Problem:
The existing SDMA engine selection logic had several issues:
1. Same VirtualGPU/stream could use different SDMA engines for consecutive
async copies since copy_engine_status may report engines as busy
2. Busy and Preferred engine check for every copy
3. No global tracking of which VirtualGPU uses which engine, leading to
suboptimal resource allocation
Solution:
Implemented a global SDMA engine allocator with per-stream affinity:
- Added Device::SdmaEngineAllocator to manage VirtualGPU → engine assignments
* Maintains global map of active assignments
* Enforces exclusivity: different streams use different engines (except
inter-GPU copies where preferred engines are prioritized for optimal
hardware paths like XGMI links)
* Thread-safe allocation/release with Monitor lock
- Modified VirtualGPU to cache assigned engine locally (assigned_sdma_engine_)
for fast lookup without map access on hot path
- Refactored rocrCopyBuffer() to:
1. Check local cached engine first → use if assigned
2. Call AllocateSdmaEngine() if not assigned → cache result
- Moved HSA API queries (memory_copy_engine_status, memory_get_preferred_copy_engine)
into AllocateEngine() for cleaner separation of concerns
- Engine release on HostQueue::finish() instead of only VirtualGPU destruction
* Improves engine utilization by releasing earlier
* Added virtual ReleaseSdmaEngines() method to device::VirtualDevice
- Added future path for simple round-robin allocation (kUseSimpleRR) for
next-gen GPUs with uniform SDMA bandwidth (disabled by default)
Cleanup:
- Removed selectSdmaEngine() helper (logic moved to allocator)
- Removed getSdmaRWMasks() (allocator accesses maxSdmaReadMask_/WriteMask_ directly)
- Removed unused sdmaEngineReadMask_/WriteMask_ member variables from DmaBlitManager
Benefits:
- Ensures consistent per-stream SDMA engine usage
- Prevents cross-stream contention and engine thrashing
- Prioritizes hardware-optimal paths for inter-GPU transfers
- Better resource utilization through earlier release
- Cleaner, more maintainable code structure
* Add HasExpertSchedMode device prop
* Add unit tests for HasExpertSchedMode
* Add gfx12 check for HasExpertSchedMode prop
* Update gfx major version check and test for ExpertSchedMode
* Minor fix and ROCr version bump
* Update projects/rocr-runtime/runtime/hsa-runtime/inc/hsa_ext_amd.h
* Update projects/rocr-runtime/runtime/hsa-runtime/inc/hsa_ext_amd.h
* Apply suggestion from @dayatsin-amd
* Apply suggestion from @dayatsin-amd
---------
Co-authored-by: Stefan Sokolovic <stefan.sokolovic2@amd.com>
Co-authored-by: David Yat Sin <77975354+dayatsin-amd@users.noreply.github.com>
* When writing bulk packets always invalidate packet headers, Its
possible that the CP fetcher can have multiple packets in flight. In
such cases we may end up with a malformed packet because the writes are
not complete yet CP finds a valid header.
* While reusing signals, its possible we can come across a timestamp
that can contain several signals, like when profiling a graph. Reading
timestamps from all signals can make the call severely CPU bound.
Instead cache only that signal so as to avoid the overhead for critical
path.
* clr: Use graph segment scheduling to process HIP Graphs
* Add a broader path to use capture packet capture for all topologies
* Refactor code
* Use DEBUG_HIP_GRAPH_SEGMENT_SCHEDULING to toggle new vs classic path,
Enabled by default
* clr: Few fixes and improvements
* clr: Detect complex graphs to take classic path
* Use DEBUG_HIP_GRAPH_SEGMENT_SCHEDULING=2 to force segment scheduling
path
* clr: Fix a cornercase stack corruption
* clr: Track commands of segments instead of snapshots
* clr: Fix Batch dispatch logic
* Track fence_dirty_ flag for command of other streams
* Dependency resolution markers can now accomodate dirty fence on cross
streams
---------
Co-authored-by: Ioannis Assiouras <Ioannis.Assiouras@amd.com>
Co-authored-by: Godavarthy Surya, Anusha <agodavar@amd.com>
* clr: Adjust call to ICmdBuffer::CmdCopyMemoryToImage for PAL >= 955
PAL starting versino 955 adds a new argument to
ICmdBuffer::CmdCopyMemoryToImage. Adjust teh callsite to account
fort his.
* clr: Handle new GpuUtil::TraceSessionState cases for PAL >= 939
Starting PAL API version 939, GpuUtil::TraceSessionState changes its
possible values. Adjust for it.
* clr: require PAL version 954
Bump the PAL required vesion to 954, as this is required for proper
debugger support.
* Support Windows HANDLE in interop_map_buffer
* Refactored Windows HANDLE in interop_map_buffer
* ROCr System Dependent Handle Type
* Fix for ROCr Handle Conversion Bug
* Remove Windows Header
* clr: SWDEV-547890 - Maintain an MQD for the emulated AQL queue
To simplify the shader debugger implementation, maintain the relevant
parts of the emulated AQL queue's MQD (amd_queue_t): read_dispatch_id,
write_dispatch_id, compute_tmpring_size.
With this MQD, the shader debugger can handle the emulated AQL queue
the same way it does the real AQL queue, no specialization is required.
* clr: SWDEV-547890 - Conservatively update the MQD's read_dispatch_id
The read_dispatch_id cannot be smaller than the current aql_packet_id
- hsa_queue.size for the debugger to work correctly.
The read_dispatch_id really should be updated when the CmdBuf is marked
as complete. Left a FIXME to address it in a future commit.
---------
Co-authored-by: Laurent Morichetti <laurent.morichetti@amd.com>
* clr: SWDEV-547890 - Maintain an MQD for the emulated AQL queue
To simplify the shader debugger implementation, maintain the relevant
parts of the emulated AQL queue's MQD (amd_queue_t): read_dispatch_id,
write_dispatch_id, compute_tmpring_size.
With this MQD, the shader debugger can handle the emulated AQL queue
the same way it does the real AQL queue, no specialization is required.
* clr: SWDEV-547890 - Conservatively update the MQD's read_dispatch_id
The read_dispatch_id cannot be smaller than the current aql_packet_id
- hsa_queue.size for the debugger to work correctly.
The read_dispatch_id really should be updated when the CmdBuf is marked
as complete. Left a FIXME to address it in a future commit.
SaleelK
Godavarthy Surya, Anusha
Shadi Dashmiz
Ioannis Assiouras
German Andryeyev
marandje
Sourabh U Betigeri
Maneesh Gupta
Filip Jankovic
systems-assistant[bot]
Fábio Mestre
Pengda Xie
Jin Jung
Lancelot Six
Rahul Manocha
harkgill-amd
AidanBeltonS
Todd tiantuo Li
Karthik Jayaprakash
cadolphe-amd
Victor Zhang
sluzynsk-amd
pcritchl-amd
lancesix
Rakesh Roy
Sam Ruscica
MachineTom
Ajay GunaShekar
lmoriche
Jaydeep