Putt Sakdhnagool
Team Lead at NSTDA Supercomputer Center (ThaiSC)
Bangkok Metropolitan Area Thailand
Summary
👤
Senior🎓
Top SchoolPutt Sakdhnagool is a Team Lead and HPC researcher with 8 years of experience designing and operating production supercomputing clusters, including leading ThaiSC’s LANTA (ranked #70 on the Top500 in Nov 2022) and designing the center’s first cluster, TARA. He blends deep expertise in CUDA, parallel programming, compilers, and scheduler tuning with hands-on systems leadership—optimizing cluster performance, coordinating vendors, and driving maintenance and operational strategies. As a researcher and former ORNL visiting scholar, he focuses on automatic parallelization and accelerator programming models while also applying his skills as a startup CTO building cloud-native services in Go on AWS. Comfortable shifting between low-level compiler research and pragmatic engineering, he’s notable for turning advanced HPC techniques into reliable, production-grade infrastructure for science and industry.
8 years of coding experience
3 years of employment as a software developer
B.Eng, Computer Engineering, B.Eng, Computer Engineering at Kasetsart UniversityUniversity of California San DiegoPh.D, Computer Engineering, Ph.D, Computer Engineering at Purdue University
English
Github Skills (46)
describe10
linux10
modular9
python9
hpc9
cpp9
cuda8
xml8
flags8
sampling8
benchmark8
hpc-cluster7
benchmarking7
gpu7
country-codes7
Programming languages (6)
Github contributions (5)
thaisc-hpc/lanta-benchmark
Jul 2020 - Nov 2020
Lanta Benchmark Suite is a set of applications for measuring performance of a HPC cluster. These set of applications represent workload for ThaiSC users. Lanta Benchmark Suite is expected to be used in part for performance evaluation of the new Lanta cluster.
Contributions:7 releases, 76 commits, 16 PRs in 4 months
benchmarkingbenchmark-suiteinfinibandevaluationbenchmark
puttsk/cuda-tutorial
Jun 2018 - Jul 2022
Contributions:51 commits, 5 PRs, 44 pushes in 4 years 2 months
cudahands-ongpu-accelerationcuda-programminggpu
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