NVIDIA recently shared a case study involving risk calculations at a JP Morgan Chase that I think is significant for the extreme levels of acceleration gained by integrating GPUs with conventional CPUs, and also as an illustration of a mainstream financial application of GPU technology.
JP Morgan Chase’s Equity Derivatives Group began evaluating GPUs as computational accelerators in 2009, and now runs over half of their risk calculations on hybrid systems containing x86 CPUs and NVIDIA Tesla GPUs, and claims a 40x improvement in calculation times combined with a 75% cost savings. The cost savings appear to be derived from a combination of lower capital costs to deliver an equivalent throughput of calculations along with improved energy efficiency per calculation.
Implicit in the speedup of 40x, from multiple hours to several minutes, is the implication that these calculations can become part of a near real-time business-critical analysis process instead of an overnight or daily batch process. Given the intensely competitive nature of derivatives trading, it is highly likely that JPMC will enhance their use of GPUs as traders demand an ever increasing number of these calculations. And of course, their competition has been using the same technology as well, based on numerous conversations I have had with Wall Street infrastructure architects over the past year.
My net take on this is that we will see a succession of similar announcements as GPUs become a fully mainstream acceleration technology as opposed to an experimental fringe. If you are an I&O professional whose users are demanding extreme computational performance on a constrained space, power and capital budget, you owe it to yourself and your company to evaluate the newest accelerator technology. Your competitors are almost certainly doing so.
The lines are blurring between software and services — with the rise of cloud computing, that trend has accelerated faster than ever. But customers aren’t just looking at cloud business models, such as software-as-a-service (SaaS), when they want more flexibility in the way they license and use software. While in 2008 upfront perpetual software licenses (capex) made up more than 80% of a company’s software license spending, this percentage will drop to about 70% in 2011. The other 30% will consist of different, more flexible licensing models, including financing, subscription services, dynamic pricing, risk sharing, or used license models.
Forrester is currently digging deeper into the different software licensing models, their current status in the market, as well as their benefits and challenges. We kindly ask companies that are selling software and/or software related services to participate in our ~20-minute Online Forrester Research Software Licensing Survey, letting us know about current and future licensing strategies. Of course, all answers are optional and will be kept strictly confidential. We will only use anonymous, aggregated data in our upcoming research report, and interested participants can get a consolidated upfront summary of the survey results if they chose to enter an optional email address in the survey.