Data Fabric White Paper
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Transcript of Data Fabric White Paper
Thinking Outside the Stack:Data Fabric – a high performance, low latency,
message-oriented middleware platform
Table of Contents
Introduction ................................................................................................................... 2
Evolving Business Needs ........................................................................................ 3
Background – The limits of older approaches to data distribution......... 4
Innovation without obsolescence ..........................................................................5
Summary .......................................................................................................................11
Thinking Outside the Stack | 2
IntroductionAs market data volumes continue their inexorable rise, the need to widely distribute that data to drive business applications increases exponentially. Yet most distribution technologies still rely on an aged IP stack unable to scale with increasing data volumes to achieve low latency, determinism, throughput and scalability.
In this white paper, NYSE TechnologiesSM describes establishing a foundation for the next generation of business applications through Data Fabric™, a high performance, low latency, message oriented middleware platform for distributing significant volumes of application level information across the enterprise.
Building on the innovation first introduced in earlier versions of NYSE Technologies’ messaging infrastructure and based on years of production experience, the Data Fabric architecture by-passes both the kernel and operating system, while using industry standard servers and 10 Gigabit Ethernet or 40 Gigabit InfiniBand networks to achieve unprecedented performance.
3 | Thinking Outside the Stack
Firms need speed, reliability, scalability and flexibility in the data feeds to their analytics and trading systems. The main benefits of Data Fabric to meet these needs are:
� Reduced cost through hardware footprint reduction, and minimizing operational complexity.
� Reduced latency, utilizing direct memory access and kernel bypass methods.
� Flexible deployment options with multiple transports to fulfil different deployment strategies.
Systems based on legacy technology are always lagging behind and missing opportunities. Of course, there are quick fixes. Pushing older system designs to the limits by, for example, placing them on new servers and operating systems might improve latency to some extent but it will not solve jitter – unpredictability that can result in data delivery delays. Also unexpected changes in system load due to external events, such as economic news, make capacity planning as much an art as a science; modern systems need to be able to deal with dramatic load changes.
Undoubtedly, market data rates will continue to grow. Massive volatility in trading volumes, such as the “Flash Crash” make planning difficult and require designs that provide headroom in daily operations to accommodate sharp and significant spikes in market data volumes. Firms cannot afford to deliver data too slowly because the operating
system is churning away on different tasks while managing data. Data Fabric offers proven technology to handle huge volumes of data with consistently low latency.
In addition to the sheer growth in data volumes, financial firms are increasing the complexity of their trading platforms. Where they once might have relied on a few algorithms, now they have dozens or even hundreds across the firm. The challenge is to deliver the data to everyone who needs it with the lowest possible latency. With NYSE Technologies’ Data Fabric, they can deploy their algorithms across dozens of machines with no significant adverse effect on latency.
Data Fabric offers firms the opportunity to take a fresh look at how they deploy their trading engines and the types of trading strategies they employ. With highly reliable, low latency delivery, a firm which previously had positioned all its trading on a single box to avoid delays and jitter can now distribute trading applications more widely. This also allows firms to look at more sophisticated multi-asset trading; they can distribute data from multiple sources to multiple users with minimal latency.
With the availability of OpenMAMA™, firms have the added flexibility of an open source messaging API to utilize Data Fabric. OpenMAMA eliminates the risk of vendor lock-in, protects the investment in technology, and reduces friction associated with implementing new trading technologies.
Evolving Business Needs
Thinking Outside the Stack | 4
The traditional method for distributing data throughout a firm is message-oriented middleware based on TCP/IP, which provides a way to publish data from many sources to consumers through either multicast or point-to-point semantics. A message must traverse multiple layers in the TCP/IP stack for both the sender and the receiver, requiring additional processing time and context switching to complete delivery. Before transmission, the message is copied from application memory into operating system memory on the host, before being published on the network. When the message is received by the interested host, it follows the reverse process and is copied from operating system memory into application memory. These copy operations introduce non-deterministic latency as the processor must allocate cycles to the operating system in addition to the application.
Still today, TCP encounters significant difficulty in scaling and ensuring fairness among multiple subscribers. Increasing the number of subscribers to a single publisher degrades the performance of the publisher in terms of message processing as well as latency, since it must maintain message transports to each individual subscriber. The order of subscriptions is also impacted, as the first subscriber will receive messages earlier than the last subscriber in a round robin delivery method.
In order to address the limitations of TCP, UDP multicast became the dominant technology for high performance data distribution. However, multicast is a one-size-fits-all approach where the client system is responsible for consuming all data on a multicast group and discarding data. Workarounds do exist, like partitioning the multicast by consumer demand or isolating small consumers. However, these introduce more complexity, which leads to higher maintenance costs and reduced flexibility. The ability of a client system to consume data is limited by the kernel and IP stack’s capacity to process data. On a modern server, the amount of application processing capacity outstrips the ability of the IP stack to service those clients. The net result is buffer overruns with substantial data loss or excessive dwell time in the kernel, resulting in poor system performance.
Performance issues in middleware and software are problematic as market data volumes grow, server hardware advances in speed and networks continue to increase capacity and speed. The IP technology stack, now over 30 years old, is showing its age and is the bottleneck in data messaging.
