- awaitCompletion code may do a endless spin wait for cases where we
dont submit a handler. One such case can be the hipExt*Launch API which
takes a stop event. In that case we optimize the stop event by attaching
a signal to the dispatch packet but dont submit a handler when we attach
the signal. That means if awaitCompletion() is called after that, we
would keep on waiting on command status on the host rather than simply
checking signal value.
Change-Id: Ie8bf175aeefa3f9e4299b1ae7ae9108dad67e283
[ROCm/clr commit: 561fb8a459]
We must be in protected way to get last command when calling
awaitCompletion() where lastCommand will be released and
possibly destroyed.
This can solve scope lock(notify_lock_) crash in
Event::notifyCmdQueue() with AMD_DIRECT_DISPATCH = true.
Change-Id: I4297166f912a71112f4a8945d993160ba9afdc34
[ROCm/clr commit: 749385155a]
1.Move global amd::monitor listenerLock before global
class runtime_tear_down as it will be referenced in
~RuntimeTearDown() after main(). It should be freed
later than runtime_tear_down.
2.Update Device::~Device() to SVM free coopHostcallBuffer_
before context_ is released and freed.
Change-Id: I1d21378ff463477d3238d71e5e2a1a7d6b9147ad
[ROCm/clr commit: 544c45364f]
Adding a safety check prevents an invalid memory access
if timestamps and kernelNames vectors are of different size.
The patch also moves the addKernelNames for the accumulate command
into dispatchAqlPacket function.
Change-Id: Iea0927e1253800403a1ae3f3d72de1e7d96476c3
[ROCm/clr commit: d44f44a5b1]
Fork() duplicates all system memory resources, but runtime can't duplicate
GPU resources. Thus, avoid tearDown() calls for the child process(s).
Change-Id: Id6b12bacd5112b9ad3747c218e09cba98ea1b42c
[ROCm/clr commit: ae2992ea43]
When CL-GL interop is used, a GL context are used by two or more threads at the same time, which causes race condition.
Solution:
Add lock when accessing GL functions during CL-GL interop.
Change-Id: I3a34da3cbdf74c401111cc4e3a04ad84cc52709e
[ROCm/clr commit: 0c6a952a90]
- Remove Last graph node optimization and instead submit a barrier NOP
packet always. This simplifies the code.
Change-Id: Ied443173ba47a08b6df148ac7e3ead712acda11c
[ROCm/clr commit: badf2b0880]
- No cpu wait is needed when profiler is attached, Doing this changes
the application profile when roctracer is attached.
Change-Id: I2b9cfc48d697cf5ed54bb6a240d8c12bdb079171
[ROCm/clr commit: 51e4368723]
Switch commands creation to the new suballocator to avoid
frequent expensive OS calls
Change-Id: I3597c811820e577c15708bad8b8a41aa53acc400
[ROCm/clr commit: 5b0bfdcbad]
The "optimized" version of memcpy is outdated and
was used in win32 only.
Change-Id: I7f2e0e9051e37cec95438266824b5b0025c324c6
[ROCm/clr commit: 7448113cfc]
- Create a vector to allow multiple TS to be stored in Command.
- This would mean we dont wait for entire batch in Accumulate command
to finish when we exhaust signals.
- Reduce the number of signals created at init to 64. This min value
may still need to be tuned but the KFD allows max of 4094 interrupt
signals per device.
- Store kernel names whenever they are available and not just when
profiling. If we dynamically enable profiling like for Torch, a crash
can happen if hipGraphInstantiate wasnt included in Torch profile scope
beacuse we previously entered kernel names only when profiler is
attached.
Change-Id: I34e7881a25bbc763f82fdeb3408a8ea58e1ec006
[ROCm/clr commit: c157bfb202]
- The correlation_id had random junk values which we were inserting in
the dispatch AQL packet even when no profiler was attached but if we had
a valid timestamp.
- Also make sure we dont even write the reserved2 field in the AQL
packet if no profiler attached.
Change-Id: Icdb7493198c1bb5e2d786a97e027288660854cd7
[ROCm/clr commit: 9a6ddae7b2]
It seems that due to removal of vdev()->isHandlerPending(),
Marker queued to ensure finish is not enqueued and that cause
hung at waiting event for kernel enqueue command.
Change-Id: I364abb2dcb4897b11a7eb61b5d85013b69292792
[ROCm/clr commit: eecbc2e436]
- Report kernel names for optimized graph path
- Refactor code so that we store profiling info in Accumulate command
Change-Id: Ib97735a0239aeb9fc3a50a4bb7126dd0bcadc8af
[ROCm/clr commit: b056686607]
For avx build, the start address of values_ buffer in KernelParameters is not
correct as it is computed based on 16-byte alignment.
Change-Id: I3b28ae02d2c9c0517d4a348d95ae8c6721bec83d
[ROCm/clr commit: c4f773db0b]
- Do not use extra barrier to detect graph end. If its a kernel node we
can use a completion signal for the last packet. Saves roughly 6us for
Phantom testcase per graph launch.
Change-Id: I5e0c2479d9964fbeda86ed97533f6718f49a7f91
[ROCm/clr commit: c3bd229f4f]
- Track all captured commands under a new AccumulateCommand
- Add begin() and end() methods to capture commands
- Explicit TS object now passed to certain methods because
profilingBegin() and profilingEnd() now happen separately and thus can
run into threading issues
Change-Id: I171106bdcad72b057836cb2f3fc398db3533119f
[ROCm/clr commit: 40f41f4d0b]
- Refactor code and cleanup logic for callback saving for event records
Change-Id: I5c56aa8e9c968a5bca70fb07ad1796da318e9e89
[ROCm/clr commit: 1338ff37e8]
This header file is used by ROCclr and might be used by HIP too.
ROCclr folder is a right place for this header file.
Change-Id: Ie2307331f9bd445f3c295d2ccbfc4924b0fa9510
[ROCm/clr commit: 124de0c519]
Some pytorch tests use a tracer plugin and rely on profiling information
to be reported right after hipDeviceSynchronize()
Change-Id: Ib021a1e7b1a30b3c24de72627c471810f7f7878d
[ROCm/clr commit: 5438b6362e]
Support hipExternalMemoryGetMappedMipmappedArray().
Add ImageExternalBuffer to differiate ImageBuffer.
Currently we only support tiling_optimal mode as
vulkan driver doesn't provide tiling information.
Change-Id: I7e3524cdde53e4df9f728894bcebf4bd3f58d4d9
[ROCm/clr commit: 6398f604b0]
Allocate marker only if HW event doesn't exist for the last command.
Change-Id: I3e7284202365a9c75313fb5403f0c1908ab51d1e
[ROCm/clr commit: 596b496c16]
Saleel Kudchadker
taosang2
Ioannis Assiouras
German Andryeyev
kjayapra-amd
Gu, Wangfeng
Satyanvesh Dittakavi
Jaydeep Patel
jiabaxie
Alex Xie
Anusha GodavarthySurya