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Accelerating Apache Spark with FPGAs: A Case Study for 10TB TPCx HS Spark Benchmark Acceleration

408 views · Published 10 October 2018 · 29:51 · Indexed 30 October 2026

Channel: Databricks · 2018 · Science & Technology

In the last few years, RNNs have achieved significant success in modeling time series and sequence data, in particular within the speech, language, and text domains. Recently, these techniques have been begun to be applied to session-based recommendation tasks, with very promising results. This talk explores the latest research advances in this domain, as well as practical applications. I will provide an overview of RNNs, covering common architectures and applications, before diving deeper into RNNs for session-based recommendations. I will pay particular attention to the challenges inherent in common personalization tasks and the specific adjustments to models and optimization techniques required for success.

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Accelerating Apache Spark with FPGAs: A Case Study for 10TB TPCx HS Spark Benchmark Acceleration

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