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Interested in developing COBOL Applications that run in Microsoft Azure? Review the following documentation:https://www.microfocus.com/documentation/enterprise-developer/ed80/ED-VS2022/GUID-E459A5FF-B996-4F9C-89B4-3C2AFCA98FE5.html#EnterpriseDeveloper#SupportTips/KnowledgeDocs

Hi, VS Enterprise 2019 (v.16.11.5) VC 7.0.00248 SN I am compiling one of my .pco files and I get the following Output: ... error COBCH0641 : '.' missing following procedure name declaration, or unrecognized verb ... In the Error List I get loads of errors (strangely, other .pco files appear also) When I doubleclick on the error in the Output window, VS puts me on the last line (2576) of the program. I can see the red ‘wave’ on line 2576 but that is not helping me. I also tried to Show All Copybooks but the red ‘wave’ is still on line 2576 . When I doubleclick on the error in the Error List window, VS puts me on line 1753 for some reason. I never touched the .pco file, I only changed 1 .cpy and 2 .cob files. These .cpy and .cob files are used in other programs and they compile fine. How can I get to the exact line where the compile error occurs ? I really don’t see what is happening here. Can anybody help me ? Thanks! Kr, Stefan

My goal is to access a method in C++ or C# .dll file. I have performed the following in C++,however unable to get the expected output. 1. Created a C++ Sample.dll to display "Hello World" on the console.2. Release Sample.dll and Sample.lib into my COBOL working folder.3. Accessed the .dll and the method from AcuCobol program using CALL.4. Didn't show any exception while accessing the .dll or the method.5. However "Hello world" is not getting displayed.6. Also, how to pass a value into a function in the .dll and return the processed value. Please advise. Thanks, Aji Cherian

v1.11.2 Releasing RocketCE Packages with OpenCE v1.11.2 v1.10.0 Releasing RocketCE Packages with OpenCE v1.10.0 v1.9.1 Releasing RocketCE Packages with OpenCE v1.9.1 v1.8.1 Releasing RocketCE Packages with OpenCE v1.8.1 v1.8.0 Releasing RocketCE Packages with OpenCE v1.8.0 v1.7.0 Releasing RocketCE Packages with OpenCE v1.7.0 v1.6.0 Releasing RocketCE Packages with OpenCE v1.6.0 v1.5.1 Releasing RocketCE Packages with OpenCE v1.5.1 v1.5.0 Releasing RocketCE Packages with OpenCE v1.5.0 v1.4.1 Releasing RocketCE Packages with OpenCE v1.4.1  v1.3.1 Releasing RocketCE Packages with OpenCE v1.3.1 ------------------------------Rajesh NukalaRocket Internal - All Brands------------------------------

Does anyone have a sample COBOL program that can open COM1: serial port#COBOL

As part of this Rocket provides the AI/ML conda packages and GPU Operator for Power machines.The RocketCE conda packages are build and supported for Power 9 and Power 10 with ppc64le architecture. These packages are installed into a conda environment so after installation is complete, the frameworks are ready for use. Presently these packages are available in RocketCE conda channel.Note: Access and availability to this data is subject to the community and can change at any time.We are releasing RocketCE packages based on OpenCE v1.6.0.To know more about RocketCE and the various packages released with OpenCE1.6.0 please use the appropriate links below. RocketCE Conda for download and deployment of machine learning open source component builds on IBM Power RocketCE System Requirements Releasing RocketCE Tensorflow v2.8.0 with OpenCE v1.6.0 Releasing RocketCE Pytorch v1.10.2 with OpenCE v1.6.0 Releasing RocketCE OnnxRuntime v1.11.0 with OpenCE v1.6.0 Releasing RocketCE Xgboost v1.5.2 wit

Are any fixes required to run on a z16?  I cannot find any documentation on the Rocket site.

