Latency war the present & the future

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Latency War - the Present & The Future
Gaurav Raizada
Quantinsti

It's the Latency, Stupid
Well known and referenced article
“a network link with low bandwidth can be made
better with money, but network link with bad latency
cannot be helped”
This was the scene in 1996, when bandwidth was the
constraint. Speeds were in Kbps.
Cheshire later become Wizard at Apple. Pioneering Zeroconf
http://rescomp.stanford.edu/~cheshire/rants/Latency.html

Misnomer – Bad Terminology
Would you say that a Boeing 747 is three times "faster" than a Boeing
737? Of course not. They both cruise at around 500 miles per hour.
The difference is that the 747 carries 500 passengers where as the
737 only carries 150. The Boeing 747 is three times bigger than the
Boeing 737, not faster.
Now, if you wanted to go from New York to London, the Boeing 747 is
not going to get you there three times faster. It will take just as long as
the 737.
In fact, if you were really in a hurry to get to London quickly, you'd
take Concorde, which cruises around 1350 miles per hour. It only
seats 100 passengers though, so it's actually the smallest of the three.
Size and speed are not the same thing.
On the other hand, If you had to transport 1500 people and you only
had one aeroplane to do it, the 747 could do it in three trips where
the 737 would take ten, so you might say the Boeing 747 can
transport large numbers of people three times faster than a Boeing
737, but you would never say that a Boeing 747 is three times faster
than a Boeing 737.

System Architecture of a Traditional Trading System
• Traditionally a trading system would consist of
– A system to read data from the market
– A storehouse of historical data
– A tool to analyse historical data
– A system where the trader can input his trading decisions
– A system to route orders to the exchange

• The server – which is mostly a data store
Workshop on Algorithmic & High Frequency Trading
Order Manager
Market Data
Operational Data Store
Exchange
Data
Warehouse
/
Storehouse
of
historical
data
Data Vendor
Trader’s tool
Main Centre of operations –
analyzing market data wrt to
historical data in operational
data store and generating
orders
Server Exchange

• If data operations are simple… operational data store can be in
application layer (trader’s pc)
Order Manager
Market Data
Operation
al Data
Store
Exchange
Data
Warehouse
/
Storehouse
of
historical
data
Data Vendor
Trader’s tool
Main Centre of operations –
analyzing market data wrt to
historical data in operational
data store and generating
orders
Application Server Exchange

System Architecture of an Automated Trading System
• With the advent of DMA & automated trading, the
following changes in architecture took place:
– Latency between Event Occurrence & Order Generation had to be
reduced to an order of milliseconds and lower.
– Order Management had to be made more robust to handle generation
of thousands of orders in a second
– Risk Management had to be done in real time and without human
intervention

System Architecture of an Automated Trading System
• To be able to back-test strategies, two components are
required: (ii) a simulator destination instead of an actual
exchange
Application
Order Manager
Market Data
Complex Event Processing
engine
Exchange 1
Storage
Application Server Exchange
Strategy
Settings
UI
State Mgmt
(PnL +
Position)
Order /
Execution
Monitor
Within
application
RMS
Maths
Calc
RMS
Admin
Monitor
Exchange 2
F
I
X
F
I
X
Data
Normalizer
Order
Router
Back
office
record
MktData
Store
Event
History
Adaptor for
third party
apps – R,
Matlab, etc
Data
Retrieval
Data Vendor
Replay of
stored
data
Simulator
exchange

Introduction to low latency
• Technology – State of Art
• Approach to latency improvement
• Latest in Low Latency -approaches and technologies
being deployed to achieve low latency

Why aim for Low Latency or Lowest ?
• It may be necessary to lower latency just to remain competitive
• The strategy demands low latency, perhaps.
• It may be desirable to improve latency to stop getting picked off by competitors
• With introduction of Colocations and increasing focus in remaining fastest in the
market, significant capital is invested. However it can all go waste, if correct
technology is not identified and implemented.
• The issue is that latency is difficult to quantify. As a result the value of latency
improvement, though easily understood, is extremely difficult to quantify
• Lower latency systems cost a lot more to build and deploy. Hence the objective
should be to find the right balance between investment and return on investment
in low latency

Latencies – Strategy wise
Citihub, 2009

Current Scenario
• Synchronized Markets – Correlated
• Volumes and Trades have increased
• Orders per Trade has increased drastically
• Synchronized Trading Patterns
• Need to increase throughput and lower latency
simultaneously
• CPUs not getting faster – since 2007. Only cores are
being added, not the frequency. Moore’s Law is
failing

Performance Degradation with Throughput
http://www.ibm.com/developerworks/websphere/library/techarticles/0706_lou/0706_lou.html

Causes of Degradation
• Massive headroom to allow for bursts typically 10:1 (like bridges and dams)
• Can be triggered by a shortage of any one of it’s resources:
– CPU cycles
– Memory
– I/O channel capacity
– Disk transfers
– Network transfers
• Shortage of one can trigger another e.g. shortage of memory causing CPU
Typical system response time against throughput and I/O thrashing
• Distributed deployments add an order of magnitude more complexity

Amdahl’s law
• Amdahl's law, also
known as Amdahl's
argument,is used to find
the maximum expected
improvement to an
overall system when
only part of the system is
improved. It is often
used in parallel
computing to predict the
theoretical maximum
speedup using multiple
processors.

Network Effects

Latency by Distance

Spread Networks
Estimated roundtrip time for an ordinary cable is 14.5 milliseconds,
giving users of Spread Networks a slight advantage.
In October 2012, Spread Networks announced latency
improvements, bringing the estimated roundtrip time from 13.1
milliseconds to 12.98 milliseconds.
Some companies, such as McKay Brothers and Tradeworx, are using
air-based transmission to offer lower estimated roundtrip times (9
milliseconds and 8.5 milliseconds respectively) that are very close
to the theoretical minimum possible (about 7.5-8 milliseconds).

Microbursts

Corvil Analysis
“For this feed, how much bandwidth is needed to protect
99.99% of packets from loss with no more than 100
microseconds of latency to be experienced during the busy 1
second of the trading day”

Latency Recommendations

Latency Breakdown
• Latency can be broken down into the following components
• L = P + N + S + I + AP
– P is Propagation time - sending the bits along the wire,
speed of light constrained
– N is Network packet processing – routing, switching and
protection
– S is Serialization time - pulling the bits on/off the wire
– I is Interrupt handling time – receiving the packet on a
server
– AP is Application Processing time

Technology Mix

Costs in Time (Years) for Time Reduction (micro-seconds)

Tips
• Servers – Fastest Cores, Cache,
• Operating Systems – RT kernels
• Fastest Network Infra (Switches, Routers )
• Retune the TCP stack
• Program Runtime – isolcpus, stack bypass
• Solid State Drives
• Latency Tuning – TCP_NODELAY, sendfile(2), Lock
Free Codes

Sample Solution Path

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Program Delivery
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Latency war the present & the future

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