Benchmarking Fortran DO CONCURRENT on CPUs and GPUs Using BabelStream

Hammond, Jeff R.; Deakin, Tom; Cownie, James H.; McIntosh–Smith, Simon

doi:10.1109/pmbs56514.2022.00013

Cited by 6 publications

(2 citation statements)

References 18 publications

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“…Due to the novelty of DC support for GPUs, there are only a few examples of its use in the literature (such as a spherical surface diffusion tool called DIFFUSE [9], and an implementation of the BabelStream benchmark [10]). There are additional works in progress, including a chemistry mini-app called CCSD(T) 4 , a CFD weather mini-app called MiniWeather 5 , a hydrodynamics mini-app called CloverLeaf 6 , and a conjugate gradient solver used in Solar physics called POT3D 7 .…”

Section: Related Workmentioning

confidence: 99%

“…From our previous experience in porting OpenACC to DC [7], we learned that using manual data management yields better performance than relying on unified managed memory (UM) capabilities. Unified managed memory is an NVIDIA feature that will automatically page data to and from the GPU and CPU for GPU-accelerated codes 10 . This eases the burden of the programmer by not requiring manual management of the data movement.…”

Section: A Code 1 [A]: Current Openacc Implementationmentioning

confidence: 99%

See 1 more Smart Citation

Acceleration of a production Solar MHD code with Fortran standard parallelism: From OpenACC to `do concurrent'

Caplan¹,

M.²,

Linker³

2023

Preprint

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There is growing interest in using standard language constructs for accelerated computing, avoiding the need for (often vendor-specific) external APIs. These constructs hold the potential to be more portable and much more 'future-proof'. For Fortran codes, the current focus is on the do concurrent (DC) loop. While there have been some successful examples of GPU-acceleration using DC for benchmark and/or small codes, its widespread adoption will require demonstrations of its use in full-size applications. Here, we look at the current capabilities and performance of using DC in a production application called Magnetohydrodynamic Algorithm outside a Sphere (MAS). MAS is a state-of-the-art model for studying coronal and heliospheric dynamics, is over 70,000 lines long, and has previously been ported to GPUs using MPI+OpenACC. We attempt to eliminate as many of its OpenACC directives as possible in favor of DC. We show that using the NVIDIA nvfortran compiler's Fortran 202X preview implementation, unified managed memory, and modified MPI launch methods, we can achieve GPU acceleration across multiple GPUs without using a single OpenACC directive. However, doing so results in a slowdown between 1.25x and 3x. We discuss what future improvements are needed to avoid this loss, and show how we can still retain close to the original code's performance while reducing the number of OpenACC directives by a factor of five.

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Section: Related Workmentioning

confidence: 99%

Section: A Code 1 [A]: Current Openacc Implementationmentioning

confidence: 99%

Acceleration of a production Solar MHD code with Fortran standard parallelism: From OpenACC to `do concurrent'

Caplan¹,

M.²,

Linker³

2023

Preprint

View full text Add to dashboard Cite

show abstract

Design of Neko—A Scalable High‐Fidelity Simulation Framework With Extensive Accelerator Support

Jansson,

Karp,

Wahlgren

et al. 2024

Concurrency and Computation

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Recent trends and advancements in including more diverse and heterogeneous hardware in High‐Performance Computing (HPC) are challenging scientific software developers in their pursuit of efficient numerical methods with sustained performance across a diverse set of platforms. As a result, researchers are today forced to re‐factor their codes to leverage these powerful new heterogeneous systems. We present our design considerations of Neko—a portable framework for high‐fidelity spectral element flow simulations. Unlike prior works, Neko adopts a modern object‐oriented Fortran 2008 approach, allowing multi‐tier abstractions of the solver stack and facilitating various hardware backends ranging from general‐purpose processors, accelerators down to exotic vector processors and Field‐Programmable Gate Arrays (FPGAs). Focusing on the performance and portability of Neko, we describe the framework's device abstraction layer managing device memory, data transfer and kernel launches from Fortran, allowing for a solver written in a hardware‐neutral yet performant way. Accelerator‐specific optimizations are also discussed, with auto‐tuning of key kernels and various communication strategies using device‐aware MPI. Finally, we present performance measurements on a wide range of computing platforms, including the EuroHPC pre‐exascale system LUMI, where Neko achieves excellent parallel efficiency for a large direct numerical simulation (DNS) of turbulent fluid flow using up to 80% of the entire LUMI supercomputer.

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Heliophysics and space weather information architecture and innovative solutions: Current status and ways forward

Masson,

Fung,

Camporeale

et al. 2024

Advances in Space Research

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Benchmarking Fortran DO CONCURRENT on CPUs and GPUs Using BabelStream

Cited by 6 publications

References 18 publications

Acceleration of a production Solar MHD code with Fortran standard parallelism: From OpenACC to `do concurrent'

Acceleration of a production Solar MHD code with Fortran standard parallelism: From OpenACC to `do concurrent'

Design of Neko—A Scalable High‐Fidelity Simulation Framework With Extensive Accelerator Support

Heliophysics and space weather information architecture and innovative solutions: Current status and ways forward

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