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Fortran at LBNL
The LBNL CLaSS group, led by Dr. Damian Rouson, is pursuing several related efforts with a goal of accelerating adoption of parallel Fortran features in the HPC community.
Projects
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Parallel Runtime Interface for Fortran (PRIF)
- A compiler-independent and network-independent interface that implements the parallel features of Fortran, allowing multiple parallel backend implementations to support the parallel features of multiple Fortran compilers.
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Caffeine
- CoArray Fortran Framework of Efficient Interfaces to Network Environments: A parallel runtime library that aims to support Fortran compilers by implementing the Parallel Runtime Interface for Fortran (PRIF) atop various communication libraries
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Flang Testing Project
- The Berkeley Lab Flang team develops tests for the LLVM-Project Flang Fortran compiler. Because of the paramount importance of parallelism in high-performance computing, we are focusing on Fortran’s parallel features, commonly denoted "Coarray Fortran."
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Inference Engine
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Fortran Package Manager
- The Fortran Package Manager (fpm) is a package manager and build system for Fortran. Its key goal is to improve the user experience of Fortran programmers. It does so by making it easier to build your Fortran program or library, run the executables, tests, and examples, and distribute it as a dependency to other Fortran projects.
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Matcha
- Motility Analysis of T-Cell Histories in Activation. A virtual T-cell simulation written in Fortran 2018
Team Members
If you have any questions or comments, please email the team!
Current team members include:
Publications
A selection of recent publications relevant to Fortran research.
Please consult team member pages above for complete publication lists.
2023
Damian Rouson, Brad Richardson, Dan Bonachea, Katherine Rasmussen, "Parallel Runtime Interface for Fortran (PRIF) Design Document, Revision 0.2", Lawrence Berkeley National Laboratory Technical Report, December 20, 2023, LBNL 2001563, doi: 10.25344/S4DG6S
This design document proposes an interface to support the parallel features of Fortran, named the Parallel Runtime Interface for Fortran (PRIF). PRIF is a proposed solution in which the runtime library is responsible for coarray allocation, deallocation and accesses, image synchronization, atomic operations, events, and teams. In this interface, the compiler is responsible for transforming the invocation of Fortran-level parallel features into procedure calls to the necessary PRIF procedures. The interface is designed for portability across shared- and distributed-memory machines, different operating systems, and multiple architectures. Implementations of this interface are intended as an augmentation for the compiler’s own runtime library. With an implementation-agnostic interface, alternative parallel runtime libraries may be developed that support the same interface. One benefit of this approach is the ability to vary the communication substrate. A central aim of this document is to define a parallel runtime interface in standard Fortran syntax, which enables us to leverage Fortran to succinctly express various properties of the procedure interfaces, including argument attributes.
Michelle Mills Strout, Damian Rouson, Amir Kamil, Dan Bonachea, Jeremiah Corrado, Paul H. Hargrove, Introduction to High-Performance Parallel Distributed Computing using Chapel, UPC++ and Coarray Fortran, Tutorial at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC23), November 12, 2023,
A majority of HPC system users utilize scripting languages such as Python to prototype their computations, coordinate their large executions, and analyze the data resulting from their computations. Python is great for these many uses, but it frequently falls short when significantly scaling up the amount of data and computation, as required to fully leverage HPC system resources. In this tutorial, we show how example computations such as heat diffusion, k-mer counting, file processing, and distributed maps can be written to efficiently leverage distributed computing resources in the Chapel, UPC++, and Fortran parallel programming models.
The tutorial is targeted for users with little-to-no parallel programming experience, but everyone is welcome. A partial differential equation example will be demonstrated in all three programming models. That example and others will be provided to attendees in a virtual environment. Attendees will be shown how to compile and run these programming examples, and the virtual environment will remain available to attendees throughout the conference, along with Slack-based interactive tech support.
Come join us to learn about some productive and performant parallel programming models!
Michelle Mills Strout, Damian Rouson, Amir Kamil, Dan Bonachea, Jeremiah Corrado, Paul H. Hargrove, Introduction to High-Performance Parallel Distributed Computing using Chapel, UPC++ and Coarray Fortran (CUF23), ECP/NERSC/OLCF Tutorial, July 2023,
A majority of HPC system users utilize scripting languages such as Python to prototype their computations, coordinate their large executions, and analyze the data resulting from their computations. Python is great for these many uses, but it frequently falls short when significantly scaling up the amount of data and computation, as required to fully leverage HPC system resources. In this tutorial, we show how example computations such as heat diffusion, k-mer counting, file processing, and distributed maps can be written to efficiently leverage distributed computing resources in the Chapel, UPC++, and Fortran parallel programming models. This tutorial should be accessible to users with little-to-no parallel programming experience, and everyone is welcome. A partial differential equation example will be demonstrated in all three programming models along with performance and scaling results on big machines. That example and others will be provided in a cloud instance and Docker container. Attendees will be shown how to compile and run these programming examples, and provided opportunities to experiment with different parameters and code alternatives while being able to ask questions and share their own observations. Come join us to learn about some productive and performant parallel programming models!
