About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

STAC Points to Everest Boost

Subscribe to our newsletter

Via a report sponsored by data feed handler specialists SR Labs, the benchmarkers at STAC have just announced data for initial tests run on Intel’s recently-introduced Everest chip. Compared to Intel’s standard Westmere chip, one data point suggests a 22% reduction in mean latency.

Everest – or Intel’s Xeon X5698 – is a dual core chip, with each core running at 4.4 Ghz, compared to the X5687 (aka Westmere), with four cores at 3.6 GHz. Intel describes Everest as an “off roadmap” chip designed for “very specific, niche high performance computing applications” while still “running within warranty covered norms, specifications and safe thermal envelope.”

The tests were run using SR Labs’ MIPS (Market Data In Process System) feed handling software. While multi-core chips are often leveraged to boost application performance, some applications are inherently single-threaded, and so benefit more from increased speed of each core. Market data feed handlers and exchange matching engines are two such applications.

For the geeks, the two “stacks under test” comprised:

– SR Labs MIPS In-Process Market Data Line Handler for TVITCH 4.1 
– CentOS 5.5, 64-bit Linux 
– IBM x3650 Server 
– Myricom 10G-PCIE2-8B2-2S Network Interface 
– Processor: 
SUT A: 2 x quad core Intel Xeon 5687 3.60 GHz (“Westmere”) 
SUT B: 2 x dual core Intel Xeon 5698 4.40 GHz (“Everest”)

The test harness for this project incorporated TS-Associates’ TipOff and Simena F16 Fiber Optic Tap for wire-based observation, along with TS-Associates’ Application Tap cards for precise in-process observation. A Symmetricom SyncServer S350 was the time source for the harness.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: The Role of Data Fabric and Data Mesh in Modern Trading Infrastructures

The demands on trading infrastructure are intensifying. Increasing data volumes, the necessity for real-time processing, and stringent regulatory requirements are exposing the limitations of legacy data architectures. In response, firms are re-evaluating their data strategies to improve agility, scalability, and governance. Two architectural models central to this conversation are Data Fabric and Data Mesh. This...

BLOG

The New Shape of Market Data: Why Institutions Are Moving Toward a More Modular, Machine-Readable Architecture

For decades, the market-data ecosystem has been defined by reliance on a handful of dominant vendors. Their breadth, depth and entitlements frameworks became foundational to both the trading desk and the wider enterprise. But the requirements of the modern financial technology stack have shifted dramatically. Cloud-native development, agentic AI workflows, and a proliferation of analytics-driven...

EVENT

Data Management Summit London

Now in its 16th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

Entity Data Management Handbook – Third Edition

Welcome to the third edition of the Entity Data Management Handbook which is available for free download. In this updated edition we delve into the role entity data plays in the smooth running of financial institutions and capital markets, the challenges of attaining high quality data, and various aspects, approaches and technologies involved in managing...