Low-Latency Datacenters

John Ousterhout

The Datacenter Revolution

●  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

●  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

Phase 1: Scale Phase 2: Low Latency

Network Latency (Round Trip)

April 12, 2016 Low-Latency Datacenters Slide 3

Component 2010 Possible Today

5-10 Years

Switching fabric 100-300 µs 5 µs 0.2 µs

Software 50 µs 2 µs 1 µs

NICs 8-128 µs 3 µs 0.2 µs

Propagation delay 1 µs 1 µs 1 µs

Total 200-400 µs 11 µs 2.4 µs

(Within a datacenter, 100K servers)

Storage Latency

April 12, 2016 Low-Latency Datacenters Slide 4

Disk 5–10 ms

Flash 50–500 µs Nonvolatile memory (e.g. 3D XPoint) 1–10 µs

April 12, 2016 Low-Latency Datacenters Slide 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 6

Reducing Software Stack Latency

High Latency

1. Optimize layers (specialize?)

2. Eliminate layers

3. Bypass layers

April 12, 2016 Low-Latency Datacenters Slide 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: 1000-10000 servers

●  Durability/availability equivalent to replicated disk

●  1000x improvements in: §  Performance §  Energy/op (relative to disk-based storage)

Master

Backup

Master

Backup

Master

Backup

Master

Backup …

Appl.

Library

Appl.

Library

Appl.

Library

Appl.

Library …

Datacenter Network Coordinator

1000 – 100,000 Application Servers

1000 – 10,000 Storage Servers

April 12, 2016 Low-Latency Datacenters Slide 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

●  Arachne project: core-aware thread scheduling §  Partial design, implementation beginning §  Initial performance result: 9ns context switches!

Application

Operating System

Thread Scheduling

April 12, 2016 Low-Latency Datacenters Slide 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

...

Top-of-rack switches

Servers

Datacenter Network

Congestion at edges (host-TOR links)

April 12, 2016 Low-Latency Datacenters Slide 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 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?

February 24, 2016 Platform Lab Introduction Slide 12

New Platform Lab

Platforms

Large Systems Collaboration

Create the next generation of platforms to stimulate new classes of applications

February 24, 2016 Platform Lab Introduction Slide 13

Platform Lab Faculty

John Ousterhout Faculty Director

Mendel Rosenblum Keith Winstein Guru Parulkar Executive Director

Bill Dally Phil Levis Sachin Katti Christos Kozyrakis

Nick McKeown

February 24, 2016 Platform Lab Introduction Slide 14

Theme: Swarm Collaboration Infrastructure

Wired/Wireless Networks

Next-Generation Datacenter Clusters

(Cloud/Edge) Device Swarms

February 24, 2016 Platform Lab Introduction Slide 15

Platform Lab Affiliates

Questions/Comments?

April 12, 2016 Low-Latency Datacenters Slide 16

April 12, 2016 Low-Latency Datacenters Slide 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

Large-Scale Collaboration

April 12, 2016 Low-Latency Datacenters Slide 18

Data for one user

Gmail: email for one user

Facebook: 50-500 friends

Morning commute: 10,000-100,000 cars

“Region of Consciousness”