Skip to content
Snippets Groups Projects
Select Git revision
  • hpvm-release-epochs
  • main default
  • hpvm-release-epochs0
  • v2.0
  • v2.0rc
  • v1.0
  • v0.5
7 results
Blame Permalink
index.rst 1.24 KiB

Components

HPVM consists of a few relatively independent key components.

  • Patched LLVM: provides HPVM IR and a compilation infrastructure, including clang and opt.
  • HPVM code generator: a few opt passes that lowers HPVM IR to LLVM IR, which is then compiled into object code and binary.

:doc:`Compilation process of HPVM </references/hpvm-specification>` shows how these 2 components work together. In addition, there are:

  • Frontends (Keras/PyTorch): code generators in Python for lowering Keras and PyTorch DNN models into HPVM-C format.
  • Predictive tuner: an autotuner library in Python for finding approximation choices (configurations) with best performance gain within some loss of Quality of Service (QoS, such as accuracy).
  • HPVM profiler: an API in Python for measuring real performance of configurations.
  • Tensor runtime: a backend which holds implementations for some common tensor operators (such as convolution) that HPVM-C functions can be converted into.

The documentation of these components are listed below, which explains their role, usage, and other details.