Numerix CrossAsset XL and Windows HPC Server 2008 R2

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1 Numerix CrossAsset XL and Windows HPC Server 2008 R2 Faster Performance for Valuation and Risk Management in Complex Derivative Portfolios Microsoft Corporation Published: February 2011 Abstract Numerix, a leading provider of cross-asset analytics for derivative portfolio valuation and risk management, working together with Microsoft to enable Numerix CrossAsset XL with Windows HPC Server 2008 R2 and Windows HPC Services for Excel This highperformance computing (HPC) solution allows financial services professionals from traders and risk managers to insurance actuaries to more efficiently manage their portfolios and assess risk on an interactive and day-to-day basis because the solution provides enhanced accuracy and more timely pricing and risk information. This paper presents benchmark and performance test results for typical derivative portfolio use cases. The test results show that portfolio calculation speed increased almost linearly as more compute nodes were added to a HPC cluster. In terms of compute time, the testing showed the following excellent results: For a portfolio of 10,000 Foreign Exchange (FX) trades, it took minutes to compute results on a standalone desktop with two quad-core processors. Running it on a twonode cluster with one head node and one compute node (two quad-core processors per node) reduced compute time to 12.5 minutes an 88 percent improvement. On a nine-node cluster (two quad-core processors per node), calculation speed for 10,000 FX trades was almost 50 times faster than with a standalone desktop. For a variable annuity Guaranteed Minimum Benefit (GMxB) policy set of 10,000, total compute time was reduced from minutes on a desktop to 2.6 minutes on a 72- core HPC cluster a 98 percent improvement. These faster calculations save large amounts of time. Financial services professionals get the answers they need faster, so they can respond more quickly to changing market dynamics as they manage their derivative portfolios.

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3 Table of Contents Challenges to Managing Complex Derivative Portfolios on a Daily Basis... 1 Risk Management with Numerix and Microsoft High Performance Computing... 1 HPC Performance Testing for Derivative Portfolio Calculations... 2 Test Environment... 2 Use Cases and Test Results... 3 Use Case 1: FX Trader in Numerix CrossAsset XL... 3 Use Case 1 Test Results... 4 Use Case 2: Variable Annuity GMxB Policy Pricing in Numerix CrossAsset XL... 6 Use Case 2 Test Results... 7 Conclusion Resources... 11

4 Challenges to Managing Complex Derivative Portfolios on a Daily Basis Managing risk and valuing complex derivative portfolios on a daily basis is challenging and computationally intensive. Traders, risk managers, and actuaries in capital markets and insurance must have timely and accurate information to assess value and risk. However, they are faced with several major challenges: Choosing between time and accuracy: Traders, risk managers, and actuaries have had to rely on estimates and rough calculations based on stale data. Capturing all derivative trading activity into a common framework with consistent valuations across asset classes has been time-consuming, cumbersome, and error prone. Running risk analysis on large, computationally intensive derivative portfolios and bespoke deal types generally takes too long to provide information that can be used for daily risk management. Market uncertainty, increasing regulatory demands, and new accounting standards (as outlined in Basel II, FAS 133/157, and IAS 39, for example) are creating increased pressure on derivative portfolio managers to establish accurate, timely, and consistent pricing, risk, and reporting measures enterprise-wide. To meet these challenges, financial services professionals need a powerful, highly scalable solution for the pricing, valuation, and risk management of today s most complex derivative portfolios. Risk Management with Numerix and Microsoft High- Performance Computing Currently, many financial services professionals are limited in their ability to perform valuations and assess risk by the computing power of their individual desktops. To increase performance, forward-looking companies are creating solutions that use highperformance computing. Numerix and Microsoft are working together to provide a cost-effective HPC-based solution for managing risk and valuing derivative or variable annuity portfolios. Numerix CrossAsset XL takes advantage of the features of the Windows HPC Server 2008 R2 and Windows HPC Services for Excel solution to access powerful grid-computing capabilities. These tools from Numerix, when coupled with the value of an integrated HPC solution from Microsoft, provide: Rapid unified risk calculations. Accelerated real-time valuations. Improved systems productivity. Interoperability and full transparency for deal definitions. Numerix CrossAsset XL A flexible, Microsoft Excel based platform for structuring, pricing, and analyzing derivative or structured products. Features Grid-computing enabled for parallel Excel computations, with built-in support for Windows HPC Server 2008 R2. Broad instrument support, available as a complete crossasset solution or individual modules. Comprehensive library of singleand multi-factor models and high-performance numerical methods. Hundreds of templates and examples, and a Structuring Wizard for new deal types. Simple payoff scripting language for defining bespoke instruments. Full valuations and Greeks (even for structured products). Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 1

