PredictWallStreet pairs real-time quotes with trader sentiment


PredictWallStreet pairs real-time quotes with trader sentiment

http://www.finextra.com/News/Announcement.aspx?pressreleaseid=51290

Source: PredictWallStreet

PredictWallStreet, the global online stock prediction community, today announced the pairing of real-time stock and index quotes with real-time trader sentiment based on daily polls to facilitate faster data delivery which can result in more powerful intraday trading insights.

Predictions from PredictWallStreet’s online community of thousands of traders and investors are aggregated and processed via proprietary collective intelligence algorithms to produce daily forecasts of stock and index movements.

“While these patented prediction and forecasting technologies are designed to give investors a powerful edge in the market, we continually strive to sharpen that edge,” notes Craig Kaplan, CEO. He adds that “while these forecasts, alone, can be valuable trading tools, combining them with real-time quotes distributed by Interactive Data will enable more insightful trading decisions throughout the day.”

“We are pleased to provide the real-time market data delivery component to PredictWallStreet to support important investment decisions for their subscribers,” said Bill Chambers, Vice President and General Manager for Wealth Solutions at Interactive Data.

Terracotta Blends Low Latency and Big Data (remember they bought APAMA)


Terracotta Blends Low Latency and Big Data

http://low-latency.com/blog/terracotta-blends-low-latency-and-big-data/?utm_source=weekly&utm_medium=email&utm_campaign=ll_13-07-18

Software AG’s Terracotta unit has introduced its Universal Messaging product, a middleware platform spanning enterprise to web to mobile connectivity, providing low latency performance and big data transport as appropriate – and aligning with the emerging ‘big data in motion’ paradigm.

“Big, fast data at your fingertips requires seamless real-time data movement, no matter what type of system or device you are using,” says Eddie McDaid, managing director of Universal Messaging at Terracotta.

Previously offered as part of the webMethods SOA middleware offered by its parent, Terracotta is integrating Universal Messaging with its BigMemory in-memory technology and In-Genius analytics offerings. The origin of the product is with my-Channels, which Software AG acquired in April 2012.

Universal Messaging offers common APIs – for C++, C#, Java, VBA, .Net and Python – to support publish/subscribe, message queue and peer-to-peer communications. It also supports a number of different transports, from low-latency shared memory and multicast for enterprise applications, to fuller function sockets and HTTP/S for web and mobile.

Indeed, the product supports a number of electronic trading services, including for FX and fixed income, from the likes of Deutsche Bank, UBS, Credit Suisse, JPMorgan Chase and Tullett Prebon. 

Separately, Terracotta this week completed its acquisition of complex event processing vendor Apama, which is also likely to form part of its big data platform, offering the ability to perform analytics on streaming data

Azul Systems forms commerical partnership with Simplex Consulting


Azul Systems forms commerical partnership with Simplex Consulting

http://www.atmonitor.co.uk/news/newsview.aspx?title=azul-systems-forms-commerical-partnership-with-simplex-consulting

Published on   Jul 10, 2013

logo

 Azul Systems, the provider of Java runtime scalability, has announced the formation of a commercial partnership with Japanese financial technologies firm Simplex Consulting Inc.

Under the agreement, Simplex will add Azul’s Zing Java Virtual Machine (JVM) to its portfolio of Java-based trading solutions which includes Simplex FX (FX trading platform), Simplex PRISM (derivatives front/middle office solution suite), Simplex BLAST (equities and listed derivatives front/middle office solution suite) and will promote Zing to its new and existing clientele. The combination of Zing and Simplex’s solutions aims to provide reliable, dependable and high throughput delivery of messages, low latency for market access or algorithmic trading, and high performance for large, memory-consuming risk calculations for various asset classes such as CVA (credit value adjustment) risk calculations.

