arXiv subjects

John Dennis

Publications and source records attributed to John Dennis.

4 recordsLinked to original sources

arXiv2026

xDSL-CCPP: An alternative code generator for atmospheric modelling

The Common Community Physics Package (CCPP) is a framework designed to simplify the exchange of physics packages between state-of-the-art atmospheric models. A core software component of CCPP is a code generator: a bespoke Python-based application that uses regular expressions to transform an input specification into Fortran source code. While the code generator initially provided a simple transformation capability, the demands of state-of-the-art atmospheric models have resulted in significant increases in its complexity. Furthermore, ongoing code modernisation efforts to enable GPU-based computing have placed additional demands on the code generator for which it was never designed. Domain Specific Languages (DSLs) have proven to be highly effective in High Performance Computing (HPC), offering the ability to simplify code modernisation efforts. However, traditionally the effort and specialist skills required in the development of a DSL have been a blocker to adoption. In recent years, however, there have been great advances in compiler technologies, and frameworks such as MLIR and xDSL have the potential to greatly lower this barrier to entry. In this paper, we present xDSL-CCPP, a new application-specific code generator based upon the latest MLIR and xDSL compiler technologies, for CCPP. Demonstrating a reduction in bespoke tooling code of around three times, from approximately 15,000 LoC to 5,000 LoC, we highlight the opportunities provided by these compiler frameworks and demonstrate how they significantly lower the barrier to development of HPC application-specific DSLs whilst maintaining application performance and promoting flexibility.

cs.DC↗

arXiv2026

Evaluating LLMs for Translating Legacy Fortran Atmospheric Physics to GPU-Accelerated JAX

Legacy Fortran physics packages in atmospheric models such as CESM, WRF, and E3SM pose a barrier to GPU modernization, while manual porting requires accelerator-programming expertise. We present LAFT (LLM-Assisted Fortran Translation), an agentic framework for converting Fortran atmospheric physics parameterizations into GPU-accelerated JAX while preserving numerical agreement with the Fortran reference. LAFT coordinates source-code analysis, translation, repair, runtime validation, and performance profiling. It combines a deterministic front end for metadata extraction and bridge generation, structured translation prompts, numerical validation, and profiling-guided feedback to identify inefficient execution patterns. The bridge handles array-layout conversion separately from scientific computation. We evaluate LAFT using the Kessler warm-rain microphysics scheme and four LLMs: Claude, GPT, Gemini, and Qwen. All four validated translations reproduce the Fortran reference outputs to near floating-point precision for the evaluated case, but their GPU performance differs substantially with execution design. The Gemini-generated implementation achieves up to a 357-fold speedup over serial Fortran in cached execution at 1,000,000 atmospheric columns, excluding compilation and host-device transfers. The results demonstrate that numerical agreement alone does not ensure efficient GPU execution and motivate combining numerical validation with hardware-aware performance analysis. LAFT provides a practical workflow for modernizing legacy atmospheric physics code through LLM-assisted translation, deterministic interface generation, automated validation and repair, and reproducible profiling.

physics.ao-ph↗

arXiv2019

C. H. Robinson Uses Heuristics to Solve Rich Vehicle Routing Problems

We consider a wide family of vehicle routing problem variants with many complex and practical constraints, known as rich vehicle routing problems, which are faced on a daily basis by C.H. Robinson (CHR). Since CHR has many customers, each with distinct requirements, various routing problems with different objectives and constraints should be solved. We propose a set partitioning framework with a number of route generation algorithms, which have shown to be effective in solving a variety of different problems. The proposed algorithms have outperformed the existing technologies at CHR on 10 benchmark instances and since, have been embedded into the company's transportation planning and execution technology platform.

cs.AI↗

arXiv2015

Implementation of PFC and RCM for RoCEv2 Simulation in OMNeT++

As traffic patterns and network topologies become more and more complicated in current enterprise data centers and TOP500 supercomputers, the probability of network congestion increases. If no countermeasures are taken, network congestion causes long communication delays and degrades network performance. A congestion control mechanism is often provided to reduce the consequences of congestion. However, it is usually difficult to configure and activate a congestion control mechanism in production clusters and supercomputers due to concerns that it may negatively impact jobs if the mechanism is not appropriately configured. Therefore, simulations for these situations are necessary to identify congestion points and sources, and more importantly, to determine optimal settings that can be utilized to reduce congestion in those complicated networks. In this paper, we use OMNeT++ to implement the IEEE 802.1Qbb Priority-based Flow Control (PFC) and RoCEv2 Congestion Management (RCM) in order to simulate clusters with RoCEv2 interconnects.

cs.NI↗