rocm-systems/plugin/att/att.py

#!/usr/bin/env python3
import sys

if sys.version_info[0] < 3:
    raise Exception("Must be using Python 3")

import os
import argparse
from pathlib import Path
from ctypes import *
import ctypes
from copy import deepcopy
from trace_view import view_trace
import sys
import glob
import numpy as np
from stitch import stitch
import gc
from collections import defaultdict

class PerfEvent(ctypes.Structure):
    _fields_ = [
        ("time", c_uint64),
        ("event0", c_uint16),
        ("event1", c_uint16),
        ("event2", c_uint16),
        ("event3", c_uint16),
        ("cu", c_uint8),
        ("bank", c_uint8),
    ]

    def toTuple(self):
        return (
            int(self.time),
            int(self.event0),
            int(self.event1),
            int(self.event2),
            int(self.event3),
            int(self.cu),
            int(self.bank),
        )


class CodeWrapped(ctypes.Structure):
    """ Matches CodeWrapped on the python side """
    _fields_ = [('line', ctypes.c_char_p),
                ('loc', ctypes.c_char_p),
                ('to_line', ctypes.c_int),
                ('value', ctypes.c_int),
                ('index', ctypes.c_int),
                ('line_num', ctypes.c_int),
                ('addr', ctypes.c_int64)]


class KvPair(ctypes.Structure):
    """ Matches pair<int, int> = (key, value) on the python side """
    _fields_ = [('key', ctypes.c_int),
               ('value', ctypes.c_int)]


class ReturnAssemblyInfo(ctypes.Structure):
    """ Matches ReturnAssemblyInfo on the python side """
    _fields_ = [('code', POINTER(CodeWrapped)),
                ('jumps', POINTER(KvPair)),
                ('code_len', ctypes.c_int),
                ('jumps_len', ctypes.c_int)]


class Wave(ctypes.Structure):
    _fields_ = [
        ("simd", ctypes.c_uint64),
        ("wave_id", ctypes.c_uint64),
        ("begin_time", ctypes.c_uint64),  # Begin and end cycle
        ("end_time", ctypes.c_uint64),
        # total VMEM/FLAT/LDS/SMEM instructions issued
        # total issued memory instructions
        ("num_mem_instrs", ctypes.c_uint64),
        # total issued instructions (compute + memory)
        ("num_issued_instrs", ctypes.c_uint64),
        ("num_valu_instrs", ctypes.c_uint64),
        ("num_valu_stalls", ctypes.c_uint64),
        # VMEM Pipeline: instrs and stalls
        ("num_vmem_instrs", ctypes.c_uint64),
        ("num_vmem_stalls", ctypes.c_uint64),
        # FLAT instrs and stalls
        ("num_flat_instrs", ctypes.c_uint64),
        ("num_flat_stalls", ctypes.c_uint64),
        # LDS instr and stalls
        ("num_lds_instrs", ctypes.c_uint64),
        ("num_lds_stalls", ctypes.c_uint64),
        # SCA instrs stalls
        ("num_salu_instrs", ctypes.c_uint64),
        ("num_smem_instrs", ctypes.c_uint64),
        ("num_salu_stalls", ctypes.c_uint64),
        ("num_smem_stalls", ctypes.c_uint64),
        # Branch
        ("num_branch_instrs", ctypes.c_uint64),
        ("num_branch_taken_instrs", ctypes.c_uint64),
        ("num_branch_stalls", ctypes.c_uint64),
        ("timeline_array", POINTER(ctypes.c_int64)),
        ("instructions_array", POINTER(ctypes.c_int64)),
        ("timeline_size", ctypes.c_uint64),
        ("instructions_size", ctypes.c_uint64),
    ]


class PythonWave:
    def __init__(self, source_wave):
        for property, value in Wave._fields_:
            setattr(self, property, getattr(source_wave, property))
        self.timeline_array = None
        self.instructions_array = None


# Flags :
#   IS_NAVI = 0x1
class ReturnInfo(ctypes.Structure):
    _fields_ = [
        ("num_waves", ctypes.c_uint64),
        ("wavedata", POINTER(Wave)),
        ("num_events", ctypes.c_uint64),
        ("perfevents", POINTER(PerfEvent)),
        ("occupancy", POINTER(ctypes.c_uint64)),
        ("num_occupancy", ctypes.c_uint64),
        ("flags", ctypes.c_uint64),
        ("kernel_id_addr", POINTER(ctypes.c_uint64)),
        ("num_kernel_ids", ctypes.c_uint64),
    ]


rocprofv2_att_lib = os.getenv("ROCPROFV2_ATT_LIB_PATH")
if rocprofv2_att_lib is None:
    print(
        "ATT Lib path not set. Use export ROCPROFV2_ATT_LIB_PATH=/path/to/librocprofv2_att.so"
    )
    quit()
path_to_parser = os.path.abspath(rocprofv2_att_lib)
SO = CDLL(path_to_parser)

