commit | 571f28a87ba01482c8b24b87e4d2a1909ca61f1c | [log] [tgz] |
---|---|---|
author | Ben Vanik <ben.vanik@gmail.com> | Mon Jun 05 13:06:14 2023 -0700 |
committer | GitHub <noreply@github.com> | Mon Jun 05 13:06:14 2023 -0700 |
tree | 1e53c589244c476715b848cb522f2328e5062f59 | |
parent | df71589e19fe6de33cdd03577f5ce807d0d129cd [diff] |
Adding task system utilization tracing. (#13941) Adds one new plot per executor in a process showing a 0-100% utilization value as tracked by the workers (vs the CPU usage sampled a much lower rate).  Inspecting the area under/over the curve is an easy way to spot dispatches that could have improved distribution:  (here 2x of the wall time is only 1x the utilization, meaning with perfect distribution we could go 2x faster by 2xing the utilization)
IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.
See our website for project details, user guides, and instructions on building from source.
IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!
See our website for more information.
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.