nAG
The official YouTube Channel of nAG: Robust, trusted numerical software and computational expertise. Empowering engineering, science, and business. Part of the n2 Group.
Optimizing Lap Time Simulation (Silverstone Race Track)
Artificial Intelligence on Azure with NVIDIA | Azure HPC & AI Collaboration Centre Update
A Future in Computational Mathematics: NAG and Numerical Analysis
Modern modelling techniques in convex optimization and its applicability to finance and beyond
Tools and Methods for Application Performance Profiling
Total Cost of Ownership for HPC
Case Study Webinar: 3x Speed Improvement for CFD Solver
Getting Started with the NAG Library for Python
How to identify and quantify causes of MPI underperformance using the ITAC
Verification and Modernisation of Fortran Codes using the NAG Fortran Compiler
How to identify causes of poor OpenMP parallel performance using the Intel® VTune Amplifier
Benchmarking as the answer to HPC performance and architecture questions
The Role of Matrix Functions Webinar
How to calculate the Nearest Correlation Matrix
How to install the NAG Library
Algorithmic Differentiation Webinar
How to Use the NAG Compiler & Fortran Builder - Part 4 'Using OpenMP'
How to Use the NAG Compiler & Fortran Builder - Part 3 'Using Extra Libraries'
How to Use the NAG Compiler & Fortran Builder - Part 2 'Checking & Debugging'
How to Use the NAG Compiler and Fortran Builder - Part 1
‘Quant Finance Using the NAG Library for Python’ Part 8
‘Quant Finance Using the NAG Library for Python’ Part 7
‘Quant Finance Using the NAG Library for C’ Part 3
‘Quant Finance Using the NAG Library for C’ Part 5
‘Quant Finance Using the NAG Library for C’ Part 1
‘Quant Finance Using the NAG Library for C’ Part 4
‘Quant Finance Using the NAG Library for Python’ Part 6
‘Quant Finance Using the NAG Library for C’ Part 2
Implied Volatility Video (using the NAG C Library)
Propensity modelling