SO.AnalyseBinary.restype = ReturnInfo
SO.AnalyseBinary.argtypes = [ctypes.c_char_p, ctypes.c_int, ctypes.c_bool]
SO.wrapped_parse_binary.argtypes = [ctypes.c_char_p, ctypes.c_char_p]
SO.wrapped_parse_binary.restype = ReturnAssemblyInfo


def parse_binary(filename, kernel=None):
    if kernel is None or kernel == "":
        kernel = ctypes.c_char_p(0)
        print("Parsing all kernels")
    else:
        with open(glob.glob(kernel)[0], "r") as file:
            kernel = file.readlines()
        print("Parsing kernel:", kernel[0].split(": ")[0])
        kernel = kernel[0].split(": ")[1].split(".kd")[0]
        kernel = str(kernel).encode("utf-8")
    filename = os.path.abspath(str(filename))
    info = SO.wrapped_parse_binary(str(filename).encode("utf-8"), kernel)

    code = []
    kernel_addr = defaultdict(lambda : "Unknown")
    last_known_function = "Unknown"
    for k in range(info.code_len):
        code_entry = info.code[k]

        line = deepcopy(code_entry.line.decode("utf-8"))
        if "; Begin " in line:
            last_known_function = line.split("; Begin ")[1]

        loc = deepcopy(code_entry.loc.decode("utf-8"))

        to_line = int(code_entry.to_line) if (code_entry.to_line >= 0) else None
        loc = loc if len(loc) > 0 else None

        # asm, inst_type, addr, loc, index, line_num, hitcount, cycles
        code.append([line, int(code_entry.value), to_line, loc, int(code_entry.index),
                    int(code_entry.line_num), int(code_entry.addr), 0, 0])

        if code[-1][-3] != 0 and len(code) > 1:
            kernel_addr[code[-1][-3]] = last_known_function

    jumps = {}
    for k in range(info.jumps_len):
        jumps[info.jumps[k].key] = info.jumps[k].value

    return code, jumps, kernel_addr


def getWaves_binary(name, shader_engine_data_dict, target_cu):
    filename = os.path.abspath(str(name))
    info = SO.AnalyseBinary(filename.encode("utf-8"), target_cu, False)

    kernel_addr = [int(info.kernel_id_addr[k]) for k in range(info.num_kernel_ids)]

    waves = [info.wavedata[k] for k in range(info.num_waves)]
    events = [deepcopy(info.perfevents[k]) for k in range(info.num_events)]
    occupancy = [int(info.occupancy[k]) for k in range(int(info.num_occupancy))]
    flags = "navi" if (info.flags & 0x1) else "vega"

    waves_python = []
    for wave in waves:
        if wave.instructions_size < 2:
            continue
        pwave = PythonWave(wave)
        pwave.timeline = [
            (wave.timeline_array[2 * k], wave.timeline_array[2 * k + 1])
            for k in range(wave.timeline_size)
        ]
        pwave.instructions = [
            tuple([wave.instructions_array[4 * k + m] for m in range(4)])
            for k in range(wave.instructions_size)
        ]
        waves_python.append(pwave)
    shader_engine_data_dict[name] = (waves_python, events, occupancy, flags, kernel_addr)


def getWaves_stitch(SIMD, code, jumps, flags, latency_map, hitcount_map, bIsAuto):
    for pwave in SIMD:
        pwave.instructions = stitch(pwave.instructions, code, jumps, flags, bIsAuto)
        if pwave.instructions is not None:
            for inst in pwave.instructions[0]:
                hitcount_map[inst[-1]] += 1
                latency_map[inst[-1]] += inst[3]


def persist(trace_file, SIMD):
    trace = Path(trace_file).name
    simds, waves = [], []
    begin_time, end_time, timeline, instructions = [], [], [], []
    mem_ins, issued_ins, valu_ins, valu_stalls = [], [], [], []
    vmem_ins, vmem_stalls, flat_ins, flat_stalls = [], [], [], []
    lds_ins, lds_stalls, salu_ins, salu_stalls = [], [], [], []
    smem_ins, smem_stalls, br_ins, br_taken_ins, br_stalls = [], [], [], [], []