Since version 8.1.3, the definitive sample ZDDOPTS parameter members have been shipped with the associated user interfaces to which they relate, i.e. ChangeMan ZDD and ChangeMan ZMF for Eclipse (ZMF4ECL). We finally stopped shipping these sample members with the ZMF Server and/or Sernet (i.e. mainframe) software in 8.2 Patch 1. So, how can the sample ZDDOPTS members now be accessed?- For ZDD, the sample members can be found in the Samples\ZddOpts subdirectory of the ChangeMan ZDD client installation directory. For example, the C:\Program Files\Micro Focus\ChangeMan ZDD\Samples\ZddOpts folder.- For ZMF4ECL, the sample ZDDOPTS members are shipped in the ChangeMan ZMF Eclipse Samples (ChangeMan ZMF4ECL Samples) plugin, which is supplied as a part of the ZMF4ECL Update Site. After installing this plugin, the sample members can be extracted to the local file system using the eclipse workbench File – Export option and selecting ChangeMan ZMF4ECL – ZDDOPTS Sample Files. #ZMF4ECL#Clientpack#Ch

I'm trying to import email text into the database, for some incoming emails I'm getting the above error on the store of the text data. Is there any intelligent way to scan for which characters are objected to so I can then make decisions about translating/ditching them? ------------------------------Iain SharpHead of Technical ServicesPci Systems LtdSheffield GB------------------------------

Hello all, wondering if anyone had any luck uploading to Amazon S3 using UniBasic/UniData.The requirement is to call Amazon S3 HTTP REST API directly in UniBasic, using AWS Signature Version 4. Are there any samples out there we can use?Thanks------------------------------Pedro RochaRunnerTechBoca Raton FL US------------------------------

As part of this Rocket provides the AI/ML conda packages and GPU Operator for Power machines.The RocketCE conda packages are build and supported for Power 9 and Power 10 with ppc64le architecture. These packages are installed into a conda environment so after installation is complete, the frameworks are ready for use. Presently these packages are available in RocketCE conda channel.Note: Access and availability to this data is subject to the community and can change at any time.We are releasing RocketCE packages based on OpenCE v1.5.1.To know more about RocketCE and the various packages released with OpenCE1.5.1 please use the appropriate links below. RocketCE Conda for download and deployment of machine learning open source component builds on IBM Power RocketCE System Requirements Releasing RocketCE Pytorch v1.10.1 with OpenCE v1.5.1 Knowing about Matrix-multiply assist (MMA) capabilities in Power 10 systems Useful Conda Commands ------------------------------Rajesh NukalaRocket Int

Overview  ONNX Runtime is a cross-platform inference and training machine-learning accelerator.  ONNX Runtime is an accelerator for machine learning models with multi-platform support and a flexible interface to integrate with hardware-specific libraries. ONNX Runtime can be used with models from PyTorch, Tensorflow/Keras, TFLite, scikit-learn, and other frameworks.   This release of RocketCE is based on Release OpenCE v1.6.0 and it includes ONNX Runtime v1.11.0.  These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le.    CPU Support  RocketCE includes CPU only variant of ONNX Runtime which is built without GPU support. This inclusion allows for training and inferencing to be done on Power 9 and Power 10 systems that do not have GPUs, or on systems where you want to train and inference without using the GPUs.  GPU Support&nbs

Overview  TensorFlow is an open source library to help you develop and train machine learning models.   RocketCE includes several packages from the TensorFlow ecosystem and these packages are available in channel rocketce of anaconda.org.   First release of RocketCE is based on OpenCE Release v1.6.0. In this version of RocketCE, there is TensorFlow 2.8.0.  These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le.  CPU Support  RocketCE includes a version of TensorFlow built without GPU support. This inclusion allows for training and inferencing to be done on Power 9 and Power 10 systems that do not have GPUs, or on systems where you want to train and inference without using the GPUs.   GPU Support  This version of Tensorflow will have support for GPU based operations. This can be used in Power 9 systems.   Installation instructions  CPU Only Variant  To install Tensorflow built for CPU support run the following command: conda install -c rocketce ten

