Jorge Naranjo
High Performance Computing Lead at New York University Abu Dhabi
United Arab Emirates
Summary
👤
Senior🎓
Top SchoolJorge Naranjo is a High Performance Computing lead and computational scientist with 14+ years of experience enabling and optimizing scientific applications across national supercomputing centers and research universities. He has deep expertise in HPC architectures, performance analysis, code porting and tuning for multi-core and GPU-accelerated systems, and currently focuses on HPC-AI convergence and performance portability for Exascale environments. At NYU Abu Dhabi and NYU he blends hands-on application optimization with software environment management to preserve scientific integrity in complex, multi-platform stacks. His background spans academia and industry—from drug discovery GUI tools to real-time image processing and biomedical signal research—giving him a rare cross-disciplinary perspective on applied compute challenges. Based in the UAE, Jorge is also interested in cloud, Big Data and emerging areas like blockchain, bringing curiosity-driven exploration to production-grade HPC solutions.
14 years of coding experience
14 years of employment as a software developer
Bachelor of Science (BSc), Telecommunications Engineering, Bachelor of Science (BSc), Telecommunications Engineering at UCLVAdvanced Studies Diploma, DSP, Advanced Studies Diploma, DSP at Universidad de Vigo
Github Skills (3)
hpc3
computer-vision2
cpp2
Programming languages (2)
Github contributions (5)
nyuad-hpc/dalman
Aug 2016 - Feb 2022
Contributions:175600 pushes in 5 years 7 months
jonarbo/GREASY
Jan 2012 - Feb 2012
Greasy is an HTC approach to HPC environments (HT&PC). Versatile and easy-to-use parallel framework/runtime aimed at many task computing, ideally in HPC environments. Greasy is a tool designed to make easier the deployment of embarrassingly parallel simulations in any environment. It is able to run in parallel a list of different tasks, schedule them and run them using the available resources. It is the perfect tool to use, for example, when your application is a serial program, and you need to run a large number of instances with different parameters. Greasy packs all these separate runs and uses the resources granted to run as many tasks as possible in parallel. As this tasks finish, Greasy will continue starting the tasks that were waiting for resources. Since one of the main principles of Greasy is to keep it simple for the user, the list of tasks is just that: a list of tasks in a text file. Then, each line in the file becomes a task to be run by Greasy. It is able to manage dependencies between tasks, or to rerun a task in case of failure if desired. Greasy can be easily configured by default with a configuration file, and can be also customized for each particular execution using environment variables. It also provides a log system where all greasy actions will be recorded to keep track of what is the progress of your run.
Contributions:21 commits in 23 days
hpc
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