The University of Utah announced the creation of a new oneAPI Center of Excellence focused on developing portable, scalable, and high-performance data compression techniques.
The oneAPI center will be led from the Center for Extreme Data Management Analysis and Visualization (CEDMAV) at the University of Utah and will involve the cooperation of the Applied Scientific Computing Center (CASC) at Lawrence Livermore National Laboratory . It will accelerate ZFP compression software using oneAPI’s open and standards-based programming across multiple architectures to advance exascale computing.
Participants said the center’s efforts extend long-standing collaborations of organizations dedicated to developing advanced data formats and layouts for efficient storage and access to large-scale scientific data for data architectures. high performance computing (HPC).
“CEDMAV at the University of Utah, in collaboration with the CASC at LLNL, has pioneered research in managing extreme data applications involving scientific simulations and experimental setups,” said Manish Prashar, director of the Scientific Computing and Imaging Institute at the University of Utah. “This collaboration has a long history of developing and deploying open source scientific software that finds wide adoption in communities of interest. This oneAPI Center of Excellence will strengthen this collaboration and help this academic research find practical adoption on multi-architecture systems.
Developed by LLNL, ZFP is a state-of-the-art software for lossless, error-controlled compression of floating-point data that is becoming a de facto standard in the HPC community, with many scientific and technical applications and users. ZFP (de)compression lends itself particularly well to parallel data execution thanks to its decomposition into small independent data blocks, and parallel backends have been developed for the OpenMP, CUDA and HIP programming models, according to computer scientist LLNL Peter Lindström.
“As ZFP Development Manager, I am excited about this opportunity with our long-time collaborators at the University of Utah to extend the capabilities of our ZFP Compressor to run efficiently on next-generation supercomputers. , including the Aurora system at Argonne National Laboratory, one of the world’s first exascale systems,” Lindstrom said. “The resulting compression software will enable large-scale scientific computing applications, among other things, to effectively increase memory capacity and bandwidth while dramatically reducing communication and I/O time and offline storage.”
Together with LLNL’s ZFP development team, the oneAPI Center of Excellence will develop a portable, scalable and high-performance ZFP backend based on SYCL that runs on accelerator architectures from different vendors, including data center GPUs Intel. As one of the software technologies selected by the Department of Energy’s (DOE) Exascale Computing Project (ECP), ZFP is embraced by massively parallel simulations and technologies running on some of the world’s largest supercomputers, which will benefit several high-visibility scientific applications. Additionally, the widespread adoption of ZFP in industry and academia will help advance many large-scale data management technologies, including HDF5, ADIOS, OpenZGY, OpenVisus, and Zarr.
Developing a high-performance SYCL port of ZFP on accelerator architectures supporting multiple vendors will benefit multiple high-visibility compute-intensive applications and better showcase the power of an open, standards-based software ecosystem. .
“The work of the University of Utah and Lawrence Livermore National Laboratory on the development of a high-performance ZFP library based on SYCL facilitates the availability of large-scale scientific data for high-performance computing architectures, enabling applications exascale to target multiple accelerator architectures,” said Scott Apeland, Principal. Intel Developer Ecosystem programs. “This latest Center of Excellence will show how open, standards-based oneAPI development benefits the developer community.”
CEDMAV’s research approach stems from a systematic assessment of HPC application needs and how they drive new research and innovation, followed by practical validation and deployment in broader communities. CEDMAV’s previous collaborations with LLNL include shared research projects, dual-appointed staff, student interns, and postdocs.
“It is an honor for CEDMAV to establish this oneAPI Center of Excellence in collaboration with LLNL. This will provide a great opportunity to consolidate our collaboration and expand it with the support and collaboration of Intel engineers,” said said Valerio Pascucci, founding director of CEDMAV and former head of the CASC data analysis group at LLNL, “It’s exciting to see the emergence of the oneAPI programming model that we plan to fully adopt in this project. In particular, the SYCL cross-platform abstraction will greatly increase the productivity of our teams in creating high-performance code that runs efficiently on modern, heterogeneous architectures. Various hardware-software architectures are becoming ubiquitous in high-performance systems, and oneAPI technology will dramatically increase the impact of ZFP in a wide range of applications.
CEDMAV at the University of Utah is internationally recognized for its activities involving theoretical and algorithmic research, systems development, and the deployment of tools to process extreme data. This research sits at the intersection of scientific visualization, big data management, HPC and data analytics.
The Center for Applied Scientific Computing serves as LLNL’s window to the broader research communities in computer science, computational physics, applied mathematics, and data science. With partners in academia, industry, and other government laboratories, it conducts world-class scientific research and development on issues critical to national security.
About an API
oneAPI is an open, unified, cross-architecture programming model for processor and accelerator architectures (GPUs, FPGAs and others). The standards-based programming model simplifies software development and delivers uncompromising performance for accelerated computing without proprietary lock-in, while enabling integration of existing code. With oneAPI, developers can choose the best architecture for the specific problem they are trying to solve without having to rewrite software for the next architecture and platform.
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