HDF News

The HDFView 2.14 and HDF Java 3.3.2 release is now available. This release supports HDF5-1.8 and 32-bit object identifiers and was tested with HDF5-1.8.19 and HDF 4.2.13. It can be obtained from: https://support.hdfgroup.org/downloads/index.html It can also be obtained directly from: https://support.hdfgroup.org/products/java/release/download.html More information on this release can be found on the HDF Java home page. This is a maintenance release with a few bug fixes. It includes changes to the error exception handling in the Java HDF wrappers. These changes fix an issue that affected the display of HDF4 files in HDFView....

CONTENTS Release of HDF 4.2.13 Release of HDF 4.2.13 The HDF 4.2.13 release is now available. It can be obtained from the HDF4 home page: https://support.hdfgroup.org/products/hdf4/ HDF 4.2.13 is a minor release with a few changes, including: Support was added for macOS Sierra 10.12.5. Several memory leaks were fixed. The minimum CMake version supported is 3.2.2. For detailed information regarding this release, please see the Release Notes....

CONTENTS Release of HDF5-1.8.19 Release of HDF5-1.8.19 The HDF5-1.8.19 release is now available. It can be obtained from the HDF5 Download page: https://www.hdfgroup.org/downloads/hdf5/ It can also be obtained directly from: https://support.hdfgroup.org/HDF5/release/obtain518.html HDF5-1.8.19 is a minor release with a few new features and changes. Important changes include: Several H5PL (C) APIs were added to manipulate the entries of the plugin path table: H5PLappend, H5PLget, H5PLinsert, H5PLprepend, H5PLremove, H5PLreplace, and H5PLsize. H5Dget_chunk_storage_size (C) was added to obtain the storage size of a chunk in the file. This API was specifically added in support of H5DOread_chunk, but may also be useful for other purposes. H5DOread_chunk (High Level C) was added to read a raw data chunk directly from a dataset in a file, bypassing HDF5's internal data transfer pipeline, including...

Release of HDF5-1.8.18 (Newsletter #152) - 11/16/16 Release of HDF Java Products for HDF5-1.8 (HDFView 2.13, HDF JNI 3.2.1) (Newsletter #151) - 7/25/16 Release of HDF 4.2.12 (Newsletter #150) - 6/30/16 Release of HDF5-1.10.0-patch (Bulletin) - 5/26/16 Release of HDF5-1.8.17 (Newsletter #149) - 5/13/16 Release of HDF5-1.10.0 (Newsletter #148) - 3/31/16 ...

David Pearah, The HDF Group Hello again, HDF User Community, As I mentioned in my last blog post -- HDF: The Next 30 Years (Part 2) -- we're looking for ways to better engage our users, which includes providing better tools for you to get support from the HDF Community.  We are looking for your input on three things: the HDF User Forum, Roadmap for HDF5, and Focus Groups - please take a few minutes to complete these short surveys and let us know what you think! Discussion Board and Listserv Forum Feedback:  LINK  We currently provide a listserv as the primary way that folks post questions and feedback to the community, and we would like your feedback since we're looking at web-based tools to complement or...

Dave Pearah, The HDF Group In my previous post—HDF: The Next 30 Years (Part 1)—I outlined the challenges and opportunities facing The HDF Group as an open source company. In a nutshell: Opportunity: large-scale adoption around the world in many different industries with great community-driven development (700+ projects in Github) Challenge: sufficient profit from existing business (consulting) to sustainably extend and maintain the core HDF5 platform The HDF Group is blessed with an amazingly talented + passionate + dedicated team of folks who care deeply about the HDF community, and we're all working together to determine the best path forward to sustainability, i.e. the NEXT 30 years. We want to share some of the steps that we're already taking, and -- more importantly --...

The HDF Group’s HDF Server has been nominated for Best Use of HPC in the Cloud, and Best HPC Software Product or Technology in HPCWire’s 2016  Readers’ Choice Awards. HDF Server is a Python-based web service that enables full read/write web access to HDF data – it can be used to send and receive HDF5 data using an HTTP-based REST interface. While HDF5 provides powerful scalability and speed for complex datasets of all sizes, many HDF5 data sets used in HPC environments are extremely large and cannot easily be downloaded or moved across the internet to access data on an as-needed basis.  Users often only need to access a small subset of the data.  Using HDF Server, data can be kept in one...

David Pearah, The HDF Group Hello HDF Community! Thanks for the warm welcome into the HDF family: in my 4+ months as the new CEO, I've been blown away by your passion, diversity of interests and applications, and willingness to provide feedback on:  1. why you use HDF5?, and  2. how can HDF5 be improved? I also want to thank my predecessor Mike Folk for his invaluable and ongoing support. The HDF community is growing fast: when I last checked, there are nearly 700 HDF5 projects in GitHub! I've had the privilege of connecting via phone/web with dozens of you over the past few months. Across all of my discussions, one piece of feedback came back loud and clear: The HDF Group needs to be more engaged with its users and help foster...

Pearah joins The HDF Group as new Chief Executive Officer

Champaign, IL — The HDF Group today announced that its Board of Directors has appointed David Pearah as its new Chief Executive Officer. The HDF Group is a software company dedicated to creating high performance computing technology to address many of today’s Big Data challenges.

Pearah replaces Mike Folk upon his retirement after ten years as company President and Board Chair. Folk will remain a member of the Board of Directors, and Pearah will become the company’s Chairman of the Board of Directors.

Pearah said, “I am honored to have been selected as The HDF Group’s next CEO. It is a privilege to be part of an organization with a nearly 30-year history of delivering innovative technology to meet the Big Data demands of commercial industry, scientific research and governmental clients.”

Industry leaders in fields from aerospace and biomedicine to finance join the company’s client list.  In addition, government entities such as the Department of Energy and NASA, numerous research facilities, and scientists in disciplines from climate study to astrophysics depend on HDF technologies.

Pearah continued, “We are an organization led by a mission to make a positive impact on everyone we engage, whether they are individuals using our open-source software, or organizations who rely on our talented team of scientists and engineers as trusted partners. I will do my best to serve the HDF community by enabling our team to fulfill their passion to make a difference.  We’ve just delivered a major release of HDF5 with many additional powerful features, and we’re very excited about several innovative new products that we’ll soon be making available to our user community.”

“Dave is clearly the leader for HDF’s future, and

We are excited and pleased to announce HDF5-1.10.0, the most powerful version of our flagship software ever.> This major new release of HDF5 is more powerful than ever before and packed with new capabilities that address important data challenges faced by our user community. HDF5 1.10.0 contains many important new features and changes, including those listed below. The features marked with * use new extensions to the HDF5 file format. The Single-Writer / Multiple-Reader or SWMR feature enables users to read data while concurrently writing it. * The virtual dataset (VDS) feature enables users to access data in a collection of HDF5 files as a single HDF5 dataset and to use the HDF5 APIs to work with that dataset. *   (NOTE:...