    for wave in SIMD:
        if wave.instructions is None:
            continue
        simds.append(wave.simd)
        waves.append(wave.wave_id)
        begin_time.append(wave.begin_time)
        end_time.append(wave.end_time)
        mem_ins.append(wave.num_mem_instrs)
        issued_ins.append(wave.num_issued_instrs)
        valu_ins.append(wave.num_valu_instrs)
        valu_stalls.append(wave.num_valu_stalls)
        vmem_ins.append(wave.num_vmem_instrs)
        vmem_stalls.append(wave.num_vmem_stalls)
        flat_ins.append(wave.num_flat_instrs)
        flat_stalls.append(wave.num_flat_stalls)
        lds_ins.append(wave.num_lds_instrs)
        lds_stalls.append(wave.num_lds_stalls)
        salu_ins.append(wave.num_salu_instrs)
        salu_stalls.append(wave.num_salu_stalls)
        smem_ins.append(wave.num_smem_instrs)
        smem_stalls.append(wave.num_smem_stalls)
        br_ins.append(wave.num_branch_instrs)
        br_taken_ins.append(wave.num_branch_taken_instrs)
        br_stalls.append(wave.num_branch_stalls)
        timeline.append(wave.timeline)
        instructions.append(wave.instructions)

    df = {
        "name": [trace for _ in range(len(begin_time))],
        "id": [i for i in range(len(begin_time))],
        "simd": simds,
        "wave_slot": waves,
        "begin_time": begin_time,
        "end_time": end_time,
        "mem_ins": mem_ins,
        "issued_ins": issued_ins,
        "valu_ins": valu_ins,
        "valu_stalls": valu_stalls,
        "vmem_ins": vmem_ins,
        "vmem_stalls": vmem_stalls,
        "flat_ins": flat_ins,
        "flat_stalls": flat_stalls,
        "lds_ins": lds_ins,
        "lds_stalls": lds_stalls,
        "salu_ins": salu_ins,
        "salu_stalls": salu_stalls,
        "smem_ins": smem_ins,
        "smem_stalls": smem_stalls,
        "br_ins": br_ins,
        "br_taken_ins": br_taken_ins,
        "br_stalls": br_stalls,
        "timeline": timeline,
        "instructions": instructions,
    }
    return df


def mem_max(array):
    mem_dict = {}
    for SE in array:
        for wave in SE:
            for inst in wave:
                try:
                    mem_dict[inst[0]][0] = max(mem_dict[inst[0]][0], inst[1])
                except:
                    mem_dict[inst[0]] = inst[1:]
                assert mem_dict[inst[0]][1] == inst[2]

    return mem_dict


def lgk(count):
    return "lgkmcnt({0})".format(count)


def vmc(count):
    return "vmcnt({0})".format(count)


def both_cnt(count):
    return lgk(count) + " " + vmc(count)


def insert_waitcnt(flight_count, assembly_code):
    flight_count = mem_max(flight_count)
    for key in sorted(flight_count):
        line_n = key
        (
            issue_amount,
            waitcnt_amount,
        ) = flight_count[key]
        if "vmcnt" in assembly_code[line_n] and "lgkmcnt" in assembly_code[line_n]:
            counter_type = both_cnt
        elif "vmcnt" in assembly_code[line_n]:
            counter_type = vmc
        elif "lgkmcnt" in assembly_code[line_n]:
            counter_type = lgk
        else:
            print("Error: Line mismatch")
            exit(-1)

        for count in range(waitcnt_amount + 1, issue_amount):
            print("Inserted line: " + str(line_n))
            as_index = line_n - count / (issue_amount + 1)
            assembly_code[as_index] = "\ts_waitcnt {0}\t\t; Timing analysis.".format(
                counter_type(count)
            )
            as_index += 0.5 / (issue_amount + 1)
            assembly_code[as_index] = "\ts_nop 0\t\t\t\t\t\t; Counters: " + str(
                issue_amount
            )

    return assembly_code


def gen_timelines(DBFILES):
    TIMELINES = [np.zeros(int(1E6), dtype=np.float32) for k in range(5)]
    TIME_RESOLUTION = 16
    for df in DBFILES:
        for T in range(len(df["timeline"])):
            timeline = df["timeline"][T]
            time_acc = 0
            tuples3 = [(0, df["begin_time"][T])] + [(int(t[0]), int(t[1])) for t in timeline]

            for state in tuples3:
                t_end = (time_acc + state[1])//TIME_RESOLUTION
                if t_end > 1E8:
                    print("Warning: Time limit reached for ", state[0], state[1])
                    break
                elif t_end > TIMELINES[state[0]].size:
                    TIMELINES[state[0]] = np.hstack(
                        [TIMELINES[state[0]], np.zeros_like(TIMELINES[state[0]])]
                    )
                TIMELINES[state[0]][time_acc//TIME_RESOLUTION : t_end] += 1
                time_acc += state[1]
    return TIMELINES


if __name__ == "__main__":
    pathenv = os.getenv("OUTPUT_PATH")
    if pathenv is None:
        pathenv = "."
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "assembly_code", help="Path to the assembly code. Must be the first parameter."
    )
    parser.add_argument(
        "--trace_file", help="Filter for trace files", default=None, type=str
    )
    parser.add_argument(
        "--att_kernel", help="Kernel file", type=str, default=pathenv + "/*_kernel.txt"
    )
    parser.add_argument("--ports", help="Server and websocket ports, default: 8000,18000")
    parser.add_argument(
        "--mode",
        help="""ATT analysis modes:\n
                        off: Only run ATT collection, disable analysis.\n
                        file: dump json files to disk.\n
                        network: Open att server over the network.""",
        type=str,
        default="off",
    )
    args = parser.parse_args()

