Datatype selection option for roofline (#624)

Added command line option to specify which datatype(s) to capture into the roofline PDF(s).
All datatypes are still collected by roofline call if applicable, but only specific datatypes are plotted into PDF outputs. Will dump out all datatypes into one graph, but separate FP from Int into two graphs if needed. Will skip datatype and give error message if the datatype is not valid on a particular gpu arch.
Default is FP32

Reworked roofline calls and plotting to be general enough such that any new datatypes added into rocm-amdgpu-bench can easily be reflected in rocprof-compute with simple modifications in roofline_calc.py.

Adjusted ctest to reflect expected default pdf outputs from roofline.

---------

Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com>

[ROCm/rocprofiler-compute commit: a492e92034]

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

@@ -41,7 +41,17 @@ FONT_SIZE = 16
 FONT_COLOR = "black"
 FONT_WEIGHT = "bold"
 
-SUPPORTED_SOC = ["mi200", "mi300"]
+# SUPPORTED_DATATYPES table is based on datatype support in rocm-amdgpu-bench repository
+# Indicates which datatypes per gpu arch can be generated by the roofline binary
+SUPPORTED_DATATYPES = {
+    "gfx90a": ["FP16", "BF16", "FP32", "FP64", "I8"],  # Unsupported: F8
+    "gfx940": ["FP8", "FP16", "FP32", "FP64"],  # Unsupported: BF16, I8
+    "gfx941": ["FP8", "FP16", "FP32", "FP64"],  # Unsupported: BF16, I8
+    "gfx942": ["FP8", "FP16", "FP32", "FP64"],  # Unsupported: BF16, I8
+}
+
+PEAK_OPS_DATATYPES = ["FP8", "FP32", "FP64"]
+MFMA_DATATYPES = ["FP8", "FP16", "BF16", "FP32", "FP64", "I8"]
 
 TOP_N = 10
 
@@ -106,31 +116,25 @@ def calc_ceilings(roofline_parameters, dtype, benchmark_data):
 
     x1 = y1 = x2 = y2 = -1
     x1_mfma = y1_mfma = x2_mfma = y2_mfma = -1
-    target_precision = dtype[2:]
 
-    if dtype != "FP16" and dtype != "I8":
-        peakOps = float(benchmark_data[dtype + "Flops"][roofline_parameters["device_id"]])
+    ops_flops = "Ops" if (dtype[:1] == "I") else "Flops"
+
+    if dtype in PEAK_OPS_DATATYPES:
+        peakOps = float(
+            benchmark_data[dtype + "{}".format(ops_flops)][
+                roofline_parameters["device_id"]
+            ]
+        )
     for i in range(0, len(cacheHierarchy)):
         # Plot BW line
         console_debug("roofline", "Current cache level is %s" % cacheHierarchy[i])
         curr_bw = cacheHierarchy[i] + "Bw"
         peakBw = float(benchmark_data[curr_bw][roofline_parameters["device_id"]])
 
-        if dtype == "I8":
-            peakMFMA = float(
-                benchmark_data["MFMAI8Ops"][roofline_parameters["device_id"]]
-            )
-        else:
-            peakMFMA = float(
-                benchmark_data["MFMAF{}Flops".format(target_precision)][
-                    roofline_parameters["device_id"]
-                ]
-            )
-
         x1 = float(XMIN)
         y1 = float(XMIN) * peakBw
-        # Note: No reg peakOps for FP16 or INT8
-        if dtype != "FP16" and dtype != "I8":
+
+        if dtype in PEAK_OPS_DATATYPES:
             x2 = peakOps / peakBw
             y2 = peakOps
 
@@ -138,8 +142,16 @@ def calc_ceilings(roofline_parameters, dtype, benchmark_data):
             x1_mfma = peakOps / peakBw
             y1_mfma = peakOps
 
-        x2_mfma = peakMFMA / peakBw
-        y2_mfma = peakMFMA
+        if dtype in MFMA_DATATYPES:
+            target_precision = (dtype) if (dtype[:1] == "I") else ("F" + dtype[2:])
+
+            peakMFMA = float(
+                benchmark_data["MFMA{}{}".format(target_precision, ops_flops)][
+                    roofline_parameters["device_id"]
+                ]
+            )
+            x2_mfma = peakMFMA / peakBw
+            y2_mfma = peakMFMA
 
         # These are the points to use:
         console_debug("roofline", "coordinate points:")
@@ -153,8 +165,7 @@ def calc_ceilings(roofline_parameters, dtype, benchmark_data):
     # -------------------------------------------------------------------------------------
     #                                     Plot computing roof
     # -------------------------------------------------------------------------------------
-    # Note: No FMA roof for FP16 or INT8
-    if dtype != "FP16" and dtype != "I8":
+    if dtype in PEAK_OPS_DATATYPES:
         # Plot FMA roof
         x0 = XMAX
         if x2 < x0:
@@ -166,9 +177,7 @@ def calc_ceilings(roofline_parameters, dtype, benchmark_data):
         graphPoints["valu"].append(peakOps)
 
     # Plot MFMA roof
-    if (
-        x1_mfma != -1 or dtype == "FP16" or dtype == "I8"
-    ):  # assert that mfma has been assigned
+    if x1_mfma != -1 or (dtype in MFMA_DATATYPES):  # assert that mfma has been assigned
         x0_mfma = XMAX
         if x2_mfma < x0_mfma:
             x0_mfma = x2_mfma
@@ -206,6 +215,8 @@ def calc_ai(mspec, sort_type, ret_df):
     at_end = False
     next_kernelName = ""
 
+    supported_dt = SUPPORTED_DATATYPES[mspec.gpu_arch]
+
     for idx in df.index:
         # CASE: Top kernels
         # Calculate + append AI data if
@@ -251,7 +262,7 @@ def calc_ai(mspec, sort_type, ret_df):
                 + (df["SQ_INSTS_VALU_MFMA_MOPS_F32"][idx] * 512)
                 + (df["SQ_INSTS_VALU_MFMA_MOPS_F64"][idx] * 512)
             )
-            if mspec.gpu_series != "MI200":
+            if "FP8" in supported_dt:
                 total_flops += df["SQ_INSTS_VALU_MFMA_MOPS_F8"][idx] * 512
         except KeyError:
             console_debug(
@@ -291,7 +302,7 @@ def calc_ai(mspec, sort_type, ret_df):
             pass
 
         try:
-            if mspec.gpu_series != "MI200":
+            if "FP8" in supported_dt:
                 mfma_flops_f8 += df["SQ_INSTS_VALU_MFMA_MOPS_F8"][idx] * 512
             mfma_flops_f16 += df["SQ_INSTS_VALU_MFMA_MOPS_F16"][idx] * 512
             mfma_flops_bf16 += df["SQ_INSTS_VALU_MFMA_MOPS_BF16"][idx] * 512