bmaxa
Legenda
- Poruka
- 70.808
Zgodna stvarcica za ljubitelje AVX512:
Izvor: https://nn-512.com/
Introduction
NN-512 is a compiler that generates C99 code for neural net inference
It takes as input a simple text description of a convolutional neural net inference graph
It produces as output a stand-alone C99 implementation of that graph
The generated C99 code uses AVX-512 vector instructions to perform inference
The generated C99 code is human-readable and should be compiled with GCC 9.1 or later
Earlier versions of GCC may also be used, yielding slightly inferior object code
The generated C99 code has no dependencies outside the C POSIX library
NN-512 is a Go program with no dependencies outside the Go standard library
The NN-512 compiler executable is stand-alone
NN-512 performs a variety of inference graph optimizations
Fusion of elementwise operations into adjacent operations
Fusion of similar convolutions (as needed for, e.g., ResNet)
Removal of concatenations (as needed for, e.g., DenseNet)
End-to-end planning of memory layout
NN-512 generates specialized code for each tensor operation
Guided by a description of the target CPU cache hierarchy
Thread-level parallelism is maximized while limiting synchronization costs
Simplified code is generated for tensor edges, exploiting tile/vector overhang
Complete knowledge of memory layout simplifies addressing
Izvor: https://nn-512.com/