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# Authors: Andreas Hansson

import gzip
import optparse
import os

import m5
from m5.objects import *
from m5.util import addToPath
from m5.stats import periodicStatDump

addToPath('../')
from common import MemConfig

addToPath('../../util')
import protolib

# this script is helpful to observe the memory latency for various
# levels in a cache hierarchy, and various cache and memory
# configurations, in essence replicating the lmbench lat_mem_rd thrash
# behaviour

# import the packet proto definitions, and if they are not found,
# attempt to generate them automatically
try:
    import packet_pb2
except:
    print "Did not find packet proto definitions, attempting to generate"
    from subprocess import call
    error = call(['protoc', '--python_out=configs/dram',
                  '--proto_path=src/proto', 'src/proto/packet.proto'])
    if not error:
        print "Generated packet proto definitions"

        try:
            import google.protobuf
        except:
            print "Please install the Python protobuf module"
            exit(-1)

        import packet_pb2
    else:
        print "Failed to import packet proto definitions"
        exit(-1)

parser = optparse.OptionParser()

parser.add_option("--mem-type", type="choice", default="DDR3_1600_8x8",
                  choices=MemConfig.mem_names(),
                  help = "type of memory to use")
parser.add_option("--mem-size", action="store", type="string",
                  default="16MB",
                  help="Specify the memory size")
parser.add_option("--reuse-trace", action="store_true",
                  help="Prevent generation of traces and reuse existing")

(options, args) = parser.parse_args()

if args:
    print "Error: script doesn't take any positional arguments"
    sys.exit(1)

# start by creating the system itself, using a multi-layer 2.0 GHz
# crossbar, delivering 64 bytes / 3 cycles (one header cycle) which
# amounts to 42.7 GByte/s per layer and thus per port
system = System(membus = SystemXBar(width = 32))
system.clk_domain = SrcClockDomain(clock = '2.0GHz',
                                   voltage_domain =
                                   VoltageDomain(voltage = '1V'))

mem_range = AddrRange(options.mem_size)
system.mem_ranges = [mem_range]

# do not worry about reserving space for the backing store
system.mmap_using_noreserve = True

# currently not exposed as command-line options, set here for now
options.mem_channels = 1
options.mem_ranks = 1
options.external_memory_system = 0
options.tlm_memory = 0
options.elastic_trace_en = 0

MemConfig.config_mem(options, system)

# there is no point slowing things down by saving any data
for ctrl in system.mem_ctrls:
    ctrl.null = True

    # the following assumes that we are using the native DRAM
    # controller, check to be sure
    if isinstance(ctrl, m5.objects.DRAMCtrl):
        # make the DRAM refresh interval sufficiently infinite to avoid
        # latency spikes
        ctrl.tREFI = '100s'

# use the same concept as the utilisation sweep, and print the config
# so that we can later read it in
cfg_file_name = os.path.join(m5.options.outdir, "lat_mem_rd.cfg")
cfg_file = open(cfg_file_name, 'w')

# set an appropriate burst length in bytes
burst_size = 64
system.cache_line_size = burst_size

# lazy version to check if an integer is a power of two
def is_pow2(num):
    return num != 0 and ((num & (num - 1)) == 0)

# assume we start every range at 0
max_range = int(mem_range.end)

# start at a size of 4 kByte, and go up till we hit the max, increase
# the step every time we hit a power of two
min_range = 4096
ranges = [min_range]
step = 1024

while ranges[-1] < max_range:
    new_range = ranges[-1] + step
    if is_pow2(new_range):
        step *= 2
    ranges.append(new_range)

# how many times to repeat the measurement for each data point
iterations = 2

# 150 ns in ticks, this is choosen to be high enough that transactions
# do not pile up in the system, adjust if needed
itt = 150 * 1000

# for every data point, we create a trace containing a random address
# sequence, so that we can play back the same sequence for warming and
# the actual measurement
def create_trace(filename, max_addr, burst_size, itt):
    try:
        proto_out = gzip.open(filename, 'wb')
    except IOError:
        print "Failed to open ", filename, " for writing"
        exit(-1)

