Nanotechnology Now – Press Release: Open-source GPU technology for supercomputers: Researchers navigate advantages and disadvantages

House > Press > Open-source GPU know-how for supercomputers: Researchers navigate benefits and downsides

Vladimir Stegailov, HSE University professor

CREDIT
Vladimir Stegailov
Vladimir Stegailov, HSE College professor

CREDIT
Vladimir Stegailov

Summary:
Researchers from the HSE Worldwide Laboratory for Supercomputer Atomistic Modelling and Multi-scale Evaluation, JIHT RAS and MIPT have in contrast the efficiency of widespread molecular modelling applications on GPU accelerators produced by AMD and Nvidia. In a paper printed by the Worldwide Journal of Excessive Efficiency Computing Functions, the students ported LAMMPS on the brand new open-source GPU know-how, AMD HIP, for the primary time.

Open-source GPU know-how for supercomputers: Researchers navigate benefits and downsides


Moscow, Russia | Posted on April 30th, 2021

The students completely analysed the efficiency of three molecular modelling applications – LAMMPS, Gromacs and OpenMM – on GPU accelerators Nvidia and AMD with comparable peak parameters. For the assessments, they used the mannequin of ApoA1 (Apolipoprotein A1) — apolipoprotein in blood plasma, the principle provider protein of ‘good ldl cholesterol’. They discovered that the efficiency of analysis calculations is influenced not solely by parameters, but additionally by software program atmosphere. It turned out that ineffective efficiency of AMD drivers in difficult situations of parallel launch of computing kernels can result in appreciable delays. Open-source options nonetheless have their disadvantages.

Within the lately printed paper, the researchers have been the primary to port LAMMPS on a brand new open-source GPU know-how, AMD HIP. This creating know-how seems to be very promising because it helps successfully use one code each on Nvidia accelerators and on new GPUs by AMD. The developed LAMMPS modification has been printed as an open supply and is accessible within the official repository: customers from everywhere in the world can use it to speed up their calculations.

‘We completely analysed and in contrast the GPU accelerator reminiscence sub-systems of Nvidia Volta and AMD Vega20 architectures. I discovered a distinction within the logics of parallel launch of GPU kernels and demonstrated it by visualizing this system profiles. Each the reminiscence bandwidth and the latencies of various ranges of GPU reminiscence hierarchy in addition to the efficient parallel execution of GPU kernels — all these facets have a serious impression on the true efficiency of GPU applications,’ mentioned Vsevolod Nikolskiy, HSE College doctoral pupil and one of many paper’s authors.

The paper’s authors argue that participation within the technological race of the modern microelectronics giants demonstrates an apparent pattern towards better number of GPU acceleration applied sciences.

‘On the one hand, this truth is optimistic for finish customers, because it stimulates competitors, rising effectiveness and the reducing value of supercomputers. Then again, will probably be much more troublesome to develop efficient applications because of the want to think about the supply of a number of various kinds of GPU architectures and programming applied sciences,’ commented Vladimir Stegailov, HSE College professor. ‘Even supporting program portability for abnormal processors on completely different architectures (x86, Arm, POWER) is commonly difficult. Portability of applications between completely different GPU platforms is a way more difficult concern. The open-source paradigm eliminates many obstacles and helps the builders of massive and sophisticated supercomputer software program.’

In 2020, the marketplace for graphic accelerators skilled a rising deficit. The favored areas of their use are well-known: cryptocurrency mining and machine studying duties. In the meantime, scientific analysis additionally requires GPU accelerators for mathematical modelling of latest supplies and organic molecules.

‘Creating highly effective supercomputers and creating quick and efficient applications is how instruments are ready for fixing probably the most complicated world challenges, such because the COVID-19 pandemic. Computation instruments for molecular modelling are used globally immediately to seek for methods to struggle the virus,’ mentioned Nikolay Kondratyuk, researcher at HSE College and one of many paper’s authors.

An important applications for mathematical modelling are developed by worldwide groups and students from dozens of establishments. Growth is carried out throughout the open-source paradigm and beneath free licenses. The competitors of two modern microelectronics giants, Nvidia and AMD, has led to the emergence of a brand new open-source infrastructure for GPU accelerators’ programming, AMD ROCm. The open-source character of this platform provides hope for max portability of codes developed with its use, to supercomputers of assorted varieties. Such AMD technique is completely different from Nvidia’s strategy, whose CUDA know-how is a closed customary.

It didn’t take lengthy to see the response from the educational neighborhood. Tasks of the most important new supercomputers based mostly on AMD GPU accelerators are near completion. The Lumi in Finland with zero.5 exaFLOPS of efficiency (which has similarities to efficiency of 1,500,000 laptops!) is rapidly being constructed. This yr, a extra highly effective supercomputer, Frontier, is anticipated within the USA (1.5 exaFLOPS), and in 2023 – an much more highly effective El Capitan (2 exaFLOPS) is anticipated.

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Contacts:
Liudmila Mezentseva

7-926-313-2406

@HSE_eng

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