Application
Driver
NIC
TCP/IP Transport Driver
TCP/IP Sockets Provider
App Memory
Kernel Memory
Application
Driver
NIC
TCP/IP Transport Driver
TCP/IP Sockets Provider
App Memory
Kernel Memory
Network Infrastructure
Application
Driver
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Publisher
Application
Driver
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TCP/IP Sockets Provider
TCP/IP Transport Driver
TCP/IP Sockets Provider
App Memory
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App Memory
Kernel Memory
TCP/IP Transport Driver
Figure 1. TCP/IP implementation
Background -The Limits of Older Approaches to Data Distribution
While the IP stack is ubiquitous for moving the vast majority of data over networks today, it is still based on the same approach that was introduced with the advent of UNIX and the Internet in the 1970s.
5 | Thinking Outside the Stack
Breaking new boundaries, NYSE Technologies was one of the first to market with Remote Direct Memory Access (RDMA), which writes data messages to local memory and then replicates them to other computers in microseconds.
This approach revolutionized the movement of data and clearly showed its superiority over IP-based messaging systems. However, as with any point-to-point solution, it can suffer when widespread distribution is required. The first client will receive the data very quickly but as additional clients are added, the message must be sent to each client, resulting in additional latency and network bandwidth.
Local Direct Memory Access (LDMA) is similar, but as the name suggests, it operates within a single physical server. As the number of cores on a server has increased, application architects have been able to collapse their designs so that market data consumption, analytics and trading can be deployed on a single server. NYSE Technologies introduced an LDMA messaging model enabling extremely high performance for messaging applications where the publisher and subscribers are located on the same server.
A publisher writes a message to the Data Fabric transport, which is sent to the network once and the physical switch replicates to all interested clients. On receipt, the message is moved straight to user space memory where Data Fabric does a rapid look-up to determine if any clients are interested. At no point is the IP stack involved. The net result is that Data Fabric MultiVerb offers substantial savings in CPU utilization and latency, while delivering significant scalability.
Now with Data Fabric, NYSE Technologies is once again introducing an industry leading transport, MultiVerb. By taking advantage of the IB verbs over Infiniband or 10 gigabit Ethernet, Data Fabric utilizes full kernel bypass and zero copy semantics, and now uses multicast delivery to be able to achieve massive scalability with minimal latency.
Innovation without Obsolescence Publisher
Application
HCA
DMA Ring Buffer
Subscriber
Application
HCA
DMA Ring Buffer
Data Fabric RDMA
Data Fabric RDMA
Interrupt/Copy Boundary
Interrupt/Copy Boundary
InfiniBand / 10 Gigabit Ethernet
Send once - network replicates packets
Publisher
Application
HCA
Memory Region
HCA
InfiniBand / 10 Gigabit Ethernet
Data Fabric MultiVerb
Interrupt/Copy Boundary
Interrupt/Copy Boundary
Application
Memory Region
Data Fabric MultiVerb
HCA
Interrupt/Copy Boundary
Application
Memory Region
Data Fabric MultiVerb
HCA
Interrupt/Copy Boundary
Application
Memory Region
Data Fabric MultiVerb
HCA
Interrupt/Copy Boundary
Application
Memory Region
Data Fabric MultiVerb
Figure 3. Data Fabric Local Direct Memory Access (LDMA) transport schematic.
Figure 4. Data Fabric MultiVerb transport schematic.
Figure 2. Data Fabric Remote Direct Memory Access transport schematic.
DMA Ring Buffer
DMA Ring Buffer
Publisher Application
Data Fabric LDMA
Data Fabric LDMA
Subscriber Application
Interrupt/Copy Boundary
Thinking Outside the Stack | 6
Data Fabric also supports traditional TCP over 1 Gigabit Ethernet for less demanding applications that require firewalls or wider distribution.
Data Fabric works with NYSE Technologies’ Open Middleware Agnostic Messaging APITM(OpenMAMATM) which allows firms to choose the middleware, or combination of middleware tools, that best suit their current needs. Data Fabric supports multiple IPC idioms including TCP, shared memory, LDMA, RDMA and MultiVerb, without requiring specialized network knowledge of software developers.
As a firm’s architecture changes, they can reconfigure their systems without writing new code. Moving from one transport to another is merely a configuration change. The solution also offers zero client configuration by centralizing this to the Naming Service Daemon (NSD). The NSD also maintains detailed client statistics to ease management and control.
NYSE Technologies is a trusted name in capital markets and continues to innovate by constantly working on new developments. To keep ahead of user requirements, NYSE Technologies is testing Data Fabric on Intel Sandy Bridge processors and on large multi-core boxes with 60 to 80 cores.
Figure 5. MultiVerb transport latency results with 1000 consumers on a QDR InfiniBand network.
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www.nyx.com©2012 NYSE Euronext All Rights Reserved dc/N11605/120130
© 2012 NYSE Euronext. All rights reserved. All third party trademarks are owned by their respective owners and are used with permission. OpenMAMA™ is a trademark owned by the Linux Foundation. This announcement may contain forward-looking statements regarding NYSE Euronext and its affiliates. Such statements are based upon the current beliefs and expectations of management and are subject to significant risks and uncertainties. Actual results may differ from those set forth in the forward-looking statements
Summary As a trusted name in capital markets, NYSE Technologies continues to break new ground in next generation messaging and is fundamentally changing the approach to middleware. While upgrading servers and networks improves performance, this moves the bottleneck to the software stack, which has lagged behind improvements in hardware technology. By leveraging next generation hardware and semantics, Data Fabric delivers breakthrough performance as the capital markets community faces increasing challenges. It’s all about thinking outside the stack.
Find Out MoreCall: +1.212.510.3600 +44 (0)207 379 2897
Email: [email protected]
Visit: http://nysetechnologies.nyx.com/data-technology/data-fabric