Overview  XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible, and portable. It implements machine learning algorithms under the Gradient Boosting framework.   This release of RocketCE is based on Release OpenCE v1.6.0 and it includes XGBoost 1.5.2.  These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le.    CPU Support  RocketCE includes CPU only variant of XGBoost which is built without GPU support. This can be used in Power 9 and Power 10 systems that do not have GPUs, or on systems where you want to train and inference without using the GPUs.    GPU Support  This version of XGBoost will have support for GPU based operations. This can be used in Power 9 systems.    Installation instructions  CPU Variant  To install XGBoost of CPU variant, un one of the

Overview  RocketCE Pytorch includes support for IBM's Distributed Deep Learning (DDL).   This version of Pytorch will have the support of matrix-multiply assist (MMA) which was introduced in Power 10.  This release of RocketCE is based on Release OpenCE v1.6.0 and it includes Pytorch 1.10.2.  These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le.     CPU Support  The CPU-only variant of Pytorch is built without GPU and CUDA support. It has a smaller installation size, and omits features that would require a GPU. This can be used in both Power 9 and Power 10 systems.   GPU Support  This version of Pytorch will support GPU based operations. This can be used in Power 9 systems.    Installation instructions  CPU Variant  To install pytorch built for CPU support run the follo

have three of these error messages this morning.   Guessing it has something to do with my enabling callx?unix_GetUserLogonMode [82] Your system privilege level is not sufficient for this statement.Both users have sys1 level set.Thanks for any help in understanding the error message.Craig

Overview  RocketCE Pytorch includes support for IBM's Distributed Deep Learning (DDL).   This version of Pytorch will have the support of matrix-multiply assist (MMA) which was introduced in Power 10.  This release of RocketCE is based on Release OpenCE v1.5.1 and it includes Pytorch 1.10.1.  These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le.     CPU Support  The CPU-only variant of Pytorch is built without GPU and CUDA support. It has a smaller installation size, and omits features that would require a GPU. This can be used in both Power 9 and Power 10 systems.   GPU Support  This version of Pytorch will support GPU based operations. This can be used in Power 9 systems.    Installation instructions  CPU Variant  To install pytorch built for CPU support run the follo

As part of this Rocket provides the AI/ML conda packages and GPU Operator for Power machines.The RocketCE conda packages are build and supported for Power 9 and Power 10 with ppc64le architecture. These packages are installed into a conda environment so after installation is complete, the frameworks are ready for use. Presently these packages are available in RocketCE conda channel.Note: Access and availability to this data is subject to the community and can change at any time.We are releasing RocketCE packages based on OpenCE v1.5.0.To know more about RocketCE and the various packages released with OpenCE1.5.0 please use the appropriate links below. RocketCE Conda for download and deployment of machine learning open source component builds on IBM Power RocketCE System Requirements Releasing RocketCE Tensorflow v2.7.0 with OpenCE v1.5.0 Releasing RocketCE Pytorch v1.10.0 with OpenCE v1.5.0 Releasing RocketCE OnnxRuntime v1.10.0 with OpenCE v1.5.0 Releasing RocketCE Xgboost v1.5.1 wit

As part of this Rocket provides the AI/ML conda packages and GPU Operator for Power machines.The RocketCE conda packages are build and supported for Power 9 and Power 10 with ppc64le architecture. These packages are installed into a conda environment so after installation is complete, the frameworks are ready for use. Presently these packages are available in RocketCE conda channel.Note: Access and availability to this data is subject to the community and can change at any time.We are releasing RocketCE packages based on OpenCE v1.3.1.To know more about RocketCE and the various packages released with OpenCE1.3.1 please use the appropriate links below. RocketCE Conda for download and deployment of machine learning open source component builds on IBM Power RocketCE System Requirements Getting started with TensorFlow Getting Started with Pytorch Getting Started with ONNX Runtime Getting Started with XGBoost Knowing about Matrix-multiply assist (MMA) capabilities in Power 10 systems Usefu

Overview  XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible, and portable. It implements machine learning algorithms under the Gradient Boosting framework.   This release of RocketCE is based on Release OpenCE v1.5.0 and it includes XGBoost 1.5.1.  These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le.    CPU Support  RocketCE includes CPU only variant of XGBoost which is built without GPU support. This can be used in Power 9 and Power 10 systems that do not have GPUs, or on systems where you want to train and inference without using the GPUs.    GPU Support  This version of XGBoost will have support for GPU based operations. This can be used in Power 9 systems.    Installation instructions  CPU Variant  To install XGBoost of CPU variant, un one of the