    CSV_MODE = False
    if args.mode.lower() == 'csv':
        CSV_MODE = True
    elif args.mode.lower() == 'file':
        args.dumpfiles = True
    elif args.mode.lower() == "network":
        args.dumpfiles = False
    else:
        print("Skipping analysis.")
        quit()

    with open(os.getenv("COUNTERS_PATH"), "r") as f:
        lines = [l.split("//")[0] for l in f.readlines()]

        EVENT_NAMES = []
        clean = lambda x: x.split("=")[1].split(" ")[0].split("\n")[0]
        for line in lines:
            if "PERFCOUNTER_ID=" in line:
                EVENT_NAMES += ["id: " + clean(line)]
            elif "att: TARGET_CU" in line:
                args.target_cu = int(clean(line))
        for line in lines:
            if "PERFCOUNTER=" in line:
                EVENT_NAMES += [clean(line).split("SQ_")[1].lower()]
    if args.target_cu is None:
        args.target_cu = 1

    att_kernel = glob.glob(args.att_kernel)

    if len(att_kernel) == 0:
        print("Could not find att output kernel:", args.att_kernel)
        exit(1)
    elif len(att_kernel) > 1:
        print("Found multiple kernel matching given filters:")
        for n, k in enumerate(att_kernel):
            print("\t", n, "->", k)

        bValid = False
        while bValid == False:
            try:
                args.att_kernel = att_kernel[int(input("Please select number: "))]
                bValid = True
            except KeyboardInterrupt:
                exit(0)
            except:
                print("Invalid option.")
    else:
        args.att_kernel = att_kernel[0]

    # Assembly parsing
    bIsAuto = False
    if args.assembly_code.lower().strip() == 'auto':
        args.assembly_code = args.att_kernel.split('_kernel.txt')[0]+'_isa.s'
        bIsAuto = True
    path = Path(args.assembly_code)
    if not path.is_file():
        print("Invalid assembly_code('{0}')!".format(args.assembly_code))
        sys.exit(1)

    # Trace Parsing
    if args.trace_file is None:
        filenames = glob.glob(args.att_kernel.split("_kernel.txt")[0] + "_*.att")
    else:
        filenames = glob.glob(args.trace_file)
    assert len(filenames) > 0

    print('Att kernel:', args.att_kernel)
    code, jumps, kern_addr = parse_binary(args.assembly_code, None if bIsAuto else args.att_kernel)

    DBFILES = []
    EVENTS = []
    OCCUPANCY = []
    GFXV = []
    analysed_filenames = []
    occupancy_filenames = []
    dispatch_kernel_names = {}
    shader_engine_data_dict = {}
    for name in filenames:
        getWaves_binary(name, shader_engine_data_dict, args.target_cu)

    gc.collect()
    latency_map = np.zeros((len(code)), dtype=np.int64)
    hitcount_map = np.zeros((len(code)), dtype=np.int32)
    for name in filenames:
        SIMD, perfevents, occupancy, gfxv, addrs = shader_engine_data_dict[name]

        for id, addr in enumerate(addrs):
            dispatch_kernel_names[id] = kern_addr[addr]
        if len(occupancy) > 16:
            OCCUPANCY.append( occupancy )
            occupancy_filenames.append(name)
        if np.sum([0]+[len(s.instructions) for s in SIMD]) == 0:
            print("No waves from", name)
            continue
        getWaves_stitch(SIMD, code, jumps, gfxv, latency_map, hitcount_map, bIsAuto)

        analysed_filenames.append(name)
        EVENTS.append(perfevents)
        DBFILES.append( persist(name, SIMD) )
        GFXV.append(gfxv)

    gc.collect()
    for k in range(len(code)):
        code[k][-2] = int(hitcount_map[k])
        code[k][-1] = int(latency_map[k])

    if CSV_MODE:
        from att_to_csv import dump_csv
        dump_csv(code)
        quit()


    gc.collect()

    drawinfo = {
        "TIMELINES": gen_timelines(DBFILES),
        "EVENTS": EVENTS,
        "EVENT_NAMES": EVENT_NAMES,
        "OCCUPANCY": OCCUPANCY,
        "ShaderNames": occupancy_filenames,
        "DispatchNames": dispatch_kernel_names,
    }
    view_trace(
        args,
        code,
        DBFILES,
        analysed_filenames,
        args.dumpfiles,
        0,
        gfxv,
        drawinfo
    )