Understanding deal and portfolio risk and capital requirements is a computationally expensive process that requires the execution of multiple financial forecasting models every day and in often in real time. This post describes how it works …
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We worked with our financial services customers to develop an open-source, scalable, cloud-native, high throughput computing solution on AWS — AWS HTC-Grid. HTC-Grid allows you to submit large volumes of short and long running tasks and …
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Combinatorial Optimization is one of the most popular fields in applied optimization, and it has various practical applications in almost every industry, including both private and public sectors. Examples include supply chain optimization, …
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Many shared file systems are used in supporting read-intensive applications, like financial backtesting. These applications typically exploit copies of datasets whose authoritative copy resides somewhere else. For small datasets, in-memory …
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The Financial Services industry makes significant use of high performance computing (HPC) but it tends to be in the form of loosely coupled, embarrassingly parallel workloads to support risk modelling. The infrastructure tends to scale out …
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HPC in Financial Services is interesting for a lot of reasons that have nothing to do with banking. It’s an embarrassingly parallel workload, typically made up from zillions of short’ish jobs (seconds to minutes). And the …
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Batch processing is a common need across varied machine learning use cases such as video production, financial modeling, drug discovery, or genomic research. The elasticity of the cloud provides efficient ways to scale and simplify batch …
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