jm + martin-thompson   7

"Aeron: High-Performance Open Source Message Transport" [slides, PDF]
a new networked pub/sub library from Martin "Disruptor" Thompson, based around a replicated, persistent log of messages, with exceptionally low latency. Apache-licensed. Very similar to the realtime messaging stack we've built in Swrve. ;)

https://github.com/real-logic/Aeron
realtime  messaging  pub-sub  ipc  queues  transports  martin-thompson  slides  latencies  open-source  java  libraries 
november 2014 by jm
Simple Binary Encoding
an OSI layer 6 presentation for encoding/decoding messages in binary format to support low-latency applications. [...] SBE follows a number of design principles to achieve this goal. By adhering to these design principles sometimes means features available in other codecs will not being offered. For example, many codecs allow strings to be encoded at any field position in a message; SBE only allows variable length fields, such as strings, as fields grouped at the end of a message.

The SBE reference implementation consists of a compiler that takes a message schema as input and then generates language specific stubs. The stubs are used to directly encode and decode messages from buffers. The SBE tool can also generate a binary representation of the schema that can be used for the on-the-fly decoding of messages in a dynamic environment, such as for a log viewer or network sniffer.

The design principles drive the implementation of a codec that ensures messages are streamed through memory without backtracking, copying, or unnecessary allocation. Memory access patterns should not be underestimated in the design of a high-performance application. Low-latency systems in any language especially need to consider all allocation to avoid the resulting issues in reclamation. This applies for both managed runtime and native languages. SBE is totally allocation free in all three language implementations.

The end result of applying these design principles is a codec that has ~25X greater throughput than Google Protocol Buffers (GPB) with very low and predictable latency. This has been observed in micro-benchmarks and real-world application use. A typical market data message can be encoded, or decoded, in ~25ns compared to ~1000ns for the same message with GPB on the same hardware. XML and FIX tag value messages are orders of magnitude slower again.

The sweet spot for SBE is as a codec for structured data that is mostly fixed size fields which are numbers, bitsets, enums, and arrays. While it does work for strings and blobs, many my find some of the restrictions a usability issue. These users would be better off with another codec more suited to string encoding.
sbe  encoding  protobuf  protocol-buffers  json  messages  messaging  binary  formats  low-latency  martin-thompson  xml 
may 2014 by jm
Java Garbage Collection Distilled
a great summary of the state of JVM garbage collection from Martin Thompson
jvm  java  gc  garbage-collection  tuning  memory  performance  martin-thompson 
july 2013 by jm
'Mythbusting Modern Hardware to gain "Mechanical Sympathy"' [slides]
Martin Thompson's latest talk -- taking a few common concepts about modern hardware performance and debunking/confirming them, mythbusters-style
mythbusters  hardware  mechanical-sympathy  martin-thompson  java  performance  cpu  disks  ssd 
may 2013 by jm
Martin Thompson, Luke "Snabb Switch" Gorrie etc. review the C10M presentation from Schmoocon
on the mechanical-sympathy mailing list. Some really interesting discussion on handling insane quantities of TCP connections using low volumes of hardware:
This talk has some good points and I think the subject is really interesting.  I would take the suggested approach with serious caution.  For starters the Linux kernel is nowhere near as bad as it made out.  Last year I worked with a client and we scaled a single server to 1 million concurrent connections with async programming in Java and some sensible kernel tuning.  I've heard they have since taken this to over 5 million concurrent connections.

BTW Open Onload is an open source implementation.  Writing a network stack is a serious undertaking.  In a previous life I wrote a network probe and had to reassemble TCP streams and kept getting tripped up by edge cases.  It is a great exercise in data structures and lock-free programming.  If you need very high-end performance I'd talk to the Solarflare or Mellanox guys before writing my own.

There are some errors and omissions in this talk.  For example, his range of ephemeral ports is not quite right, and atomic operations are only 15 cycles on Sandy Bridge when hitting local cache.  A big issue for me is when he defined C10M he did not mention the TIME_WAIT issue with closing connections.  Creating and destroying 1 million connections per second is a major issue.  A protocol like HTTP is very broken in that the server closes the socket and therefore has to retain the TCB until the specified timeout occurs to ensure no older packet is delivered to a new socket connection.
mechanical-sympathy  hardware  scaling  c10m  tcp  http  scalability  snabb-switch  martin-thompson 
may 2013 by jm
Single Producer/Consumer lock free Queue step by step
great dissection of Martin "Disruptor" Thompson's lock-free single-producer/single-consumer queue data structure, with benchmark results showing crazy speedups. This is particularly useful since it's a data structure that can be used to provide good lock-free speedups without adopting the entire Disruptor design pattern.
disruptor  coding  java  jvm  martin-thompson  lock-free  volatile  atomic  queue  data-structures 
march 2013 by jm

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