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Can my code be accelerated by an RPU? Part 2: Verticals


In our previous post, we introduced you to Quside’s Randomness Processing Unit (RPU) and outlined how you could use it to accelerate your stochastic workloads, whatever type they may be. In this post, we will explore different business verticals and provide some examples of specific workloads that can be accelerated efficiently with an RPU so that you can make the most of this device and its ecosystem.


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In summary, if you work in any of these industries and are looking for ways to improve your performance, differentiation, accuracy, or work scope, consider the benefits of using an RPU to accelerate your stochastic workload. By exploring the RPU and its ecosystem, you could gain valuable insights and stay ahead of the competition in any of these fast-paced industries.

José Ramon Martínez

José Ramon Martínez

Leader of the computing activities

He got his BSc in Physics from the UCM (Madrid); his MSc in Photonics from the UPC-UB-UAB (Barcelona); and his Ph.D. in Photonics from ICFO, where he worked at the Nanophotonics Theory Group. His research focused on Computational Physics in Nanophotonic systems, publishing 10+ articles in high-profile journals and developing various advanced high-performance computing systems.

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