Muhammad Shahbaz Tushar Swamy Alex Rucker Neeraja Yadwadkar Yaqi Zhang and Kunle Olukotun Taurus An Intelligent Data Plane Programmable Data Plane fused with Machine Intelligence ID: 814923
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Slide1
Taurus: An Intelligent Data Plane
Muhammad ShahbazTushar Swamy, Alex Rucker, Neeraja Yadwadkar, Yaqi Zhang, and Kunle Olukotun
Slide2Taurus: An Intelligent Data Plane
Programmable Data Planefused withMachine Intelligence
Deep Learning
Slide3Managing Networks is Hard!
Cloud Computing
Internet of Things (IoT)
Augmented and Virtual
Reality (AR/VR)
Slide4Approaches to Manage Networks are …
Data Plane
Switch or NIC
Fast
yet
dumb
Slow
but
intelligent
Control Plane
Intelligence
Slide5Approaches to Manage Networks are …
Data Plane
Switch or NIC
Fast
yet
dumb
Examples:
Congestion control
Load balancing (ECMP, RSS)
Queue scheduling
and more
Characteristics:
Operates on packets or
flowlets
(
i.e.,
bursts of packets)
Uses heuristics … hash, etc.
Low latency … ≤ sub µs
High throughput …
Tbps
Packets In
Packets Out
Slide6Approaches to Manage Networks are …
Data Plane
Switch or NIC
Fast
yet
dumb
Slow
but
intelligent
Control Plane
Intelligence
Slide7Approaches to Manage Networks are …
Data Plane
Switch or NIC
Slow
but
intelligent
Control Plane
Intelligence
Examples:
Anomaly detection
Automation
Recommendation
Characteristics:
Operates on flows
Performs complicated tasks
Sub-second latency
Low throughput
Packets In
Packets Out
Packet
Digest
Flow
Rule
Slide8Approaches to Manage Networks are …
Data PlaneSwitch or NICFast yet dumb
Slow but intelligent
Control Plane
Intelligence
Slide9Approaches to Manage Networks are …
Data PlaneSwitch or NICFast yet dumb
Slow but intelligent
Control Plane
Intelligence
Slide10Approaches to Manage Networks are …
Data Plane Switch or NICFast and
Control Plane
Intelligence
Intelligence
intelligent
intelligent
Slide11Data Plane
Switch or NICTaurus: An Intelligent Data PlaneIntelligence
Packets In
Packets Out
Slide12Taurus: An Intelligent Data Plane
Packet
Parser
Match-Action
Tables
Map Reduce
Unit
Match-Action
Tables
Traffic
Manager
Packets In
Packets Out
Slide13Traffic
ManagerMatch-ActionTablesMap ReduceUnitMatch-ActionTables
Taurus: An Intelligent Data Plane
Packets In
Packets Out
Packet
Parser
Implements a
finite state machine (FSM)
that operates on a user-defined
parse graph
Converts the
incoming packet bit stream into vectors
,
e.g.
,
headers (IP or TCP)
features (switch, host, or other encoded state)
Slide14Traffic
ManagerTaurus: An Intelligent Data Plane
Packet
Parser
Map Reduce
Unit
Packets In
Packets Out
Match-Action
Tables
Match-Action
Tables
Memory
ALU
A
match-action table:
Memory for
exact
(SRAM) and
ternary
(TCAM) match
ALU for basic single-cycle
VLIW operations
(no loops or multiplication)
Performs pre- and post-processing, and switching tasks:
Pre-processing
,
e.g.
, data transformation, acquisition, and repair
Post-processing
,
e.g.
, drop, route, or encode output of the learned model on a packet
Slide15Traffic
ManagerTaurus: An Intelligent Data Plane
Packet
Parser
Match-Action
Tables
Match-Action
Tables
Packets In
Packets Out
Map Reduce
Unit
Implements a
spatial SIMD architecture
, composed of
compute
and
memory
units
Compute consists of
pipelined
stages of
functional units
(FUs) and
pipeline registers
(PRs), running in
parallel
as lanes
Processes parallel
map-reduce operations
to accelerate
linear algebra
, crucial for
machine learning (ML)
, or other network functions
Slide16Taurus: An Intelligent Data Plane
Packet
Parser
Match-Action
Tables
Map Reduce
Unit
Match-Action
Tables
Packets In
Packets Out
Traffic
Manager
Responsible for
storing
and
forwarding
packets off of the chip:
Queuing
: buffer incoming packet
Replication
: clone packets across multiple egress ports (
e.g.
, multicast)
Scheduling
: forward packets based on a queuing discipline (
e.g.
, PIFO) or instructions from the match-action tables
Slide17Taurus: An Intelligent Data Plane
Packet
Parser
Match-Action
Tables
Map Reduce
Unit
Match-Action
Tables
Packets In
Packets Out
Traffic
Manager
Slide18Example: Anomaly Detection
Packet
Parser
Match-Action
Tables
Map Reduce
Unit
Match-Action
Tables
Packets In
Packets Out
Parse incoming
packets
and
read local features
like an IP address
Retrieve
out of
network events
like no. of failed
logins for a
connection
Process features
using a learned
function
and output probability
of an anomalous packet
Parsing
Pre-processing
using tables
Machine
learning
Select a port
based on the
probability
of an anomalous packet
Post-processing
using tables
Send packets
out over the
selected port
Scheduling
Traffic
Manager
Slide19Evaluation
[4] Design principles for packet parsers, ACM/IEEE ANCS’13[5] CONGA: distributed congestion-aware load balancing for datacenters, ACM SIGCOMM’14[6] Packet Transactions: High-Level Programming for Line-Rate Switches, ACM SIGCOMM’16
10
6
x
Within
2 – 15%
[5,6]
Slide20Future Work
Packet
Parser
Match-Action
Tables
Map Reduce
Unit
Match-Action
Tables
Packets In
Packets Out
Traffic
Manager
Spatial
Parse
Graph
MAT
MAT
PIFO
Ad-hoc Low-Level DSLs
A Unified High-Level Abstraction
?
Slide21Conclusion
Designed to run machine-learning inference inside a data planeProvides orders of magnitude improvement over existing approaches
Data Plane
Switch or NIC
Fast
and
Intelligence
intelligent
Taurus
Slide22Muhammad Shahbaz
http://cs.stanford.edu/~mshahbaz Questions?