סילבוס Syllabus Силабус خطة الدورة

                   Class                                                             Tirgul

1    Intro – Machine learning                                    Python
2    Intro – CNN, RNN, etc                                       Pytorch
3    training - the use of CPUs                                   Performance and power counters
4           the use of GPUs                                           CUDA I
5           GPU optimizations                                      CUDA II
6           Sparsity, pruning and compression              Sparse data structures and algorithms
7    Inference  Binarization and  quantization            Libraries for Binarization and quantization on CPU
8           The use low precession                                 Libraries for Binarization and quantization on GPUs
9           Introduction to FPGA                                   Setting the FPGA environment
10           Binarization and quantization on  FPGA    Running an example on FPGA
11    In Memory                                                         In Memory Example
12    Spiking                                                              Spiking Example
13    Put it all together