| commit | 86336293a8066b396537fae117d8549460cd85fd | [log] [tgz] |
|---|---|---|
| author | bjacob <benoitjacob@google.com> | Fri Nov 10 07:02:20 2023 -0500 |
| committer | GitHub <noreply@github.com> | Fri Nov 10 07:02:20 2023 -0500 |
| tree | 1cf6141aad948821819139c75b016b0cb483cec2 | |
| parent | db7311bb45a1a12b37fc1e0ed5bc18001d7cb9fc [diff] |
Fix data race (TSan report) on worker thread startup on macOS in `iree_thread_request_affinity` (#15499)
TSan report:
```
WARNING: ThreadSanitizer: data race (pid=45817)
Read of size 4 at 0x0001084004e0 by thread T2:
#0 iree_thread_request_affinity threading_darwin.c:230 (local-task_vmvx_semaphore_submission_test:arm64+0x100078f40)
#1 iree_task_worker_main worker.c:385 (local-task_vmvx_semaphore_submission_test:arm64+0x100071594)
#2 iree_thread_start_routine threading_darwin.c:72 (local-task_vmvx_semaphore_submission_test:arm64+0x100078e3c)
Previous write of size 4 at 0x0001084004e0 by main thread:
#0 iree_thread_create threading_darwin.c:140 (local-task_vmvx_semaphore_submission_test:arm64+0x100078ca4)
#1 iree_task_worker_initialize worker.c:66 (local-task_vmvx_semaphore_submission_test:arm64+0x1000714f8)
#2 iree_task_executor_create executor.c:161 (local-task_vmvx_semaphore_submission_test:arm64+0x10006b2b0)
```
The read of `thread->mach_port` at
https://github.com/openxla/iree/blob/ccc4c3719cea467477a783f1c9e9f1fc06b4c508/runtime/src/iree/base/internal/threading_darwin.c#L230
is not ordered relatively to the write of that variable in the parent
thread after `pthread_mach_thread_np` returns:
https://github.com/openxla/iree/blob/ccc4c3719cea467477a783f1c9e9f1fc06b4c508/runtime/src/iree/base/internal/threading_darwin.c#L140
The proposed fix is that the worker thread shouldn't need to access its
own `thread->mach_port`, it can equivalently call `mach_task_self()`.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.