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

BittWare’s TeraBox Bulks Up FPGA Processing for Trading Scale and Analytics

Subscribe to our newsletter

FPGA specialist BittWare has introduced TeraBox, an appliance that delivers up to 16 FPGAs, and targeted at high scale trading and analytics applications.

TeraBox supports up to eight BittWare S5-PCIe-DS cards, each of which hosts two Altera Stratix V FPGAs, 64 gigabytes of RAM and 16 10gE network ports. Thus, each 5U appliance can scale to 16 FPGAs, 512GB of RAM and 128 10gE ports. The appliance can also optionally host a traditional x86 processor, perhaps for monitoring or co-ordination functionality.

According to BittWare’s vice president of systems and solutions Ron Huizen, TeraBox has two likely applications in the financial markets:

* For trading systems where the entire application logic is hosted on the FPGA card, TeraBox offers high scale in one appliance, thus reducing cost of deployment compared with server-hosted approaches. Algorithmic trading and real-time risk control are applications that can likely be deployed more cost effectively with TeraBox.
* For analytics applications, such as algo back testing, pre-trade analytics and risk managemnt, TeraBox’s multiple FPGAs can work together to provide parallelised performance. Connectivity between the FPGAs can be acheived via the chassis PCIe bus, or via the 10gE network.

The latter analytics example would be to some extent breaking new ground for FPGAs, which typically have been dedicated to specific functions, such as data feed processing. For the most part, parallel analytics applications have been targeted at multi-core x86 processors, or at GPUs.

A key to deploying FPGAs for parallel applications will be the introduction of the next version of the OpenCL programming framework. OpenCL 2.0 – the specification for which was released this July – calls for support for dynamic parallelism and shared virtual memory.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research

Date: 20 May 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes For many quantitative trading firms and asset managers, building a self-provisioned historical market data environment remains one of the most time-consuming and resource-intensive steps in establishing a new research capability. Sourcing data, normalising symbologies, handling corporate actions and maintaining...

BLOG

Bloomberg Enhances RMS Enterprise to Unlock Proprietary Models and Strengthen Research Oversight

Bloomberg has announced significant enhancements to its enterprise-level Research Management Solution (RMS Enterprise), introducing two new capabilities: Custom Fundamentals and Digest Alerts. The updates are designed to address long-standing data interoperability challenges within investment firms, allowing research teams to better integrate proprietary financial models into their workflows and strengthen oversight across their organisations. For many...

EVENT

TEST Event page 2

Now in its 15th year the TradingTech Summit London brings together the European trading technology capital markets industry and examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.

GUIDE

Regulatory Data Handbook 2019/2020 – Seventh Edition

Welcome to A-Team Group’s best read handbook, the Regulatory Data Handbook, which is now in its seventh edition and continues to grow in terms of the number of regulations covered, the detail of each regulation and the impact that all the rules and regulations will have on data and data management at your institution. This...