Benchmarks: Intel Xeon Phi vs. NVIDIA Tesla GPU – Second Round

In a previous blog post, we compared Intel’s Xeon Phi and an NVIDIA Tesla GPU for Monte-Carlo financial applications. Although Monte-Carlo simulations is the most commonly used technique in financial analytics (we estimate around 70%), there are other numerical methods in use. Finite difference solvers are another important method that finds applications in all kinds of instrument pricing algorithms, while lattice-based schemes or spectral methods also feature. In this post, we’ll benchmark the two competing hardware platforms for a Partial Differential Equation (PDE) solver, using an explicit finite difference method.

Intel Xeon Phi 7120P PCIe Card

Intel Xeon Phi 7120P

NVIDIA Tesla K40 GPU Accelerator


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White Paper: xVA – Coping with the Tsunami of Compute Load

We’ve just published a new white paper which covers how to cope with the computational complexity involved in calculating various valuation adjustments, such as Credit Valuation Adjustment (CVA), Debit Valuation Adjustment (DVA), and Funding Valuation Adjustment (FVA).

These adjustments are commonly referred to as xVA. This white paper gives an overview of the different xVA adjustments, shows
how they are typically computed, and outlines where the computational complexities lie. We give recommendations on how to achieve high performance, portability, and scalability for centralised in-house xVA implementations. We show how, by careful software design, we can easily harness, not only the power of multi-core CPUs, but also accelerator co-processors such as graphic processing units (GPUs) and the Intel Xeon Phi.

You can download the paper here.

Xcelerit SDK version 2.5 Released

Xcelerit SDK, Box

Today Xcelerit announced the release of version 2.5 of its SDK, increasing performance significantly, dramatically simplifying the user experience, and adding support for Visual Studio 2012 and Windows 8. A complete list of the updates and new features can be found in the Release Notes shipped with the package.

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Xcelerit goes to College

Oxford University

Last month, Xcelerit presented at the UK Many-Core Developer conference in Oxford, UK. The conference was held in the new Andrew Wiles building, named after Oxford’s distinguished mathematician who is most famous for proving Fermat’s last theorem. It’s goal was to strengthen the UK’s expertise in many core computing and Xcelerit CTO, Jorg Lotze, was part of an accomplished panel of speakers from Oxford, Imperial College, London and Bath Universities. Industry was also well represented, with speakers from innovative hardware manufacturers like ARM featured alongside niche specialist like Ridgeway Kite Software.

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Benchmarks: NVIDIA Tesla K40 vs. K20X GPU

NVIDIA freshly released their new flagship Tesla GPU, the Tesla K40. This GPU features more memory, higher clock rates, and more CUDA cores than the previous top-end card, the K20X. But what performance improvements can we expect for financial applications? We’ve put the new card to the test and compared it to the K20X using a Monte-Carlo LIBOR swaption portfolio pricer, a real-world financial algorithm that we’ve already used in other benchmarks.

NVIDIA Tesla K40 GPU Accelerator

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Back from the Fixed Income Conference in Munich

Xcelerit were represented at last week’s Fixed Income Conference in Munich’s Sofitel Bayerpost. We had a busy display stand in the hotel concourse and our CTO Jorg Lotze gave a presentation revealing some of our CVA implementation secrets. This session was very well attended despite the late dinner at the Augustiner Keller on the evening before.

Stand Activity

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Benchmarks: Ivy Bridge vs. Sandy Bridge for Financial Analytics

Intel just released its new Ivy-Bridge server processor line (Xeon E5 v2 series), promising significant performance gains over previous-generation Sandy-Bridge processors. In this post, we will compare the two generations for a financial application – a Monte-Carlo LIBOR Swaption Porfolio pricer.

Ivy-Bridge Processor Die

Ivy-Bridge Processor Die

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Xcelerit Takes Monte-Carlo to New York City

On September 25th, Xcelerit in association with the Wilmott Forum delivered a briefing on Monte-Carlo Simulations using GPUs. The event was heavily oversubscribed and the audience of quants and other financial industry specialists listened as Dongsheng Lu, Managing Director and Head of Quantitative Research at BNY Mellon explained the complexity and challenges behind CVA and FVA calculations. His presentation was followed by John Ashley of NVIDIA, who explained how GPUs could meet the computational challenges. The event concluded with a presentation by Xcelerit’s Hicham Lahlou, who explained how heavy CVA calculations could be approached in software and how existing code can easily be retargeted to many different accelerator platforms.

The Tao of CVA

Xcelerit Explains the Joy of GPUs to Wall Street

On September 26th, Xcelerit’s New York tour continued with a seminar entitled “The Joy of GPUs: Awesome Compute Power for Banks on Budget”. The event was jointly held with IBM and NVIDIA and the venue was IBM’s Wall Street Center of Excellence on Madison Avenue. The seminar was opened by Dave Weber, IBM’s program director at the Wall Street Center. He painted a picture of IBM’s experience deploying advanced server hardware in many different financial industry sites. Jeff Sporn from NVIDIA elaborated on his company’s experience in deploying GPU hardware in a financial setting. Finally Hicham Lahlou from Xcelerit described how to “make Financial Applications Sing on GPUs”.


Phi vs. Kepler: The Interview

Following on from our recent blog post detailing our comparison of Intel Xeon Phi with NVIDIA Tesla in financial applications, Xcelerit’s CTO Jorg Lotze was interviewed by HPC wire. You can listen and read about it here