In the previous article, we discussed the performance and accuracy of Binarized Neural Networks (BNN). We also introduced a BNN coded from scratch in the Wolfram Language. The key component of this neural network is Matrix Multiplication.
Cython* is a superset of Python* that additionally supports C functions and C types on variable and class attributes. Cython generates C extension modules, which can be used by the main Python program using the import statement.
Learn techniques for vectorizing code, adding thread-level parallelism, and enabling memory optimization.
With multi-core processors now common place in PCs, and core counts continually climbing, software developers must adapt. By learning to tackle potential performance bottlenecks and issues with concurrency, engineers can future-proof their code to seamlessly handle additional cores as they are added to consumer systems.
This recipe describes how to get, build, and run the GROMACS* code on Intel® Xeon® and Intel® Xeon Phi™ processors for better performance on a single node.
Applying Intel® Threading Building Blocks Observers for Thread Affinity on Intel® Xeon Phi™ Coprocessors
In spite of the fact that the Intel® Threading Building Blocks (Intel® TBB) library   provides high-level task based parallelism intended to hide sof