5 HPC Performance Testing for Derivative Portfolio Calculations In this paper, Numerix and Microsoft demonstrate that adding computational capacity significantly improves performance on complex calculations for derivative portfolios. The performance testing was designed to answer the following questions: Does performance improve by using an HPC cluster for portfolio calculations? How much does performance change as the number of cores increases? What is the HPC cluster overhead? Test Environment A series of tests were conducted on a 12-node HPC cluster. Each node was configured identically as shown in Table 1. Each test was run on a standalone node to establish a baseline for standalone desktop performance. The desktop system had two quad-core processors, for a total of eight cores. For cluster performance testing, one of the nodes was designated as the head node, which performed the following tasks: Deployed copies of the test workbook to the rest of the nodes (called compute nodes). Opened and closed Excel on the compute nodes. Hosted the master Excel spreadsheet used for each test. Updated the results in the master spreadsheet. The compute nodes handled the calculations using Excel in server mode (no GUI running) and sent the results back to the head node. Software used in the testing included the following: Numerix CrossAsset XL Windows HPC Server 2008 R2 Windows Services for Excel 2010 Microsoft Office Excel Core HPC Cluster Compute Node Configuration Compute nodes 12 Processors per node Cores per node 8 Total cores in HPC cluster 96 Type of processor 2 quad-core Table 1. HPC cluster compute node configuration Intel Xeon E5345 (8 MB Cache, 2.33 GHz) The performance tests were run two to three times to ensure that the results were consistent. Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 2

6 Use Cases and Test Results Two use cases, each one common to a particular industry or asset class, were tested using the HPC cluster: 1. Foreign Exchange: Commonly traded and semi-exotic deals (Numerix CrossAsset XL FX Trader module). 2. Insurance industry: Variable annuity GMxB policy pricing (Numerix CrossAsset XL). Use Case 1: FX Trader in Numerix CrossAsset XL This use case tested HPC performance on the Numerix CrossAsset XL FX Trader module, which provides an intuitive Excel-based workflow interface for traders to apply sophisticated pricing and risk models to many commonly traded and semi-exotic deals. The CrossAsset XL FX Trader module provides all the building blocks needed to simulate unique portfolio trades, along with pre-built templates to get started quickly. Sets of 1,000, 5,000, and 10,000 trades were conducted with increasing numbers of cores. The following types of trades were tested in this use case: Barrier Digital Barrier European Spot/Forward Touch The tests computed the present value (PV) of each trade, along with the following first and second order Greeks: Delta Delta CCY Gamma Phi Rho Theta Vanna Vega Volga Windows HPC Server 2008 R2 An interoperable HPC solution with a productive development environment for organizations that have not had access to HPC capabilities in the past. Features Seamlessly scale from workstation to cluster by making it possible for users to harness the power of distributed computing through a familiar Windows desktop environment without requiring specialized skills or training. Rapidly develop HPC applications using the Microsoft Visual Studio development system, which provides a comprehensive parallel programming environment. Improve systems administration and cluster interoperability by simplifying the overall deployment, administration, and management over the entire system lifetime, while ensuring interoperability with existing systems infrastructure. Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 3

