FPGA AI Suite Handbook

ID 863373
Date 11/21/2025
Public
Document Table of Contents

9.3.1.1. Input Feature Tensor In-Memory Format

Input features are stored in FP16 format. FP16 format has 1 sign bit, 10 mantissa bits, and 5 exponent bits. The input features are converted by the IP hardware to its native format using a round to nearest, ties to even (RNE) rounding rule.

Feature elements are packed into CVEC-sized chunks in the channel dimension from low to high. The final CVEC chunk, at a given (d,h,w), is padded with zeros. The CVEC chunks are stored in NCDHW format. The order is as follows: batch, channel, depth, height, width, and CVEC, where CVEC is the fastest changing index and batch the slowest.

The following figure shows a sample memory layout for a 1×3×1×2×2 input tensor to a CVEC=2 architecture:

Figure 19. Input Tensor In-Memory Layout