Transparent GPU Exploitation on Apache Spark (Dr. Kazuaki Ishizaki & Madhusudanan Kandasamy)
144 views · Published 27 September 2018 · 32:51 · Indexed 30 September 2026
Channel: Databricks · 2018 · Science & Technology
Dr. Kazuaki Ishizaki, a research staff member at IBM Research, and Madhusudanan Kandasamy, a Senior Technical Staff Member at IBM, explain how the Graphics Processing Units (GPUs) are becoming popular for achieving high performance of computation intensive workloads. The GPU offers thousands of cores for floating point computation. This is beneficial to machine learning algorithms that are computation intensive and are parallelizable on the Spark platform. While the current execution strategy of Spark is to execute computations for the workload across nodes, only CPUs on each node execute computation.. Learn more here: https://databricks.com/session/transparent-gpu-exploitation-on-apache-spark Article you might like: https://databricks.com/session/scaling-genomics-pipelines-in-the-cloud About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: https://databricks.com/product/unified-data-analytics-platform Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc/ Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-named-leader-by-gartner
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