Hidekazu Sugiura, Partner at Simplex Consulting commented; “Before we signed an agreement with Azul Systems, we conducted a three (3) month Java benchmarking exercise to evaluate the effectiveness of Zing with our equities trading system. Our findings concluded that Zing immediately reduces latency jitters with minimal tuning effort. Latency and Java application performance are business-critical issues for many of our customers, hence the strong interest in promoting Zing. It is by far the best JVM on the market for any industry sector capitalizing and wanting to leverage low latency with application efficiency.”

Scott Sellers, CEO, Azul Systems, stated: “In Japan, Simplex is a highly respected software vendor for the financial community. Simplex customers demand high quality and flawless execution. By combining Zing with Simplex’s proven trading platforms and building blocks, we can jointly deliver best-in-breed solutions to the financial sector.”

Perseus Brazil Debuts Market-To-Market Liquidity Platform LiquidPath®


Perseus Brazil Debuts Market-To-Market Liquidity Platform LiquidPath®

http://perseustelecom.com/services/products/liquidpath-brazil/

LiquidPath® combines the Perseus award winning connectivity solutions with the Perseus global market-to-market ultra low-latency network. LiquidPath is a fast and cost effective solution for the deployment of the necessary equipment needed to be staged in foreign markets so that customers do not have to manage the complexities of having “feet on the street” in new emerging markets.

Perseus Telecom customers see a variety of advantages when choosing LiquidPath:

Through efficient and high-performance trading infrastructure ideal for staging Market Data, Order Management (OMS) as well as Algorithmic and High-Frequency-Trading equipment, customers can benefit from state 0f the art equipment ready to be turned on as a service.

Due to complex and static environments Perseus can offer proximity services for Direct Market Access (DMA) platforms, helping customers getting trading with exchanges or counter parties fast, saving time and money.

Customers can enjoy having balanced IT investments with LiquidPath® making it easier to plan and allocate IT expenditures for trading emerging or foreign markets.

“Liquidity Infrastructure” for local and global buy-side, sell-side and service vendors looking to access the Brazilian Securities marketplace.

LiquidPath combines the Perseus award winning fastest connectivity solution with the Perseus Global Market-to-Market ultra low-latency network . LiquidPath is a fast and cost effective solution for the deployment of trading infrastructure into foreign markets so that your firm does not have to manage the complexities of local “feet on the street” in new markets you may want to trade.

Perseus Telecom customers see a variety of advantages when choosing LiquidPath:

Efficient and high-performance trading infrastructure ideal for staging Market Data, Order Management (OMS) as well as Algorithmic and High-Frequency-Trading equipment.

Complex and static environment optimal in colocation and proximity services for Direct Market Access (DMA) platforms. Well balanced IT investments – support for planning of IT expenditures.

LiquidPath Brazil

Perseus Telecom Brazil helps customers meet their requirements for low-latency market access and cost efficient IT products and services saving both time and money.

Infrastructure

  • Exchange proximity colocation
  • Hardware as a service
  • Ultra-low latency connectivity
  • Elasticity (up and downsizing)
  • Managed and Professional Services

Connectivity

  • CT1 – 1st BVMF DC (30µs)
  • CT2 – 2nd BVMF DC (5ms)
  • SP2 / RJ1
  • Internet / Last Mile
  • Global Liquidity Centers Access

Market-To-Market

3-Market-To-Market

HIGH PRECISION TRADING IN COMPLEX MARKETS

Perseus Telecom is an award winning global provider of connectivity and services. We work with best of breed fiber assets globally. Perseus provides customers with the right

network solution at the right price. Whether connecting trading desks to exchanges, establishing global wide area networks, or connecting from Europe and North America to emerging markets in Latin America, Asia and Africa; our customers have the competitive advantage that comes with innovation and experience in finance, banking, technology, law, e-commerce, multi-site enterprise, pharmaceutical, media and telecom sectors.

Informatica Highlights Performance of SMX Messaging


Informatica Highlights Performance of SMX Messaging

http://low-latency.com/blog/informatica-highlights-performance-smx-messaging/?utm_source=weekly&utm_medium=email&utm_campaign=ll_13-06-20

blog | June 18, 2013 – 2:34am | By Pete Harris

Following on from last month’s announcement of Ultra Messaging SMX, Informatica has published a range of latency and throughput performance figures for the shared memory transport, covering a number of programming languages. Messaging latency as low as 39 nanoseconds was recorded, with overall latency more than 16 times lower than tests conducted on an earlier version of the transport, conducted in May 2010.

