Experience Report: Type-checking Polymorphic Units for Astrophysics Research in Haskell

Many of the bugs in scientific programs have their roots in mistreatment of physical dimensions, via erroneous expressions in the quantity calculus. Now that the type system in the Glasgow Haskell Compiler is rich enough to support type-level integers and other promoted datatypes, we can type-check the quantity calculus in Haskell. In addition to basic dimension-aware arithmetic and unit conversions, our units library features an extensible system of dimensions and units, a notion of dimensions apart from that of units, and unit polymorphism designed to describe the laws of physics. We demonstrate the utility of units by writing an astrophysics research paper. This work is free of unit concerns because every quantity expression in the paper is rigorously type-checked

Formal Model-Based Assurance Cases in Isabelle/SACM : An Autonomous Underwater Vehicle Case Study

Isabelle/SACM is a tool for automated construction of model-based assurance cases with integrated formal methods, based on the Isabelle proof assistant. Assurance cases show how a system is safe to operate, through a human comprehensible argument demonstrating that the requirements are satisfied, using evidence of various provenances. They are usually required for certification of critical systems, often with evidence that originates from formal methods. Automating assurance cases increases rigour, and helps with maintenance and evolution. In this paper we apply Isabelle/SACM to a fragment of the assurance case for an autonomous underwater vehicle demonstrator. We encode the metric unit system (SI) in Isabelle, to allow modelling requirements and state spaces using physical units. We develop a behavioural model in the graphical RoboChart state machine language, embed the artifacts into Isabelle/SACM, and use it to demonstrate satisfaction of the requirements

Atmospheric electrification in dusty, reactive gases in the solar system and beyond

Detailed observations of the solar system planets reveal a wide variety of local atmospheric conditions. Astronomical observations have revealed a variety of extrasolar planets none of which resembles any of the solar system planets in full. Instead, the most massive amongst the extrasolar planets, the gas giants, appear very similar to the class of (young) Brown Dwarfs which are amongst the oldest objects in the universe. Despite of this diversity, solar system planets, extrasolar planets and Brown Dwarfs have broadly similar global temperatures between 300K and 2500K. In consequence, clouds of different chemical species form in their atmospheres. While the details of these clouds differ, the fundamental physical processes are the same. Further to this, all these objects were observed to produce radio and X-ray emission. While both kinds of radiation are well studied on Earth and to a lesser extent on the solar system planets, the occurrence of emission that potentially originate from accelerated electrons on Brown Dwarfs, extrasolar planets and protoplanetary disks is not well understood yet. This paper offers an interdisciplinary view on electrification processes and their feedback on their hosting environment in meteorology, volcanology, planetology and research on extrasolar planets and planet formation

AN5D: Automated Stencil Framework for High-Degree Temporal Blocking on GPUs

Stencil computation is one of the most widely-used compute patterns in high performance computing applications. Spatial and temporal blocking have been proposed to overcome the memory-bound nature of this type of computation by moving memory pressure from external memory to on-chip memory on GPUs. However, correctly implementing those optimizations while considering the complexity of the architecture and memory hierarchy of GPUs to achieve high performance is difficult. We propose AN5D, an automated stencil framework which is capable of automatically transforming and optimizing stencil patterns in a given C source code, and generating corresponding CUDA code. Parameter tuning in our framework is guided by our performance model. Our novel optimization strategy reduces shared memory and register pressure in comparison to existing implementations, allowing performance scaling up to a temporal blocking degree of 10. We achieve the highest performance reported so far for all evaluated stencil benchmarks on the state-of-the-art Tesla V100 GPU

Ruy Blas : drama lírico en cuatro actos

In this paper we present research on applying a domain specific high-level abstractions (HLA) development strategy with the aim to “future-proof” a key class of high performance computing (HPC) applications that simulate hydrodynamics computations at AWE plc. We build on an existing high-level abstraction framework, OPS, that is being developed for the solution of multi-block structured mesh-based applications at the University of Oxford. OPS uses an “active library” approach where a single application code written using the OPS API can be transformed into different highly optimized parallel implementations which can then be linked against the appropriate parallel library enabling execution on different back-end hardware platforms. The target application in this work is the CloverLeaf mini-app from Sandia National Laboratory’s Mantevo suite of codes that consists of algorithms of interest from hydrodynamics workloads. Specifically, we present (1) the lessons learnt in re-engineering an industrial representative hydro-dynamics application to utilize the OPS high-level framework and subsequent code generation to obtain a range of parallel implementations, and (2) the performance of the auto-generated OPS versions of CloverLeaf compared to that of the performance of the hand-coded original CloverLeaf implementations on a range of platforms. Benchmarked systems include Intel multi-core CPUs and NVIDIA GPUs, the Archer (Cray XC30) CPU cluster and the Titan (Cray XK7) GPU cluster with different parallelizations (OpenMP, OpenACC, CUDA, OpenCL and MPI). Our results show that the development of parallel HPC applications using a high-level framework such as OPS is no more time consuming nor difficult than writing a one-off parallel program targeting only a single parallel implementation. However the OPS strategy pays off with a highly maintainable single application source, through which multiple parallelizations can be realized, without compromising performance portability on a range of parallel systems