    # write the magic number in 4-byte Little Endian, similar to what
    # is done in src/proto/protoio.cc
    proto_out.write("gem5")

    # add the packet header
    header = packet_pb2.PacketHeader()
    header.obj_id = "lat_mem_rd for range 0:" + str(max_addr)
    # assume the default tick rate (1 ps)
    header.tick_freq = 1000000000000
    protolib.encodeMessage(proto_out, header)

    # create a list of every single address to touch
    addrs = range(0, max_addr, burst_size)

    import random
    random.shuffle(addrs)

    tick = 0

    # create a packet we can re-use for all the addresses
    packet = packet_pb2.Packet()
    # ReadReq is 1 in src/mem/packet.hh Command enum
    packet.cmd = 1
    packet.size = int(burst_size)

    for addr in addrs:
        packet.tick = long(tick)
        packet.addr = long(addr)
        protolib.encodeMessage(proto_out, packet)
        tick = tick + itt

    proto_out.close()

# this will take a while, so keep the user informed
print "Generating traces, please wait..."

nxt_range = 0
nxt_state = 0
period = long(itt * (max_range / burst_size))

# now we create the states for each range
for r in ranges:
    filename = os.path.join(m5.options.outdir,
                            'lat_mem_rd%d.trc.gz' % nxt_range)

    if not options.reuse_trace:
        # create the actual random trace for this range
        create_trace(filename, r, burst_size, itt)

    # the warming state
    cfg_file.write("STATE %d %d TRACE %s 0\n" %
                   (nxt_state, period, filename))
    nxt_state = nxt_state + 1

    # the measuring states
    for i in range(iterations):
        cfg_file.write("STATE %d %d TRACE %s 0\n" %
                       (nxt_state, period, filename))
        nxt_state = nxt_state + 1

    nxt_range = nxt_range + 1

cfg_file.write("INIT 0\n")

# go through the states one by one
for state in range(1, nxt_state):
    cfg_file.write("TRANSITION %d %d 1\n" % (state - 1, state))

cfg_file.write("TRANSITION %d %d 1\n" % (nxt_state - 1, nxt_state - 1))

cfg_file.close()

# create a traffic generator, and point it to the file we just created
system.tgen = TrafficGen(config_file = cfg_file_name,
                         progress_check = '10s')

# add a communication monitor
system.monitor = CommMonitor()
system.monitor.footprint = MemFootprintProbe()

# connect the traffic generator to the system
system.tgen.port = system.monitor.slave

# create the actual cache hierarchy, for now just go with something
# basic to explore some of the options
from common.Caches import *

# a starting point for an L3 cache
class L3Cache(Cache):
    assoc = 16
    hit_latency = 40
    response_latency = 40
    mshrs = 32
    tgts_per_mshr = 12
    write_buffers = 16

# note that everything is in the same clock domain, 2.0 GHz as
# specified above
system.l1cache = L1_DCache(size = '64kB')
system.monitor.master = system.l1cache.cpu_side

system.l2cache = L2Cache(size = '512kB', writeback_clean = True)
system.l2cache.xbar = L2XBar()
system.l1cache.mem_side = system.l2cache.xbar.slave
system.l2cache.cpu_side = system.l2cache.xbar.master

# make the L3 mostly exclusive, and correspondingly ensure that the L2
# writes back also clean lines to the L3
system.l3cache = L3Cache(size = '4MB', clusivity = 'mostly_excl')
system.l3cache.xbar = L2XBar()
system.l2cache.mem_side = system.l3cache.xbar.slave
system.l3cache.cpu_side = system.l3cache.xbar.master
system.l3cache.mem_side = system.membus.slave

# connect the system port even if it is not used in this example
system.system_port = system.membus.slave

# every period, dump and reset all stats
periodicStatDump(period)

# run Forrest, run!
root = Root(full_system = False, system = system)
root.system.mem_mode = 'timing'

m5.instantiate()
m5.simulate(nxt_state * period)

# print all we need to make sense of the stats output
print "lat_mem_rd with %d iterations, ranges:" % iterations
for r in ranges:
    print r