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VTA Configuration
=================

The VTA stack incorporates both a hardware accelerator stack and
a TVM based software stack.
VTA incorporates flexibility out of the box: by modifying the
``3rdparty/vta-hw/config/vta_config.json`` high-level configuration file,
the user can change the shape of the tensor intrinsic,
clock frequency, pipelining, data type width, and on-chip buffer sizes.

Parameters Overview
-------------------

We explain the parameters listed in the ``vta_config.json`` file in the table
below.

+-----------------------+------------+--------------------------------------------------------+
| Attribute             | Format     | Description                                            |
+=======================+============+========================================================+
| ``TARGET``            | String     | The TVM device target.                                 |
+-----------------------+------------+--------------------------------------------------------+
| ``HW_VER``            | String     | VTA hardware version number.                           |
+-----------------------+------------+--------------------------------------------------------+
| ``LOG_INP_WIDTH``     | Int (log2) | Input data type signed integer width.                  |
+-----------------------+------------+--------------------------------------------------------+
| ``LOG_WGT_WIDTH``     | Int (log2) | Weight data type signed integer width.                 |
+-----------------------+------------+--------------------------------------------------------+
| ``LOG_ACC_WIDTH``     | Int (log2) | Accumulator data type signed integer width.            |
+-----------------------+------------+--------------------------------------------------------+
| ``LOG_BATCH``         | Int (log2) | VTA matrix multiply intrinsic input/output dimension 0.|
+-----------------------+------------+--------------------------------------------------------+
| ``LOG_BLOCK``         | Int (log2) | VTA matrix multiply inner dimensions.                  |
+-----------------------+------------+--------------------------------------------------------+
| ``LOG_UOP_BUFF_SIZE`` | Int (log2) | Micro-op on-chip buffer in Bytes.                      |
+-----------------------+------------+--------------------------------------------------------+
| ``LOG_INP_BUFF_SIZE`` | Int (log2) | Input on-chip buffer in Bytes.                         |
+-----------------------+------------+--------------------------------------------------------+
| ``LOG_WGT_BUFF_SIZE`` | Int (log2) | Weight on-chip buffer in Bytes.                        |
+-----------------------+------------+--------------------------------------------------------+
| ``LOG_ACC_BUFF_SIZE`` | Int (log2) | Accumulator on-chip buffer in Bytes.                   |
+-----------------------+------------+--------------------------------------------------------+


 .. note::

    When a parameter name is preceded with ``LOG``, it means that it describes a value that can only be expressed a power of two.
    For that reason we describe these parameters by their log2 value.
    For instance, to describe an integer width of 8-bits for the input data types, we set the ``LOG_INP_WIDTH`` to be 3, which is the log2 of 8.
    Similarly, to descibe a 64kB micro-op buffer, we would set ``LOG_UOP_BUFF_SIZE`` to be 16.

We provide additional detail below regarding each parameter:

 - ``TARGET``: Can be set to ``"pynq"``, ``"ultra96"``, ``"sim"`` (fast simulator), or ``"tsim"`` (cycle accurate sim with verilator).
 - ``HW_VER``: Hardware version which increments every time the VTA hardware design changes. This parameter is used to uniquely identity hardware bitstreams.
 - ``LOG_BATCH``: Equivalent to A in multiplication of shape (A, B) x (B, C), or typically, the batch dimension of inner tensor computation.
 - ``LOG_BLOCK``: Equivalent to B and C in multiplication of shape (A, B) x (B, C), or typically, the input/output channel dimensions of the inner tensor computation.