Ultra Messaging SMX is designed for messaging within a single server – in fact within a single multi-core chip, an architecture that has become increasingly adopted as Intel has rolled out its Sandy Bridge (and now Ivy Bridge) microprocessors – with up to 12 cores on certain Ivy Bridge chips. On chip cache memory is leveraged by SMX, since it is faster than fetching data from standard RAM.

Latency tests were conducted between threads running on the same core (2 threads per core are supported by Intel) and between cores on the same chip. Throughput tests were conducted from one thread to threads across many cores on the same chip. Informatica did not test latency between cores across sockets, since it would have been higher than for a single socket.  

Informatica tested its transport against C, C# and Java APIs, noting that trading systems are often built using a number of languages and so such support is a typical requirement. The test systems for latency included one server with an Intel Xeon E5-1620, with 4 cores, clocked at 3.6 GHz, while for throughput tests a server with a (pre-release) 10 core Ivy Bridge chip, operating at 2.8 GHz, was used. CentOS and Red Hat Linux operating systems were hosts for the C and Java tests, with Microsoft Windows 7 Professional SP1 supporting the C# tests.  

Some highlights from the tests are:

* Thread to thread latency on same core, for the C API, and 16 byte messages, was 39 nanoseconds. The same for 128 byte messages was 48 nanoseconds, for 512 byte messages was 81 nanoseconds. 

* Thread to thread latency on a sibling core, for the C API, was 103 nanoseconds for 16 byte messages, 111 nanoseconds for 128 byte messages, and 135 nanoseconds for 512 byte messages.

* C# and Java latencies were a bit higher.  For example, latency for 512 byte messages between threads on the same core was 135 nanoseconds for C# and 106 nanoseconds for Java.

* As an example of a throughput test, 16 byte messages were transmitted from one thread to up to 19 other threads on the same chip. With 19 receivers and the C API, throughput of 133.92 million messages/secomd was achieved, without batching of messages. Batching – which increases latency – increased this to 305.34 million messages/second. Informatica found that throughput increased nearly linearly as receivers were added.

While the significant decrease in high frequency trading has reduced the overall need for such low latency transports, Informatica notes that it is still required for other trading operations and strategies, such as arbitrage, market making and smart order routing.

S&P Capital IQ launches new Portfolio Risk solution delivering Real-Time Risk Analysis for Multi-Asset Class Portfolios


S&P Capital IQ launches new Portfolio Risk solution delivering Real-Time Risk Analysis for Multi-Asset Class Portfolios

http://www.bobsguide.com/guide/news/2013/Jun/17/sp-capital-iq-launches-new-portfolio-risk-solution-delivering-real-time-risk-analysis-for-multi-asset-class-portfolios.html

Solution incorporates leading risk and scenario analytics with essential market data and fundamentals to produce a one-of-a-kind offering

S&P Capital IQ today announced the launch of its Portfolio Risk solution, an advanced risk and scenario analytics tool that provides traders, portfolio and risk managers with the ability to make decisions about the pricing, hedging and capital management of multi-asset class portfolios in real-time.

Available on the S&P Capital IQ desktop, the product brings together leading risk and portfolio analytics acquired through last year’s purchase of R(2) Financial Technologies and S&P Capital IQ’s extensive market and reference data. The Portfolio Risk solution offers a fully integrated data and analytics platform, eliminating the need to invest in separate data to run risk systems. In addition, it gives users the ability to use interactive portfolio dashboards to aggregate data or drill down to the most detailed level of fundamental financials and research, enhancing understanding of impacts of potential changes on P&L at an actionable level. These views are comprehensive, yet easy to change and organized to suit individual needs.

