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Thailand’s National Science and Technology Development Agency (NSTDA) is building a new supercomputer to boost research by academia, government and industry in the country.
Touted as the largest of its kind in Southeast Asia, the supercomputer will be powered by 704 Nvidia A100 Tensor Core graphics processing units (GPUs) and hosted at NSTDA’s Supercomputer Centre (ThaiSC).
When ready by the end of 2022, it will support artificial intelligence (AI), data analytics and high performance computing (HPC) workloads in areas such as pharmaceuticals, renewable energy and weather forecasting.
“The new supercomputer at NSTDA will expand and enhance research in Thailand, speeding up the development of breakthroughs that benefit individuals and industries in the country,” said Dennis Ang, senior director for enterprise business at Nvidia in Southeast Asia, Australia and New Zealand.
Narong Sirilertworakul, president of NSTDA, said the new supercomputer will strengthen Thailand’s position in HPC and research capabilities, noting that researchers will benefit from real-world results and the ability to deploy solutions into production at scale.
ThaiSC’s users are looking forward to the new supercomputing capabilities, which will let them scale up and speed up their research projects.
One of them, Kwanchiva Thangthai, from the National Electronics and Computer Technology Centre’s speech and text understanding team, said she expects “massive efficiency gains in speech recognition research pipelines”. “We can gain competitive performance and provide a free-of-charge Thai speech-to-text service for everyone via AIForThai,” she added, referring to Thailand’s national initiative to drive AI adoption in the country.
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The new supercomputer follows an earlier move by the NSTDA to deploy an Nvidia DGX A100 system, along with the use of Nvidia’s sequencing analysis software by the National Biobank of Thailand to accelerate genomic sequencing efforts, including a genome study to combat Covid-19.
“Nvidia GPUs are the core of our molecular dynamics simulation platform,” said Thanyada Rungrotmongkol of Chulalongkorn University’s structural and computational biology research unit.
“We are inspired by the ability to apply this technology to elucidate the behaviour of protein-ligand binding. In addition, the power of Nvidia GPUs hastens the research to find inhibitors against the coronavirus.”
Elsewhere in ASEAN, clinician researchers at Singapore’s National University Health System (NUHS) will soon be able to use edge supercomputing to speed up training of AI models in areas such as radiology.
When ready by the middle of this year, the petabyte-scale edge supercomputing infrastructure, dubbed Prescience, will reside at NUHS’s premises to address data privacy and security requirements.
It is expected to reduce the time it takes to train AI models from days to hours, allowing its medical and para-medical staff to optimise patient trajectories and improve patient care.