns 8MB L3 cache 11ns 45MB DRAM 62ns 120GBs 6TB - 4 socket NVRAM’ DIMM 620ns 60GBs 24TB - 4 socket 1-sided RDMA in Data Center 1.4us 100GbE ~700K IOPS RPC in Data Center 2.4us 100GbE ~400K IOPS NVRAM’ NVMe 12us 6GBs 16TB/disk,~2M/600K NVRAM’ NVMf 90us 5GBs 16TB/disk, ~700/600K
34. No Compromises - FaRM 34 TPC-C (90 nodes) 4.5M tps 99%ile 1.9ms KV (per node) 6.3M qps at peak throughput 41μs
35. No Compromises 35 ³7KLVSDSHUGHPRQVWUDWHVWKDWQHZVRIWZDUHLQPRGHUQ GDWDFHQWHUVFDQHOLPLQDWHWKHQHHGWRFRPSURPLVH,W GHVFULEHVWKHWUDQVDFWLRQUHSOLFDWLRQDQGUHFRYHU\ SURWRFROVLQ)D50DPDLQPHPRU\GLVWULEXWHGFRPSXWLQJ SODWIRUP)D50SURYLGHVGLVWULEXWHG$&,'WUDQVDFWLRQV ZLWKVWULFWVHULDOL]DELOLW\KLJKDYDLODELOLW\KLJK WKURXJKSXWDQGORZODWHQF\7KHVHSURWRFROVZHUH GHVLJQHGIURPILUVWSULQFLSOHVWROHYHUDJHWZRKDUGZDUH WUHQGVDSSHDULQJLQGDWDFHQWHUVIDVWFRPPRGLW\ QHWZRUNVZLWK5'0$DQGDQLQH[SHQVLYHDSSURDFKWR SURYLGLQJQRQYRODWLOH'5$0´
36. DrTM The Doctor will see you now 36 5.5M tps on TPC-C 6-node cluster.
37. Security 37
38. Making smart contracts smarter CCS ‘16 38 19,366 contracts $30M USD 8,833 vulnerable 27.9% 15.7% 340 83  (UURU  H[FHSWLRQ KDQGOLQJ  7UDQVDFWLRQ RUGHULQJ 5HHQWUDQF\ KDQGOLQJ 7LPHVWDPS RUGHULQJ
39. OSDI ‘16 Scone: Secure Linux containers with Intel SGX 39
40. NDSS ‘17 Thou shalt not depend on me 40 37% vulnerable jQuery -> 36.7%, Angular -> 40.1%
41. ML & DL 41
42. lessons from Google Machine Learning Systems 42 Feature Management Visualisation Relative Metrics Systematic Bias Correction Alerts on action Thresholds 01 02 03 04 05
43. ICLR 2015 Explaining and harnessing adversarial examples 43
44. CVPR ‘15 Deep neural networks are easily fooled 44
45. Wrapping Up 45
46. Brain storm 01 02 05 04 rainstorm 03 5 Reasons to <3 Papers Thinking tools Raise Expectations Applied Lessons Order of magnitude breakthroughs Heads-up 46
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48. Don’t just take my word for it... 48 :U`_Ŷe\_`hY`heYVYf^R_ScRZ_ h`c\dSfeZeŶdR]^`de^RXZTR]hYV_ j`fcVRUV_`fXY`ceR]\e`V_`fXY ViaVcedhYV_j`fYRgVV_`fXYZ_afed _VhZUVRddeRceRaaVRcZ_X $QGUHZ1J ³,QVLGHWKHPLQGWKDWEXLOW*RRJOH%UDLQ´ KWWSZZZKXIILQJWRQSRVWFRPDXDQGUHZQJBQBKWPO
49. A new paper every weekday Published at http://blog.acolyer.org. 01 Delivered Straight to your inbox If you prefer email-based subscription to read at your leisure. 02 Announced on Twitter I’m @adriancolyer. 03 Go to a Papers We Love Meetup A repository of academic computer science papers and a community who loves reading them. 04 Share what you learn Anyone can take part in the great conversation. 05
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