The Portfolio Risk solution covers a diverse range of asset classes from cash, fixed income and equities to exotic derivatives. By offering best-in-class instrument pricing, portfolio analytics, scenario analysis and stress-testing capabilities via shareable dashboards, it facilitates communication and collaboration around risk and investment strategies while also providing full transparency into underlying methodologies and on-the-fly calculations. These features ensure that risk metrics can be calculated quickly and that new scenarios or market strategies can be tested and acted upon swiftly.

“In just over a year since our acquisition of R(2) Financial Technologies, we have successfully brought together rich data, sophisticated analytics, and relevant market commentary, news and analysis,” said Lou Eccleston, President, S&P Capital IQ. “The result is that our clients can quickly generate a transparent, fully customized risk picture enabling them to react quickly to changes in the market and to new investment ideas.”

“We are just beginning to leverage the depth of S&P Capital IQ’s data resources to deliver what we call ‘risk intelligence,’ including the power to gather new insights into how portfolios behave under varying scenarios,” said Dan Rosen, Managing Director, S&P Capital IQ. “We have assembled one of the most experienced teams of risk and financial engineering experts in the world and dedicated them to delivering interactive, real-time risk analysis as a central part of the investment decision making process.”

DataFluidics™, Reflex™, a revolutionary data processing platform for financial institutions.


DataFluidics Releases Reflex, Changes the Landscape of Ultra-Low Latency Data Processing

http://low-latency.com/article/datafluidics-releases-reflex-changes-landscape-ultra-low-latency-data-processing/?utm_source=weekly&utm_medium=email&utm_campaign=ll_13-06-13

DataFluidics™, the innovative provider of ultra-low latency technology today announced the general availability of Reflex™, a revolutionary data processing platform for financial institutions. In increasingly fragmented markets where volume-driven automated strategies span time zones and hunt razor-thin windows of opportunities, modern trading desks can no longer be satisfied with the ability to make split-second decisions based on a single market data feed. Traders can no longer rely on single-exchange connectivity either. The new frontier of profitability dictates that advanced trading firms combine and analyze several data sources to reach a decision and instantly dispatch orders to multiple destinations. Yet many current infrastructures remain tied to legacy paradigms of single-input / single-destination whose performance dramatically erodes if multi-channel logic is retrofitted into them. Firms can no longer capture profits.

Reflex was built differently. The fruit of several years of cutting-edge research, Reflex leverages the latest architectural paradigms combined with field knowledge of founder and CEO Daniel Kopko at some of the largest and most profitable firms on Wall Street.

“Reflex was built on the tangible requirement to reshape the way firms process data in today’s trading landscape”, says Kopko. “For many years I observed how firms were prevented from enacting trading ideas because the legacy platforms their execution systems were built on could not accommodate the complex interwoven streams of analytics data and real-time prices which they required.”

Reflex is optimized to enable the combination and correlation of several streaming data feeds to produce composite decisions based on highly-advanced scheduling and processing rules. With reactions capable of achieving ultra-low latency of 1.6 microseconds (with a 99 percentile of 2.5 microseconds), Reflex sets a new standard for software-based solutions which can now directly compete with more expensive alternatives such as custom FPGAs.

“The financial industry is a critical juncture: as the markets recover, some firms will reap the profits of technological choices that will pave the way to substantial gains while others will be left behind”, says Kopko. “We are delighted to make Reflex available as a credible counterpoint to costly, intractable technologies.”

Reflex can be licensed stand-alone or through OEM agreement as embedded technology to enable ultra-low latency trading decisions. The technology can also be purchased or distributed by third-party firms.

