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...

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...

DOE has continued to partner with The HDF Group, supporting development of HDF5 through two generations of computing; sponsoring this development has benefited the entire HDF5 user community. Today, DOE supports current HDF5 R&D to ensure that the data challenges of third generation exascale computing ...

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

MuQun (Kent) Yang, The HDF Group

Many NASA HDF and HDF5 data products can be visualized via the Hyrax OPeNDAP server through Hyrax’s HDF4 and HDF5 handlers.  Now we’ve enhanced the HDF5 OPeNDAP handler so that SMAP level 1, level 3 and level 4 products can be displayed properly using popular visualization tools.

Organizations in both the public and private sectors use HDF to meet long term, mission-critical data management needs. For example, NASA’s Earth Observing System, the primary data repository for understanding global climate change, uses HDF.  Over the lifetime of the project, which began in 1999, NASA has stored 15 petabytes of satellite data in HDF which will be accessible by NASA data centers and NASA HDF end users for many years to come.

In a previous blog, we discussed the concept of using the Hyrax OPeNDAP web server to serve NASA HDF4 and HDF5 products.  Each year, The HDF Group has enhanced the HDF4 and HDF5 handlers that work within the Hyrax OPeNDAP framework to support all sorts of NASA HDF data products, making them interoperable with popular Earth Science tools such as NASA’s Panoply and UCAR’s IDV.  The Hyrax HDF4 and HDF5 handlers make data products display properly using popular visualization tools. 

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:...