7 Use Case 1 Test Results Cluster vs. Desktop Performance Testing showed that performance improved significantly when trade calculations were run on an HPC cluster as opposed to a standalone desktop. As shown in Figure 1, the 10,000 trade set exhibited a substantial increase in speed as more cores were added. With as few as 32 cores, calculation speed was 27 times faster than on the desktop. With 72 cores, calculation speed was almost 50 times faster. Figure 1. FX trade calculation speed up on an HPC cluster relative to a standalone desktop From a total compute time perspective, simply using a two-node cluster with eight cores to calculate large trade sets resulted in dramatic improvements in compute time. As Table 2 shows, it took minutes to compute the results of 10,000 FX trades on a standalone desktop with two quad-core processors. Running the same calculations on a two-node cluster with a head node and one compute node, each with two quadcore processors, took only 12.5 minutes an 88 percent improvement. The 5,000 and 1,000 trade sets experienced similar Total Compute Time (minutes) FX trade count 10,000 5,000 1,000 Desktop Cluster w/8 cores Improvement 88% 86% 81% Table 2. Improvement in compute time for FX trade sets on a two-node HPC cluster versus a desktop Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 4

8 improvements in compute time at 86 and 81 percent, respectively. These significant improvements in compute time are due to Excel calculation being spread across multiple cores and multiple machines that operate in parallel. Cluster Performance In all of the tests, larger calculation sets experienced much greater performance gains than smaller sets as cores increased (Figure 2). Calculation times dropped dramatically for the 5,000 and 10,000 trade sets as up to 32 cores were added. Although smaller, the performance gains from 32 to 72 cores were still considerable. For example, running 60 portfolios with 10,000 trades each on 72 cores versus 32 cores would save almost two hours in computing time (1.7 minutes less per portfolio), giving financial services professionals vital information much faster. Figure 2. HPC cluster performance gains based on total compute time in minutes for FX trades The long, tapering performance tail shown in Figure 2 was common in all use cases. Two primary factors explain the decrease in HPC cluster performance after 32 cores: Bandwidth between the head node and the compute nodes As more cores send data back to the head node, bandwidth is consumed very quickly, creating a bottleneck for incoming data coming into the head node. Also, the head node handles workbook deployment to the compute nodes. In some cases, the head node may still be deploying workbooks when the first results begin to come in. This two-way traffic decreases available bandwidth to receive results from the compute nodes. Though there are techniques for improving overhead, such as shared memory, none were employed here. The head node s ability to process results coming in from the compute nodes The master Excel spreadsheet resides on the head node. Performance may be constrained by Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 5

9 how quickly the incoming results can be aggregated and properly placed in the master spreadsheet. The reduction in compute time for large trade sets between eight and 32 cores is very positive. For 10,000 FX trades, the compute time dropped from 12.5 minutes on eight cores to 3.7 minutes on 32 cores. Similar performance gains can be extrapolated for much larger trade sets. Cluster Overhead As cores increased, HPC cluster overhead activities not related to calculations also increased. However, larger sets of trade calculations exhibited less overhead than smaller sets (Figure 3). For example, a small 1,000 trade set running on 72 cores spent 53 percent of the total computing time on overhead activities. In contrast, the 10,000 trade set running on 72 cores only spent 23 percent of the total computing time on cluster overhead. The trend shown here suggests that the most efficient use of an HPC cluster is to run large sets of calculations on fewer cores, thus reducing overhead. Figure 3. Percent of total computing time spent on HPC cluster overhead during FX trade calculations Use Case 2: Variable Annuity GMxB Policy Pricing in Numerix CrossAsset XL This use case focuses on pricing variable annuity GMxB policies. These standard insurance derivative products have many options and must rely on pricing models and computational algorithms to create accurate prices for the policies. The data used in this case came from the Numerix CrossAsset XL GMxB Excel workbook, which contains millions of policies with many different variables. The data sets tested here represent a well-defined sample of policies. The tests calculated the present value of each policy in the set using 1,000 Monte Carlo paths. The model used for each asset was: Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 6