For more information or to start a free evaluation of the software, visit www.datafluidics.com or contact info@datafluidics.com

 

Eurex Exchange releases results of proprietary HFT research


Eurex Exchange releases results of proprietary HFT research

http://www.automatedtrader.net/articles/sponsored-articles/142740/eurex-exchange-releases-results-of-proprietary-hft-research

First Published in Automated Trader Magazine Issue 29 Q2 2013 : Sponsored Articles

Eurex Exchange is the first exchange in Europe to share part of its proprietary quantitative research on high- frequency trading (HFT) with the public. Key findings of this research include:

(a) HFT participants played an important and beneficial role during one of the most extreme market situations Eurex Exchange has seen in recent years,

(b) HFT participants play a unique and indispensable role in the recovery of market quality right after large trades, and

(c) Eurex Exchange did not find evidence of abusive HFT activity

Background

Eurex Group continuously invests in deepening its understanding of the structure and dynamics of the markets it operates. Its proprietary data contains a wealth of information on each individual order, down to the level of trader ID and microsecond granularity timestamps. This data uniquely allows the exchange to conduct extremely granular research, which is more important than ever considering the public debate. The analysis is a contribution to much needed empirics in the discussion on HFT.

Defining HFT

Key to the credibility of any research on HFT activity is a solid process to identify which order flow is – and which is not – of HFT origin. Eurex Group argues that HFT is a technologically advanced implementation of a great variety of trading strategies – some of which already existed prior to the existence of electronic trading platforms. Therefore, the exchange’s HFT selection process is based on the technical (instead of functional) characteristics of its participants’ order flow. More specifically, the exchange’s research looks at the inter-arrival time of messages, measured by the number of microseconds between any two consecutive messages from any two different participants.

To understand the underlying logic of the research, imagine a world wherein participants in a market place would not react on the exact same events when making investment decisions. In this world, the speed with which one reacts on any opportunity would generally not matter; there is no other participant hunting for the same opportunity. Therefore, from a system perspective, transaction arrival at the central exchange system would be uncorrelated. There would be a predictable number of observations with a small inter-arrival time and a somewhat smaller number of observations with a higher inter-arrival time. The expected number of observations for any inter-arrival time would be given by a Poisson distribution. In reality, trading activity is partly correlated and, since the rise of HFT, especially on a micro-second time frame. Therefore, there are observations in excess of what might be expected based on the Poisson distribution, particularly in the 0-100 microsecond time frame. These excess observations for very short inter-arrival times serve as a proxy for the ‘HFT-ness’ of a participant.

HFT participants provide important liquidity during periods of extreme market volatility

On 25 August 2011, Eurex Exchange experienced one of the most challenging market situations in its history. An institutional investor (not an HFT participant) offloaded a 6,000 contract DAX® Futures position in a 20 minute period, causing tremendous price pressure. For comparison, the average turnover increased from 300 contracts per minute to more than 1,700 contracts per minute. As a result, the market in DAX® Futures briefly lost more than four percent of its value, making the event look much like the U.S. ‘Flash Crash’. However the situation was different in two very important respects.

Dr. Randolf Roth

Dr. Randolf Roth

Firstly, although liquidity became more expensive, it did not dry up. Spreads widened and the number of available contracts declined, but these are natural consequences of increased demand. Arbitrage (against e.g. EURO STOXX 50® Index Futures, SMI® Futures, etc.) allowed participants to transfer liquidity from correlated instruments to DAX® Futures and vice versa. Trading continued in an orderly fashion, and the volatility interruption that halts trading when prices move too fast was not triggered.

Secondly, HFTs continued to be an important source of liquidity throughout the event, supplying 30 to 50 percent of the contracts available at the best bid and offer. Contrary to what one might expect, their aggregate participation was not skewed to one side or the other. Of course, only an execution proves the relevance of an order. Therefore, it is also important to note that the HFT share of passive executions remained stable and high. Furthermore, contrary to popular belief, the majority of the aggressive side of those executions were not HFT participants. Last, but not least, HFT liquidity was spread out over several price levels at all times, reducing the price impact for large aggressive orders.

HFTs increase their participation in liquidity provision after large trades

Eurex Exchange keeps close contact with end users of its trading system, such as buy side investment firms. Discussions with traders at these firms have proven to be invaluable input for decisions regarding market structure and trading system design. The exchange takes their concerns about market structure very seriously and investigates specific issues wherever possible. An often heard criticism is that HFT liquidity is spurious; “Whenever I try to hit it, it’s gone before my order reaches the exchange”.

