Developers may be interested to know that this month RAPIDS Accelerator for Apache Spark v21.10 has been made available and the open source project is now available to download. The latest release includes a wealth of community requests that are ideally suited for GPU acceleration. Such as new performance improvements and cost savings as well as new I/O and nested datatype Qualification and Profiling tool features together with updates to the spark-examples repository.
The development team has also announced that upcoming versions will introduce support for 128-bit decimal datatype, inference support for the Principle Component Analysis algorithm and additional nested data type support for multi-level struct and maps. As well as MIG support for NVIDIA Ampere Architecture based GPUs (A100/A30) which can help improve throughput on running multiple spark jobs with A100. As always, we want to thank all of you for using RAPIDS Accelerator for Apache Spark and we look forward to hearing from you. Reach out to us on GitHub and let us know how we can continue to improve your experience using RAPIDS Accelerator on Apache Spark.
RAPIDS Accelerator for Apache Spark
“RAPIDS Accelerator for Apache Spark is growing at a great pace in both functionality and performance. Standard industry benchmarks are a great way to measure performance over a period of time but another barometer to measure performance is to measure performance of common operators that are used in the data preprocessing stage or in data analytics. Most Apache Spark users are aware that Spark 3.2 was released this October. The v21.10 release has support for Spark 3.2 and CUDA 11.4. In this release, we focused on expanding support for I/O, nested data processing, and machine learning functionality. RAPIDS Accelerator for Apache Spark v21.10 released a new plug-in jar to support machine learning in Spark. “
“In addition to the plug-in, multiple new features were also added to RAPIDS Accelerator for Apache Spark’s Qualification and Profiling tool. The Qualification tool can now report the different nested datatypes and write data formats present. It now also includes support for adding conjunction and disjunction filters, and filter based Regular Expressions and usernames. The Qualifications tool is not the only one with new tricks: the Profiling tool now provides structured output format and support to scale and run a large number of event logs.”
For more information on the new features and additions to RAPIDS Accelerator for Apache Spark v21.10 jump over to the official NVIDIA website by following the link below.
Source : NVIDIA
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