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IIT Bombay; NPTEL
High Performance Scientific Computing

Master high-performance computing fundamentals, parallel programming with OpenMP and MPI, GPU computing, and scientific visualization tools for advanced computational research and simulation applications.
- Swayam
- 12 weeks
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Practical High-Performance Computing

Master high-performance computing through parallel programming, covering MPI, OpenMP, GPU tools, and practical applications in scientific computing. Learn optimization techniques and implement real-world HPC projects.
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Center for Language & Speech Processing(CLSP), JHU
The Multidimensional Phoneme Identification (MPI) Model

Explore Mario Svirsky's Multidimensional Phoneme Identification (MPI) Model and its applications in speech processing and auditory perception research.
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Center for Language & Speech Processing(CLSP), JHU
The Multidimensional Phoneme Identification MPI Model

Explore the Multidimensional Phoneme Identification (MPI) Model and its applications in speech processing and auditory perception research.
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Modern Fortran

Learn Modern Fortran programming, from basics to advanced parallel computing techniques like OpenMP, OpenACC, CUDA, and MPI. Gain practical skills through hands-on exercises and explore best practices for efficient code development.
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NHR@FAU
Parallel Programming 2020

Master OpenMP and MPI programming techniques for high-performance computing through comprehensive lectures covering computer architecture, parallelism concepts, and hybrid programming approaches.
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Nvidia
DGX Spark - Accelerated cuPyNumeric on your Desktop Cluster

Discover how to scale Python and NumPy programs across multi-GPU systems using NVIDIA cuPyNumeric without complex parallel computing code on DGX Spark desktop clusters.
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Advanced Multi-GPU Programming with OpenACC - Lecture 2

Explore advanced multi-GPU programming techniques using OpenACC and MPI, covering domain decomposition, communication overlap, and tools for debugging and profiling MPI+OpenACC applications.
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The Julia Programming Language
Julia for High-Performance Computing - JuliaCon 2022

Explore Julia's capabilities for high-performance computing through expert talks on scalability, GPU support, MPI integration, and real-world applications in scientific and engineering domains.
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Canonical Ubuntu
Introduction to Numerical Computation Applications Using Ubuntu WSL

Explore numerical computing on Ubuntu WSL for efficient solver development and deployment, with practical examples and insights on streamlining workflows for complex engineering problems.
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Advanced Multi-GPU Scaling: Communication Libraries

Discover how to scale applications beyond single GPU limitations using CUDA-aware MPI, NVSHMEM, and NCCL, demonstrated through real-world examples for computing larger workloads faster.
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Inside Livermore Lab
Interpolation at Arbitrary Points in High-Order Meshes on GPUs

Discover advanced techniques for arbitrary point interpolation in high-order mesh computations, focusing on GPU optimization and parallel processing for efficient scientific simulations.
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The Julia Programming Language
Advancements in Peridynamics.jl for Dynamic Fracture Simulations

Explore advancements in Peridynamics.jl for dynamic fracture simulations, including improved HPC support, new API, and expanded material models. Learn through tutorials and example simulations.
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NHR@FAU
C++ is Nearly All You Need for HPC

Explore modern C++ features for high-performance computing, including parallel algorithms, mdspan, and execution models for shared-memory and accelerated programming.
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The Julia Programming Language
Serving Legacy Fortran Codes with Julia Simulations Using libtrixi

Discover how to integrate Julia's computational fluid dynamics solver with legacy Fortran code using libtrixi, enabling high-performance simulations and parallel processing for earth system modeling.
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