10 Hybrid: [HW2 (USD) + Heston (SPX) + Heston (RTY) + Credit (CDX) ] + Actuarial data (Mortality/Lapse/Withdrawal Tables) Performance was measured as increasing numbers of cores were used to run the calculations on the HPC cluster. Use Case 2 Test Results Cluster vs. Desktop Performance As with the FX trades, larger calculation sets experienced much greater performance gains than smaller sets when run on an HPC cluster. Compared to a standalone desktop, the 10,000 policy calculation was 29.5 times faster on 32 cores and 53.7 times faster on 72 cores (Figure 4). Figure 4. GMxB policy calculation speed up on an HPC cluster relative to a standalone desktop The 1,000 policy set exhibited smaller performance gains, running 13.2 times faster on 72 cores than on a desktop. Given the results for the 1,000 policy set, it is clear that the larger the calculation set, the better the performance on an HPC cluster. Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 7

11 Total compute time for the 10,000 policy set on a desktop was minutes, or two hours 19 minutes. When run on 72 cores in an HPC cluster, it took only 2.6 minutes. Similar performance gains happened with the smaller policy sets (Table 3). Total Compute Time (Minutes) Variable annuity policy count 10,000 5,000 1,000 Desktop Cluster Performance In all of the policy pricing tests, the larger Cluster w/72 cores Improvement % % % calculation sets experienced greater Table 3. Improvement in compute time for GMxB policy sets on performance gains than smaller sets as cores a two-node HPC cluster versus a desktop increased (Figure 5), especially as up to 32 cores were added. The performance gains from 32 to 72 cores were smaller but still created important time savings for situations where many portfolios are calculated. Figure 5. HPC cluster performance gains based on total compute time in minutes for GMxB policies These results are very similar to the performance gains seen in the FX trades testing, as are the smaller performance gains above 32 cores. Improvements in compute time for large trade sets between eight and 32 cores remained very positive for the GMxB policies: For the 10,000 policy set, compute time dropped from 16.5 minutes on eight cores to 4.7 minutes on 32 cores. Based on these findings, similar performance gains can be extrapolated for much larger policy sets. Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 8

12 Cluster Overhead The HPC cluster overhead results for GMxB pricing calculations mirrored the results from the FX trades testing (Figure 6). The trend shown here reiterates the finding that, in terms of reducing overhead, the most efficient use of an HPC cluster is to run large sets of calculations on fewer cores. The increase in overhead as more cores are added can most likely be explained by the same factors that reduced cluster performance with more cores, as explained in Use Case 1: Bandwidth between the head node and the compute nodes to receive results. The head node s ability to process results coming in from the compute nodes. Figure 6. Percent of total computing time spent on HPC cluster overhead during GMxB policy pricing calculations Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 9

13 Conclusion The test results presented in this paper clearly demonstrate the value that HPC brings to complex derivative portfolio management. Numerix and Microsoft together provide a powerful, highly scalable solution that helps financial services professionals to more efficiently and accurately price, value, and manage risk based on available information. Testing also clearly shows that adding more cores to an HPC cluster significantly increases performance: An eight core cluster ran 10,000 FX trades in only 12.5 minutes. Calculating the present value for 10,000 GMxB policies took only 2 minutes using 72 cores. Using an HPC solution that is based on Numerix CrossAsset XL and Windows HPC Server 2008 R2 with Windows HPC Services for Excel lets traders, risk managers, and actuarial professionals access the most powerful grid computing capabilities available to the financial industry today. This also helps to solve common challenges by: Providing more timely and accurate information for daily risk management. Capturing relevant derivative trading activity into a common framework with enhanced consistency of valuations across asset classes. Significantly reducing the time needed to run risk analyses on large, computationally intensive derivative portfolios and bespoke deal types. Meeting regulatory demands and new accounting standards for accurate, timely, and consistent pricing, risk, and reporting measures enterprise-wide. Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 10

14 Resources For more information, visit the following resources: Numerix CrossAsset XL Windows HPC Server 2008 R2 Benchmark Results for Windows HPC Server 2008 R2 and Numerix CrossAsset XL 11