Support MI 350 profiling (#632)

* Add MI 350 hardware information

* Refactor MI GPU YAML file and corresponding interface

* Add SoC file for gfx950 architecture

* Add analysis report configs for MI 350 containing existing metrics

* Add placeholder None valued metrics for previous architectures to make
  baseline comparison work

* Enable testing on MI 350

* Analysis config metric changes
    - SPI changes
        - Update metric formula for default SPI pipe counter
             - Use efficiently collected pipe wise SPI counters
        - Add SPI Wave Occupancy
        - Add Scheduler-Pipe Wave Utilization
        - Update formula for VGPR Writes
        - Add Scheduler-Pipe FIFO Full Rate
   - CPC changes
	- Add CPC SYNC FIFO Full Rate
	- Add CPC CANE Stall Rate
        - Add CPC ADC Utilization
   - SQ changes
        - Add VALU co-issue efficiency
        - Add F6F4 datatype metrics
        - Update formula for total FLOPs by adding F6F4 counters
        - Add LDS STORE / LOAD / ATOMIC metrics
        - Add LDS STORE / LOAD / ATOMIC bandwidth
        - Add LDS FIFO and TA ADDR / CMD / DATA FIFO full rates

* Collect TCP_TCP_LATENCY_sum only for gfx950 (MI 350)

* Do not inject SQ_ACCUM_PREV_HIRES unnecesarily

* Do not hardcode memory and shader clock speeds

* Write num_hbm_channels to sysinfo.csv instead of hbm_bw while profiling

* Move generate sysinfo.csv to pre processing step of profiling

* Add warnings to use --specs-correction for missing sysinfo.csv values during analysis phase

* Update CHANGELOG

* Analysis phase warning to use --specs-correction when needed

[ROCm/rocprofiler-compute commit: f9aa7be97c]

projects/rocprofiler-compute/src/utils/utils.py

@@ -43,16 +43,32 @@ import pandas as pd
 
 import config
 from utils.logger import console_debug, console_error, console_log, console_warning
-from utils.mi_gpu_spec import get_mi300_num_xcds
+from utils.mi_gpu_spec import get_num_xcds
 
 rocprof_cmd = ""
 rocprof_args = ""
+spi_pipe_counter_regexs = [r"SPI_CS\d+_(.*)", r"SPI_CSQ_P\d+_(.*)"]
 
 
 def is_tcc_channel_counter(counter):
     return counter.startswith("TCC") and counter.endswith("]")
 
 
+def is_spi_pipe_counter(counter):
+    for pattern in spi_pipe_counter_regexs:
+        if re.match(pattern, counter):
+            return True
+    return False
+
+
+def get_base_spi_pipe_counter(counter):
+    for pattern in spi_pipe_counter_regexs:
+        match = re.match(pattern, counter)
+        if match:
+            return match.group(1)
+    return ""
+
+
 def using_v1():
 
     return "ROCPROF" not in os.environ.keys() or (
@@ -571,12 +587,7 @@ def run_prof(
 
     # set required env var for mi300
     new_env = None
-    if (
-        mspec.gpu_model.lower() == "mi300x_a0"
-        or mspec.gpu_model.lower() == "mi300x_a1"
-        or mspec.gpu_model.lower() == "mi300a_a0"
-        or mspec.gpu_model.lower() == "mi300a_a1"
-    ):
+    if mspec.gpu_model.lower() not in ("mi50", "mi60", "mi210", "mi250", "mi250x"):
         new_env = os.environ.copy()
         new_env["ROCPROFILER_INDIVIDUAL_XCC_MODE"] = "1"
 
@@ -661,7 +672,7 @@ def run_prof(
     if new_env and not using_v3() and not using_v1():
         # flatten tcc for applicable mi300 input
         f = path(workload_dir + "/out/pmc_1/results_" + fbase + ".csv")
-        xcds = total_xcds(mspec.gpu_model, mspec.compute_partition)
+        xcds = get_num_xcds(mspec.gpu_model, mspec.compute_partition)
         df = flatten_tcc_info_across_xcds(f, xcds, int(mspec._l2_banks))
         df.to_csv(f, index=False)
 
@@ -1065,62 +1076,6 @@ def flatten_tcc_info_across_xcds(file, xcds, tcc_channel_per_xcd):
     return df
 
 
-def total_xcds(gpu_model, compute_partition):
-    """
-    Returns the number of xcds for a gpu model and compute_partition pair.
-    """
-
-    # For mi300 chips, return result from mi_gpu_spec
-    result = get_mi300_num_xcds(gpu_model, compute_partition)
-    if result:
-        return result
-
-    # For other systems, use manual check
-    # check MI300 has a valid compute partition
-    mi300a_model = ["mi300a_a0", "mi300a_a1"]
-    mi300x_model = ["mi300x_a0", "mi300x_a1"]
-    mi308x_model = ["mi308x"]
-    if (
-        gpu_model.lower() in mi300a_model + mi300x_model + mi308x_model
-        and compute_partition == "NA"
-    ):
-        console_error("Invalid compute partition found for {}".format(gpu_model))
-
-    if gpu_model.lower() not in mi300a_model + mi300x_model + mi308x_model:
-        return 1
-    # from the whitepaper
-    # https://www.amd.com/content/dam/amd/en/documents/instinct-tech-docs/white-papers/amd-cdna-3-white-paper.pdf
-    if compute_partition.lower() == "spx":
-        if gpu_model.lower() in mi300a_model:
-            return 6
-        if gpu_model.lower() in mi300x_model:
-            return 8
-        if gpu_model.lower() in mi308x_model:
-            return 4
-    if compute_partition.lower() == "tpx":
-        if gpu_model.lower() in mi300a_model:
-            return 2
-    if compute_partition.lower() == "dpx":
-        if gpu_model.lower() in mi300x_model:
-            return 4
-        if gpu_model.lower() in mi308x_model:
-            return 2
-    if compute_partition.lower() == "qpx":
-        if gpu_model.lower() in mi300x_model:
-            return 2
-    if compute_partition.lower() == "cpx":
-        if gpu_model.lower() in mi300x_model:
-            return 1
-        if gpu_model.lower() in mi308x_model:
-            return 1
-    # TODO implement other archs here as needed
-    console_error(
-        "Unknown compute partition / arch found for {} / {}".format(
-            compute_partition, gpu_model
-        )
-    )
-
-
 def get_submodules(package_name):
     """List all submodules for a target package"""
     import importlib