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apache / tvm-vta / 6c41083fd1f7b256a34dc1e591bb98a97e44479e
commit6c41083fd1f7b256a34dc1e591bb98a97e44479e[log] [tgz]
authorThierry Moreau <moreau@uw.edu>Mon Jul 22 08:31:37 2019 -0700
committerTianqi Chen <tqchen@users.noreply.github.com>Mon Jul 22 08:31:37 2019 -0700
tree5842d8bd7b8db7bcb9a69567b2a1d8a26645688a
parent8a27e115197f5961edde7054761e3503fa40e3fb [diff]
[VTA] Runtime refactor to allow for non-shared memory FPGAs (e.g. F1) (#3554)

* updated runtime to support non-shared memory FPGAs for instruction and micro-op kernels

* adding driver-defined memcpy function to handle F1 cases

* refactor to include flush/invalidate in memcpy driver function

* update tsim driver

* bug fixes

* cleanup

* pre-allocate fpga readable buffers to improve perf

* fix

* remove instruction stream address rewrite pass for micro op kernels

* fix:

* white spaces

* fix lint

* avoid signed/unsigned compilation warning

* avoid signed/unsigned compilation warning

* fix

* fix

* addressing comments

* whitespace

* moving flush/invalidate out of memmove

* clearnup

* fix

* cosmetic

* rename API

* comment fix
7 files changed
tree: 5842d8bd7b8db7bcb9a69567b2a1d8a26645688a
  1. apps/
  2. config/
  3. hardware/
  4. include/
  5. python/
  6. scripts/
  7. src/
  8. tests/
  9. tutorials/
  10. README.md
README.md

VTA: Open, Modular, Deep Learning Accelerator Stack

VTA (versatile tensor accelerator) is an open-source deep learning accelerator complemented with an end-to-end TVM-based compiler stack.

The key features of VTA include:

  • Generic, modular, open-source hardware
    • Streamlined workflow to deploy to FPGAs.
    • Simulator support to prototype compilation passes on regular workstations.
  • Driver and JIT runtime for both simulator and FPGA hardware back-end.
  • End-to-end TVM stack integration
    • Direct optimization and deployment of models from deep learning frameworks via TVM.
    • Customized and extensible TVM compiler back-end.
    • Flexible RPC support to ease deployment, and program FPGAs with the convenience of Python.

Learn more about VTA here.