To verify or falsify this claim, Eurex Exchange took all add, modify and delete orders and rebuilt the historical order book in EURO STOXX 50® Index Futures for several days from 2012. The exchange defined “large trades” as trades that were 10 to 20 times the 10-minute moving average trade size. In EURO STOXX 50® Index Futures, such trades occur between 400 and 500 times per day. For each 100 milliseconds (ms) in the two seconds around these trades, Eurex Exchange analysed the contracts available at the best price level on the side of the order book that was affected. Based on that, it was possible to calculate the share of contracts provided by HFTs and by non-HFTs respectively (adding up to 100 percent).

Passive HFT activity development around liquidity gaps

Passive HFT activity development around liquidity gaps

Each grey lines depict the daily average market share of HFTs on the relevant side of the BBO before and after a large trade (10 times the trailing 10 minute average) in the front month Eurostoxx future. The blue line is the average of these averages. The graph shows that HFTs do not reduce their participation right before large trades and increase (rather than reduce) their market share of the relevant side of the BBO after large trades.
Bernard Hosman

Bernard Hosman

The results can be found in the figure below. The grey lines represent the combined market share of the exchange’s top 40 HFT participants, whereas the blue line is the average of the grey lines. Remarkably, instead of reducing their participation, it can be seen that on average, HFTs significantly increase their share of contracts on the best price level of the side of the order book where a large trade occurs. Furthermore, it can be seen that the participation of HFT users does not change in the second prior to the execution of the large order. Therefore, the claim that HFT participants revoke their liquidity before a large trade hits the order book does not, in general, hold true.

Strong competition among HFTs yields remarkable improvement in market quality resilience at Eurex

Over the past few years Eurex Exchange has seen a substantial increase in HFT activity. The exchange wanted to quantify the effect of increased competition among liquidity providing HFT participants on market quality. One of the areas it expected to see market structural changes was the resilience of the market; in other words: How fast does the market recover after a large trade? What happens after large trades hit the order book is extremely important as most trading is highly correlated; a slow recovery means unnecessary sub-optimal executions.

Spread resilience

Spread resilience

The grey lines show daily averages for the spread recovery paths in 2010 and 2012. The blue lines are averages for 2010 and 2012. Compared to 2010, the liquidity in the DAX30 futures became much more resilient. The averages converge around 500ms from the big trade.

To quantify the recovery process of market quality, the exchange measured the spread (in ticks) for each millisecond in the two seconds before and after the large trades that caused the spread to widen. Such events happen several hundred times a day in the front-month DAX Futures. Based on these measurements the exchange calculated daily averages for eight similarly volatile days in 2010 and 2012 (grey lines in the graph above).

The chart shows the recovery paths relative to the average pre-trade spread to account for the effect of differences in intra-day volatility; a spread recovery of four ticks is more significant if the initial spread was one tick than if the initial spread was ten ticks. The top blue line is the average of the spread recovery paths in 2010 and the bottom blue line represents those paths in 2012. The most obvious difference between 2010 and 2012 is the significant improvement in the speed of the recovery that took place. Another observation is the fact that the recovery process in 2010 only started after 5-10 ms whereas in 2012 a much faster reaction can be observed. The exchange’s working hypothesis, supported by some early findings, is that these 5-10 ms was the minimum reaction time of some exchange participants, which – at that time – provided the lion’s share of the liquidity in DAX® Futures.

Continuing research

According to the study, high-frequency trading activity is an important positive contributor to overall market quality and stability. The exchange will continue to analyse HFT activity and will share the findings with the industry.

In response to customer requests, Eurex Exchange has posted three videos on its website that detail its analysis of HFT. These include:

• HFT and non-HFT participation during an extreme market situation

• A three dimensional representation of HFT activity

• Zooming into HFT participation during micro shocks

The videos can be viewed at: http://www.eurexchange.com > Technology > High-frequency trading

For more information about technical issues surrounding HFT, please contact:

Bernard Hosman , T +49 69 211 1 3195 or bernard.hosman@eurexchange.com

For more information about legal issues surrounding HFT, please contact:

Randolf Roth , T +49 69 211 1 2793 or randolf.roth@eurexchange.com

TIBCO buys StreamBase


TIBCO buys StreamBase

http://www.automatedtrader.net/headlines/142857/tibco-buys-streambase

StreamBase acquisition strengthens TIBCO event processing & real-time analytics.

