The leading knowledge platform for the financial technology industry
The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

SunGard Accelerates Adaptiv Analytics with GPU Technology

SunGard has accelerated the speed of calculations within its Adaptiv Analytics solution by adding an underlying hardware layer of graphical and computer processing units to the software. The hardware, used in conjunction with the software, is designed to provide rapid credit risk analytics that can support growing demand for scenario-based risk and sensitivity analysis, as well as complex calculations that must be made to satisfy regulatory requirements.

The hardware layer, a card including both graphical processing units (GPUs) and computer processing units (CPUs), is not SunGard’s first attempt to combine Adaptiv Analytics with GPU technology, but it is the company’s first commercial offering in this space.

Mat Newman, executive vice president at SunGard and lead of the company’s Adaptiv business, explains: “A few years ago, Adaptiv Labs looked at the potential of GPUs. A proof of concept confirmed they could provide good calculation speeds and throughput. We talked to a few customers about the technology, but they were not sure how it could be integrated into their architectures. We needed to make the technology more palatable, so we designed a solution that includes an additional library in the software that can access the GPU technology. There is no need for specialist GPU programmers and a programmer can write risk calculations that take advantage of both the GPU and CPU technologies.”

While the processing power of CPU technology has been sufficient for calculations for many years, Newman says forthcoming regulations including more complex calculations require more processing power. SunGard suggests that using the hardware card, firms can carry out complex calculations such as credit valuation adjustment in near real-time, processing up to 100 million valuations per second, compared to average processing using a standalone CPU platform of approximately 22 million valuations per second.

Newman points out that as well as speeding up calculations and supporting more stress testing scenarios in the same time as was previously possible using CPU technology, the inclusion of GPUs can provide hardware cost efficiencies when the same amount of calculations are made in the same amount of time. The hardware card for Adaptiv Analytics is available immediately and can be deployed in house with the software or hosted by SunGard as part of its Adaptiv Analytics managed service.

Related content

WEBINAR

Upcoming Webinar: How to get value from unstructured data: new approaches, tools and capabilities

Date: 19 January 2022 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Unstructured data volumes are huge, varied in type, and ready to be tapped to gain business value. While the theory is sound, the practicalities of capturing, managing, analysing and benefitting from unstructured data can be challenging, but there are...

BLOG

Demystifying Data Science and Analytics

By Sarah Carver, head of digital services at Delta Capita. Data science and analytics are the keys to growth for any financial services organisation, and over the past decade, there has been an increased realisation in the potential value of data. However, despite the increasing importance of data science, many institutions face challenges due to...

EVENT

RegTech Summit New York City

Now in its 5th year, the RegTech Summit in NYC explores how the North American financial services industry can leverage technology to drive innovation, cut costs and support regulatory change.

GUIDE

ESG Handbook 2021

A-Team Group’s ESG Handbook 2021 is a ‘must read’ for all capital markets participants, data vendors and solutions providers involved in Environmental, Social and Governance (ESG) investing and product development. It includes extensive coverage of all elements of ESG, from an initial definition and why ESG is important, to existing and emerging regulations, data challenges...