Release Notes
Abstract
Hardware and software requirements for installing Machine Learning for IBM z/OS on IBM z.
Content
Machine Learning for IBM z/OS Enterprise Edition is an enterprise machine learning solution that runs on IBM® Z. You can run ML for z/OS as a stand-alone solution or infuse it into your enterprise AI capability as a scalable platform.
Machine Learning for IBM z/OS Core Edition is a lightweight version of MLz providing the essential services that are REST-API-based for machine learning operations including online scoring capabilities on IBM Z. Primarily aiming for AIOps use cases through AI solutions offered by IBM or IBM partners.
What's New in version 3.2.0
- Support multi-user model development environment leveraging JupyterHub.
- Enhanced trustworthy AI capability through improved monitoring configuration and intuitive visualization of explainability results.
- New capability in the Trustworthy AI component to continuously monitor and detect drift in the data distribution of model inputs and outputs, ensuring the model remains accurate and reliable.
- Support multi-class classification model scoring leveraging the on-chip AI accelerator of IBM z16 through Snap ML.
- Utilize Spark libraries as external dependencies for the scoring server to reduce the installation footprint.
- Support IBM Semeru Runtime Certified Edition for z/OS, Version 17, the latest release of Java SDK on z/OS.
- Support for z/OS Spark 3.5.0.
- Support IBM Z Deep Learning Compiler (IBM zDLC) 4.2.0 for ONNX model compilation and scoring.
- Provide the up to date machine learning support for AI Python packages on z/OS.
- Support multi-class classification model scoring leveraging the on-chip AI accelerator of IBM z16 through Snap ML.
- Utilize Spark libraries as external dependencies for the scoring server to reduce the installation footprint.
- Support IBM Semeru Runtime Certified Edition for z/OS, Version 17, the latest release of Java SDK on z/OS.
- Support for z/OS Spark 3.5.0.
What's New in version 3.1.0
- New ability to explain and understand the decisions made by AI models utilizing the MLz built-in Trustworthy AI capabilities.
- Integrate Snap ML library for high speed training and inferencing of popular machine learning models on z/OS, leveraging the on-chip AI accelerator of IBM z16.
- Provide the up-to-date machine learning support for Apache Spark and AI Python packages on z/OS.
- Improve the experience of product configuration and offer different configuration options through WMLz Configuration Tool for both WMLz Core edition and WMLz Enterprise edition.
- Incorporate the inferencing support for Watson Core time-series models.
- Provide the built-in metadata database option for repository service.
- Integrate the Jupyter Notebook server for model training to leverage the integrated Apache Spark runtime and Python runtime on z/OS.
- Enhance the documentation for WMLz services REST APIs.
- zIIP eligibility for Python model training and scoring.
- AT-TLS support for configuration tool, scoring service and Jupyter notebook server for strengthened TLS communication between WMLz services and your client applications.
- Enhanced error handling of the CICS and WOLA scoring interfaces, which enable COBOL applications to retrieve the scoring error code and error message through pre-defined output variables.
- Make the WOLA server name customizable, which enables a flexible deployment and application management for a scoring cluster configuration with instances across multiple LPARs.
- Message ID and content standardization for services and UI.
- Support IBM Z Deep Learning Compiler (IBM zDLC) 4.1.1 for ONNX model compilation and scoring.
- Support z/OS Spark 3.2.4.2.
Maintenance Level
MLz maintenance level
|
APAR/PTF for IBM Z |
Machine Learning for IBM z/OS Core Edition V3.1
|
2024 Jun
APAR PH61497/PTF UI97356
APAR PH61549/PTF UI97357
APAR PH61550/PTF UI97358
2023 Dec
APAR PH58052/PTF UI94919
APAR PH58544/PTF UI94920
APAR PH58545/PTF UI94921
2023 Oct
APAR PH57527/PTF UI94159
APAR PH57746/PTF UI94160
APAR PH57747/PTF UI94161
2023 Sep
APAR PH56809/PTF UI93788
APAR PH56840/PTF UI93789
APAR PH56841/PTF UI93790
2023 Aug
APAR PH55628/PTF UI93000
APAR PH55968/PTF UI93001
APAR PH55969/PTF UI93002
2023 Jun
APAR PH55059/PTF UI92254
|
Machine Learning for IBM z/OS Enterprise Edition V3.1
|
2024 Jun
APAR PH61497/PTF UI97359
APAR PH61549/PTF UI97360
APAR PH61550/PTF UI97361
2023 Dec
APAR PH58052/PTF UI94922
APAR PH58544/PTF UI94923
APAR PH58545/PTF UI94924
APAR PH58546/PTF UI94925
APAR PH58547/PTF UI94926
2023 Oct
APAR PH57527/PTF UI94162
APAR PH57746/PTF UI94163
APAR PH57747/PTF UI94164
2023 Sep
APAR PH56809/PTF UI93791
APAR PH56840/PTF UI93792
APAR PH56840/PTF UI93793
2023 Aug
APAR PH55628/PTF UI93003
APAR PH55821/PTF UI93004
APAR PH55968/PTF UI93005
2023 Jun
APAR PH55059/PTF UI92255
|
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Document Information
Modified date:
26 June 2024
UID
ibm17003489