Palo Alto, California – TIBCO Software has acquired StreamBase Systems the privately held provider of event processing and real-time analytics software. Financial details of the transaction were not disclosed.

With the aquisition of StreamBase TIBCO will add streaming capabilities to its event processing portfolio, enabling big data to be processed in real-time to provide an event-based alternative to batch-centric big data architectures.

“StreamBase has developed a powerful and easy-to-use offering to monitor, understand, and act on event streams in real-time for one of the most performance-intensive industries in the world today,” said Matt Quinn, CTO of TIBCO Software. “This combination extends our event-processing abilities and provides a terrific opportunity to address a growing number of use cases for data in motion – in financial services and beyond.”

“TIBCO sets the standard in low latency messaging, enterprise integration and visual and computational analytics. Now with streaming event processing and real-time analytics from StreamBase, TIBCO’s big data platform is the most capable in the industry,” said Mark Palmer, CEO, StreamBase Systems. “StreamBase has revolutionised how organisations use real-time data by speeding application development to enable companies to analyse data and take immediate action. We look forward to bringing this significant business advantage to the wide set of industries and customers TIBCO serves.”

HL Steam teams up with BlueBee in FPGA initiative


HL Steam teams up with BlueBee in FPGA initiative

http://hlsteam.com/hl-steam-teams-up-with-bluebee-for-hardware-acceleration/

HL Steam are teaming up with BlueBee in an Anglo-Dutch initiative to port the Ancoa market integrity platform towards FPGA-accelerated computer architectures.

The architectures in question here include the Convey HC-2ex, which contains:

  • 4 Intel processors of 8 cores each
  • 4 Xilinx FPGA blades
  • 64GB RAM memory
  • 80GB internal bandwith

The main goal of the project is to demonstrate that it is possible with FPGA to more efficiently process real world workloads of financial trading data at a lower cost, both in dollar and in energy terms, reducing both capital and operational expenditure.

As we see it, processing big data in financial markets requires a diverse computational approach. This means that using general purpose processors (CPUs) exclusively will not give you optimal performance. Certain parts of the processing will be better handled using GPUs, or other types of processor, if those operations need to be done on a large number of data elements in parallel.

Field-Programmable Gate Arrays (FPGA) are becoming an increasingly popular computing option, as they combine the speed and energy efficiency of hardware, with the programmability and usability of general purpose processors (CPUs).

FPGAs have been around for over 25 years, but can be notoriously difficult to program in a flexible, generic way, which is one reason why they have yet to gain the widespread popularity of GPUs despite offering great performance gains over CPUs and energy advantages.

Bluebee, a spin-off from Delft University of Technology and Imperial College, has developed a methodology to substantially increase the ease and flexibility with which platforms with heterogeneous computing elements (including FPGA) can be programmed.

The challenge here is in finding the right mapping of the application to the different processing elements, and with FPGA acceleration, to have hardware implementations of those functions for which substantial speedups are possible.

Prof Koen Bertels, CEO of Bluebee, is delighted to work with HL Steam, a London-based team who are taking a unique data-centric approach to market integrity in financial markets.

The two companies complement each other’s expertise in hardware and software, and form an ideal fit for BlueBee to prove the possibility of a significant increase in computing performance, by making FPGA available to big data applications in finance.

For further information please contact:

Prof. Koen Bertels, CEO BlueBee
Minderbroerstraat 26
2611 MV Delft
The Netherlands
www.bluebee.com

Stefan Hendrickx, CEO HL Steam
The Generator Business Centre
Unit 13, 95 Miles Road
London CR4 3FH
United Kingdom
www.hlsteam.com
+44 20 8408 1610

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