Low-Latency Datacenters. John Ousterhout

Transcription

1 Low-Latency Datacenters John Ousterhout

2 The Datacenter Revolution Phase 1: Scale How to use 10,000 servers for a single application? New storage systems: Bigtable, HDFS,... New models of computation: MapReduce, Spark,... But, latencies high: Network round-trips: 0.5 ms Disk: 10 ms Interactive apps can t access much data Phase 2: Low Latency Latencies dropping dramatically Network round-trips: 500 µs 2.5 µs? Storage: 10 ms 1 µs? Potential: new applications (collaboration?) Challenge: need a new software stack April 12, 2016 Low-Latency Datacenters Slide 2

3 Network Latency (Round Trip) Component 2010 Possible Today 5-10 Years Switching fabric µs 5 µs 0.2 µs Software 50 µs 2 µs 1 µs NICs µs 3 µs 0.2 µs Propagation delay 1 µs 1 µs 1 µs Total µs 11 µs 2.4 µs (Within a datacenter, 100K servers) April 12, 2016 Low-Latency Datacenters Slide 3

4 Storage Latency Disk 5 10 ms Flash µs Nonvolatile memory (e.g. 3D XPoint) 1 10 µs April 12, 2016 Low-Latency Datacenters Slide 4

5 Low-Latency Software Stack Existing software stacks highly layered Great for software structuring Layer crossings add latency Slow networks and disks hide software latency Can t achieve low latency with today s stacks Death by a thousand cuts Networks: Complex OS protocol stacks Marshaling/serialization costs Storage systems: OS file system overheads Need significant changes to software stacks April 12, 2016 Low-Latency Datacenters Slide 5

6 Reducing Software Stack Latency 1. Optimize layers (specialize?) High Latency 2. Eliminate layers 3. Bypass layers April 12, 2016 Low-Latency Datacenters Slide 6

7 The RAMCloud Storage System New class of storage for low-latency datacenters: All data in DRAM at all times Low latency: 5-10µs remote access Large scale: servers ,000 Application Servers Appl. Appl. Appl. Library Library Library Appl. Library Durability/availability equivalent to replicated disk 1000x improvements in: Performance Energy/op (relative to disk-based storage) Master Backup Master Backup Datacenter Network Master Backup Master Backup ,000 Storage Servers Coordinator April 12, 2016 Low-Latency Datacenters Slide 7

8 Thread Scheduling Traditional kernel-based thread scheduling is breaking down: Context switches too expensive Applications don t know how many cores are available (Can t match workload concurrency to available cores) Kernel may preempt threads at inconvenient points Fine-grained thread scheduling must move to applications Kernel allocates cores to apps over longer timer intervals Kernel asks application to release cores Application Thread Scheduling Operating System Arachne project: core-aware thread scheduling Partial design, implementation beginning Initial performance result: 9ns context switches! April 12, 2016 Low-Latency Datacenters Slide 8

9 New Datacenter Transport TCP optimized for: Throughput, not latency Long-haul networks (high latency) Congestion throughout Modest # connections/server Future datacenters: High performance networking fabric: Low latency Multi-path Congestion primarily at edges Many connections/server (1M?) Need new transport protocol Servers Datacenter Network... Top-of-rack switches Congestion at edges (host-tor links) April 12, 2016 Low-Latency Datacenters Slide 9

10 Homa: New Transport Protocol Greatest obstacle to low latency: Congestion at receiver s link Large messages delay small ones Solution: drive congestion control from receiver Schedule incoming traffic Prioritize small messages Take advantage of priorities in network Implemented at user level Designed for kernel bypass, polling-based approach Status: Evaluating scheduling algorithms via simulation April 12, 2016 Low-Latency Datacenters Slide 10

11 Conclusion Interesting times for datacenter software Revisit fundamental system design decisions Exploring from several different angles Will the role of the OS change fundamentally? April 12, 2016 Low-Latency Datacenters Slide 11

12 New Platform Lab Create the next generation of platforms to stimulate new classes of applications Platforms Large Systems Collaboration February 24, 2016 Platform Lab Introduction Slide 12

13 Platform Lab Faculty Bill Dally Sachin Katti Christos Kozyrakis Phil Levis Nick McKeown John Ousterhout Faculty Director Guru Parulkar Executive Director Mendel Rosenblum Keith Winstein February 24, 2016 Platform Lab Introduction Slide 13

14 Theme: Swarm Collaboration Infrastructure Wired/Wireless Networks Next-Generation Datacenter Clusters (Cloud/Edge) Device Swarms February 24, 2016 Platform Lab Introduction Slide 14

15 Platform Lab Affiliates February 24, 2016 Platform Lab Introduction Slide 15

16 Questions/Comments? April 12, 2016 Low-Latency Datacenters Slide 16

17 Does Low Latency Matter? Potential: enable new data-intensive applications Application characteristics Collect many small pieces of data from different sources Irregular access patterns Need interactive/real-time response Candidate applications Large-scale graph algorithms (machine learning?) Collaboration at scale April 12, 2016 Low-Latency Datacenters Slide 17

18 Large-Scale Collaboration Region of Consciousness Gmail: for one user Facebook: friends Data for one user Morning commute: 10, ,000 cars April 12, 2016 Low-Latency Datacenters Slide 18