Merge remote-tracking branch 'external/develop' into sync-develop-from-external

This commit is contained in:
Alex Xu
2025-11-26 10:09:04 -05:00
21 changed files with 445 additions and 153 deletions

View File

@@ -233,7 +233,7 @@ for a complete overview of this release.
* Fixed certain output in `amd-smi monitor` when GPUs are partitioned. It fixes the issue with amd-smi monitor such as: `amd-smi monitor -Vqt`, `amd-smi monitor -g 0 -Vqt -w 1`, and `amd-smi monitor -Vqt --file /tmp/test1`. These commands will now be able to display as normal in partitioned GPU scenarios.
```{note}
See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/rocm-rel-7.1/CHANGELOG.md) for details, examples, and in-depth descriptions.
See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/rocm-rel-7.1/CHANGELOG.md#amd_smi_lib-for-rocm-710) for details, examples, and in-depth descriptions.
```
### **Composable Kernel** (1.1.0)
@@ -677,7 +677,7 @@ See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/roc
* Enabled `TCP_TCP_LATENCY` counter and associated counter for all GPUs except MI300.
* Interactive metric descriptions in TUI analyze mode.
* You can now left click on any metric cell to view detailed descriptions in the dedicated `METRIC DESCRIPTION` tab.
* Support for analysis report output as a sqlite database using ``--output-format db`` analysis mode option.
* Support for analysis report output as a SQLite database using ``--output-format db`` analysis mode option.
* `Compute Throughput` panel to TUI's `High Level Analysis` category with the following metrics: VALU FLOPs, VALU IOPs, MFMA FLOPs (F8), MFMA FLOPs (BF16), MFMA FLOPs (F16), MFMA FLOPs (F32), MFMA FLOPs (F64), MFMA FLOPs (F6F4) (in gfx950), MFMA IOPs (Int8), SALU Utilization, VALU Utilization, MFMA Utilization, VMEM Utilization, Branch Utilization, IPC
* `Memory Throughput` panel to TUI's `High Level Analysis` category with the following metrics: vL1D Cache BW, vL1D Cache Utilization, Theoretical LDS Bandwidth, LDS Utilization, L2 Cache BW, L2 Cache Utilization, L2-Fabric Read BW, L2-Fabric Write BW, sL1D Cache BW, L1I BW, Address Processing Unit Busy, Data-Return Busy, L1I-L2 Bandwidth, sL1D-L2 BW
@@ -763,7 +763,7 @@ See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/roc
* MI300A/X L2-Fabric 64B read counter may display negative values - The rocprof-compute metric 17.6.1 (Read 64B) can report negative values due to incorrect calculation when TCC_BUBBLE_sum + TCC_EA0_RDREQ_32B_sum exceeds TCC_EA0_RDREQ_sum.
* A workaround has been implemented using max(0, calculated_value) to prevent negative display values while the root cause is under investigation.
* The profile mode crashes when `--format-rocprof-output json` is selected.
* As a workaround, this option should either not be provided or should be set to `csv` instead of `json`. This issue does not affect the profiling results since both `csv` and `json` output formats lead to the same profiling data.
* As a workaround, this option should either not be provided or should be set to `csv` instead of `json`. This issue does not affect the profiling results since both `csv` and `json` output formats lead to the same profiling data.
### **ROCm Data Center Tool** (1.2.0)
@@ -804,6 +804,14 @@ See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/roc
- Updated PAPI module to v7.2.0b2.
- ROCprofiler-SDK is now used for tracing OMPT API calls.
#### Known issues
* Profiling PyTorch and other AI workloads might fail because it is unable to find the libraries in the default linker path. As a workaround, you need to explicitly add the library path to ``LD_LIBRARY_PATH``. For example, when using PyTorch with Python 3.10, add the following to the environment:
```
export LD_LIBRARY_PATH=:/opt/venv/lib/python3.10/site-packages/torch/lib:$LD_LIBRARY_PATH
```
### **rocPRIM** (4.1.0)
#### Added
@@ -881,17 +889,12 @@ As of ROCm 7.0, the internal error state is cleared on each call to `hipGetLastE
### **rocSOLVER** (3.31.0)
#### Added
* Hybrid computation support for existing routines: STEQR
#### Optimized
Improved the performance of:
* BDSQR and downstream functions such as GESVD.
* STEQR and downstream functions such as SYEV/HEEV.
* LARFT and downstream functions such as GEQR2 and GEQRF.
* LARF, LARFT, GEQR2, and downstream functions such as GEQRF.
* STEDC and divide and conquer Eigensolvers.
### **rocSPARSE** (4.1.0)