Secondary tutorial sites by event sponsors:
Damian Rouson, Producing Software for Science with Class, SIAM Conference on Computational Science and Engineering, March 1, 2023,
- Download File: Rouson-SIAM-CSE-2023.pdf (pdf: 7.5 MB)
The Computer Languages and Systems Software (CLaSS) Group at Berkeley Lab researches and develops programming models, languages, libraries, and applications for parallel and quantum computing. The open-source software under development in CLaSS includes the GASNet-EX networking middleware, the UPC++ partitioned global address space (PGAS) template library, the Berkeley Quantum Synthesis Toolkit (BQSKit), and the MetaHipMer metagenome assembler. This talk will start with an overview of CLaSS software and the software sustainability practices commonly employed across the group. The talk will then dive more deeply into the our burgeoning contributions to the ecosystem supporting modern Fortran, including our test development for the LLVM Flang Fortran compiler. This presentation will demonstrate how agile software development techniques are helping to ensure robust front-end support for standard Fortran 2018 parallel programming features. The talk will also present several key insights that inspired our design and development of the CoArray Fortran Framework of Efficient Interfaces to Network Environments (Caffeine) parallel runtime library, emphasizing the design choices that help to ensure sustainability. Lastly, the talk will demonstrate the productivity benefits associated with the first Caffeine application in Motility Analysis of T-Cell Histories in Activation (Matcha).
Brad Richardson, Damian Rouson, Harris Snyder, Robert Singelterry, "Framework for Extensible, Asynchronous Task Scheduling (FEATS) in Fortran", Workshop on Asynchronous Many-Task Systems and Applications (WAMTA'23), Baton Rouge, LA, February 2023, doi: 10.25344/S4ZC73
Most parallel scientific programs contain compiler directives (pragmas) such as those from OpenMP, explicit calls to runtime library procedures such as those implementing the Message Passing Interface (MPI), or compiler-specific language extensions such as those provided by CUDA. By contrast, the recent Fortran standards empower developers to express parallel algorithms without directly referencing lower-level parallel programming models. Fortran’s parallel features place the language within the Partitioned Global Address Space (PGAS) class of programming models. When writing programs that exploit data-parallelism, application developers often find it straightforward to develop custom parallel algorithms. Problems involving complex, heterogeneous, staged calculations, however, pose much greater challenges. Such applications require careful coordination of tasks in a manner that respects dependencies prescribed by a directed acyclic graph. When rolling one’s own solution proves difficult, extending a customizable framework becomes attractive. The paper presents the design, implementation, and use of the Framework for Extensible Asynchronous Task Scheduling (FEATS), which we believe to be the first task-scheduling tool written in modern Fortran. We describe the benefits and compromises associated with choosing Fortran as the implementation language, and we propose ways in which future Fortran standards can best support the use case in this paper.
2022
Katherine Rasmussen, Damian Rouson, Naje George, Dan Bonachea, Hussain Kadhem, Brian Friesen, "Agile Acceleration of LLVM Flang Support for Fortran 2018 Parallel Programming", Research Poster at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC22), November 2022, doi: 10.25344/S4CP4S
The LLVM Flang compiler ("Flang") is currently Fortran 95 compliant, and the frontend can parse Fortran 2018. However, Flang does not have a comprehensive 2018 test suite and does not fully implement the static semantics of the 2018 standard. We are investigating whether agile software development techniques, such as pair programming and test-driven development (TDD), can help Flang to rapidly progress to Fortran 2018 compliance. Because of the paramount importance of parallelism in high-performance computing, we are focusing on Fortran’s parallel features, commonly denoted “Coarray Fortran.” We are developing what we believe are the first exhaustive, open-source tests for the static semantics of Fortran 2018 parallel features, and contributing them to the LLVM project. A related effort involves writing runtime tests for parallel 2018 features and supporting those tests by developing a new parallel runtime library: the CoArray Fortran Framework of Efficient Interfaces to Network Environments (Caffeine).
Damian Rouson, Dan Bonachea, "Caffeine: CoArray Fortran Framework of Efficient Interfaces to Network Environments", Proceedings of the Eighth Annual Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC2022), Dallas, Texas, USA, IEEE, November 2022, doi: 10.25344/S4459B
This paper provides an introduction to the CoArray Fortran Framework of Efficient Interfaces to Network Environments (Caffeine), a parallel runtime library built atop the GASNet-EX exascale networking library. Caffeine leverages several non-parallel Fortran features to write type- and rank-agnostic interfaces and corresponding procedure definitions that support parallel Fortran 2018 features, including communication, collective operations, and related services. One major goal is to develop a runtime library that can eventually be considered for adoption by LLVM Flang, enabling that compiler to support the parallel features of Fortran. The paper describes the motivations behind Caffeine's design and implementation decisions, details the current state of Caffeine's development, and previews future work. We explain how the design and implementation offer benefits related to software sustainability by lowering the barrier to user contributions, reducing complexity through the use of Fortran 2018 C-interoperability features, and high performance through the use of a lightweight communication substrate.
1969
A. Dubey, T. Ben-Nun, B. L. Chamberlain, B. R. de Supinski, D. Rouson, "Performance on HPC Platforms Is Possible Without C++", Computing in Science & Engineering, December 31, 1969, 25 (5):48-52, doi: 10.1109/MCSE.2023.3329330
Computing at large scales has become extremely challenging due to increasing heterogeneity in both hardware and software. More and more scientific workflows must tackle a range of scales and use machine learning and AI intertwined with more traditional numerical modeling methods, placing more demands on computational platforms. These constraints indicate a need to fundamentally rethink the way computational science is done and the tools that are needed to enable these complex workflows. The current set of C++-based solutions may not suffice, and relying exclusively upon C++ may not be the best option, especially because several newer languages and boutique solutions offer more robust design features to tackle the challenges of heterogeneity. In June 2023, we held a mini symposium that explored the use of newer languages and heterogeneity solutions that are not tied to C++ and that offer options beyond template metaprogramming and Parallel. For for performance and portability. We describe some of the presentations and discussion from the mini symposium in this article.
