Unevenly Distributed. Adrian

Transcription

1 Unevenly Distributed Adrian

2 blog.acolyer.org 350 Foundations Frontiers

3 5 Reasons to <3 Papers 03 rainstorm Applied Lessons 02 Raise Expectations 04 The Great Conversation Thinking Brain toolsstorm 3 Uneven Distribution

4 Scalability - but at what COST? Frank McSherry 4

5 5

6 But you have BIG Data! Working sets are Zipfdistributed. We can therefore store in memory all but the very largest datasets. Zipf Distribution 6

7 Musketeer One for all? 7

8 Approx Hadoop 32x! 8

9 The Scalable Commutativity Rule Improve your API Design 9

10 Raising Your Expectations 10

11 TLS 54 CVEs Jan 14 - Jan 15! Error prone languages! Lack of Separation! Ambiguous and Untestable Spec Surely we can do better? 11

12 Do Less Testing! Microsoft Windows 8.1 Relative Improvement Test Executions 40.58% Test Time 40.31% $1,567,608 Test Result Inspection 33.04% $61,533 Escaped Defects 0.20% ($11,971) Total Cost Balance 12 Cost Improvement $1,617,170

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14 Lessons from the Field 14

15 A Masterclass in Config Mgt at Facebook 15

16 Machine Learning Systems lessons from Google 01 Feature Management 02 Visualisation 03 Relative Metrics 04 Systematic Bias Correction Alerts on action Thresholds 05 16

17 The Great Conversation And the Syntopicon 17

18 Cross-Fertilization Broad Exposure to Problems and their Solutions Security Distributed Systems Databases Robotics Machine Learning Programming Languages And Many More Operating Systems, Algorithms, Networking,Optimisation, SW Engineering,... 18

19 TPC-C

20 TPC-C Published Record Holder 20 Date Mar 26th 2013 Database Manager Oracle 11g r2 Enterprise Edition w. Partitioning Performance (tpmc) 8,552,523 (8.5M) Performance (tps) 142,542 (143K) System Cost $4,663,073 #Processors 8 #Cores 128 #Threads 1024

21 Coordination Avoidance and I-Confluence Analysis TPC-C 21

22 Multi-Partition Transactions at Scale 22

23 Unevenly Distributed Turning your world Upside Down

24 Human computers at Dryden by NACA (NASA) Dryden Flight Research Center Photo Collection gov/gallery/photo/places/html/e49-54.html. Licensed under Public Domain via Commons Human_computers_-_Dryden.jpg#/media/File: Human_computers_-_Dryden.jpg

25 Computing on a Human Scale 10ns Registers & L1-L3 1:10s Office filing cabinet 70ns Main memory 116d Trip to the warehouse 10ms 10s 25 File on desk HDD

26 All Change Please Next Generation Hardware Compute HTM Persistent Memory NI FPGA GPUs Memory NVDIMMs Persistent Memory 26 Networking 100GbE RDMA Storage NVMe Next-gen NVM

27 Computing on a Human Scale 10s File on desk 1:10s Office filing cabinet 116d Trip to the warehouse m 4x capacity fireproof local filing cabinets 23-40m Phone another office (RDMA) 3h20m Next-gen warehouse

28 The New ~Numbers Everyone Should Know Latency 28 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

29 Low Latency - RAMCloud 5 μs Reads 13.5μs Writes 20μs Transactions 27μs 5-object Txns 35K tps 29 TPC-C (10 nodes)

30 No Compromises - FaRM 4.5M tps 1.9ms 6.3M qps 41μs 30 TPC-C (90 nodes) 99%ile KV (per node) at peak throughput

31 No Compromises 31 This paper demonstrates that new software in modern data centers can eliminate the need to compromise. It describes the transaction, replication, and recovery protocols in FaRM, a main memory distributed computing platform. FaRM provides distributed ACID transactions with strict serializability, high availability, high throughput and low latency. These protocols were designed from first principles to leverage two hardware trends appearing in data centers: fast commodity networks with RDMA and an inexpensive approach to providing non-volatile DRAM.

32 The Doctor will see you now DrTM 5.5M tps on TPC-C 6-node cluster. 32

33 Some things Change, Some stay the Same 33

34 A Brave New World Fast RDMA networks + Ample Persistent Memory + Hardware Transactions + Enhanced HW Cache Management + Super-fast Storage + On-board FPGAs + GPUs + =??? 34

35 5 Reasons to <3 Papers 03 rainstorm Applied Lessons 02 Raise Expectations 04 The Great Conversation Thinking Brain toolsstorm 35 Uneven Distribution

36 01 02 A new paper every weekday 03 Announced on Twitter Published at Delivered Straight to your inbox If you prefer -based subscription to read at your leisure. I 04 Go to a Papers We Love Meetup 05 Share what you learn A repository of academic computer science papers and a community who loves reading them. Anyone can take part in the great conversation.

37 THANK