Overview  ONNX Runtime is a cross-platform inference and training machine-learning accelerator.  ONNX Runtime is an accelerator for machine learning models with multi-platform support and a flexible interface to integrate with hardware-specific libraries. ONNX Runtime can be used with models from PyTorch, Tensorflow/Keras, TFLite, scikit-learn, and other frameworks.   This release of RocketCE is based on Release OpenCE v1.5.0 and it includes ONNX Runtime v1.10.0.  These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le.    CPU Support  RocketCE includes CPU only variant of ONNX Runtime which is built without GPU support. This inclusion allows for training and inferencing to be done on Power 9 and Power 10 systems that do not have GPUs, or on systems where you want to train and inference without using the GPUs.  GPU Support&nbs

Overview  RocketCE Pytorch includes support for IBM's Distributed Deep Learning (DDL).   This version of Pytorch will have the support of matrix-multiply assist (MMA) which was introduced in Power 10.  This release of RocketCE is based on Release OpenCE v1.5.0 and it includes Pytorch 1.10.0.  These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le.     CPU Support  The CPU-only variant of Pytorch is built without GPU and CUDA support. It has a smaller installation size, and omits features that would require a GPU. This can be used in both Power 9 and Power 10 systems.   GPU Support  This version of Pytorch will support GPU based operations. This can be used in Power 9 systems.    Installation instructions  CPU Variant  To install pytorch built for CPU support run the follo

Overview  TensorFlow is an open source library to help you develop and train machine learning models.   RocketCE includes several packages from the TensorFlow ecosystem and these packages are available in channel rocketce of anaconda.org.   First release of RocketCE is based on OpenCE Release v1.5.0. In this version of RocketCE, there is TensorFlow 2.7.0.  These packages are supported for both Power 9 and Power 10 Systems of IBM with linux-ppc64le.  CPU Support  RocketCE includes a version of TensorFlow built without GPU support. This inclusion allows for training and inferencing to be done on Power 9 and Power 10 systems that do not have GPUs, or on systems where you want to train and inference without using the GPUs.    GPU Support  This version of Tensorflow will have support for GPU based operations. This can be used in Power 9 systems.   Installation instruc

Hi,I have miniconda installted and I am trying to install some tools using it, but it is showing some channel error.This is what I am doing -1. I have Miniconda installed in - /shrd/miniconda/v22. I have a environment named Rocket inside - /shrd/miniconda/v2/envs/Rocket3. I have the Channel name inside the file - /shrd/miniconda/v2/.condarc                              What's inside .condarc :                                                            add_pip_as_python_dependency: False                                                             channel_alias: https://anaconda.org/                                                             channels:                                                                               - zoss-appdev4. I have a file named appdev_manifest inside - /shrd/miniconda5.  So when I am running the following command I am getting error:                                       conda install - -file /shrd/miniconda/appdev_manifest_1.2.txtERROR I AM GETTING:ba

Dear Everyone, We observed that micro focus region refresh is taking too long post upgrade i.e v5.0 Pu24 where as in v4.0 Pu14 it took less than 5 mins. Here are the observations, 1) Region is started state within a minute after clicking the start tab/issuing the start command. 2) But all the allocated SEP's are in BUSY state with the process “CICS (Facility N/A Transition)” in ES monitor and control page for longer time (30 to 40 mins). 3) CPU% remains 100% until all SEP’s became IDEL state. 4) Server slow until all the process i.e “CICS (Facility N/A Transition) PIP2" are auto cleared up from ESMAC . 5) Multiple entries in the console log with following new message “ESFEV0328I Using native mutexes for thread locking” post upgrade. Allocated SEP: 51Admin SEP : 3 Can you please someone assist me to fix this performance issue. Thanks,#ESFadmin#ESF#mutex#EnterpriseServer#EnterpriseDeveloper