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 Benchmarks GPUs for Options Risk Analytics

Subscribe to our newsletter

STAC has for the first time published results for its STAC-A2 options risk analytics benchmarks running on Nvidia graphics processing units (GPUs) that point to a near order of magnitude speed up compared to traditional x86 CPUs.

STAC-A2 is a suite of benchmark tests developed by market participants that measure the time to complete the calculation of a set of Greeks values for an option (which measure the sensitivity of the price of an option to changes, such as price of the underlying asset, volatility, interest rates, etc.). Thus, Greeks – which should be recalculated as an options price varies – provide a risk management tool for assessing market impacts on a portfolio of options.

In order to conduct the benchmarks, STAC built a system based on an IBM server with two Intel ‘Sandy Bridge’ x86 processors and two Nvidia K20Xm GPUs. Nvidia coded the STAC benchmarks using the CUDA toolkit, which is designed to implement parallel high performance computing workloads.

Among the several benchmarks calculated, results for STAC-A2.?2.GREEKS.TIME – the time taken to calculate a set of Greeks – showed a 9x improvement compared to benchmarks run on the same class of x86 processors, without GPU acceleration.

While the results are simply indicators of performance, they do point to the value of GPUs to handle complex calculations, which increasingly need to be performed in real time as part of intelligent trading strategies.

As such, GPUs complement other acceleration approaches, such as FPGAs, which have been widely implemented to perform data manipulation functions for low-latency market feed handling and trade execution. Future trading system architectures may well incorporate both FPGAs and GPUs alongside traditional CPUs to provide a best of breed platform for all aspects of a trading strategy.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Data platform modernisation: Best practice approaches for unifying data, real time data and automated processing

Financial institutions are evolving their data platform modernisation programmes, moving beyond data-for-cloud capabilities and increasingly towards artificial intelligence-readiness. This has shifted the data management focus in the direction of data unification, real-time delivery and automated governance. The drivers of this transition are improved operational efficiency as manual processes are replaced by faster, more accurate automated...

BLOG

Beyond the Blueprint: Integrating Data Fabric and Data Mesh in Capital Markets

The demands placed upon modern trading infrastructures, driven by increasing data volumes, the mandate for real-time processing, and stringent regulatory requirements, are exposing the limitations of historical data architectures. In response, capital markets firms are accelerating the re-evaluation of their data strategies to secure greater agility, scalability, and enhanced governance. A recent webinar hosted by...

EVENT

ExchangeTech Summit London

A-Team Group, organisers of the TradingTech Summits, are pleased to announce the inaugural ExchangeTech Summit London on May 14th 2026. This dedicated forum brings together operators of exchanges, alternative execution venues and digital asset platforms with the ecosystem of vendors driving the future of matching engines, surveillance and market access.

GUIDE

Complex Event Processing

Over the past couple of years, Complex Event Processing has emerged as a hot technology for the financial markets, and its flexibility has been leveraged in applications as diverse as market data cleansing, to algorithmic trading, to compliance monitoring, to risk management. CEP is a solution to many problems, which is one reason why the...