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gem5/configs/example/apu_se.py
Tony Gutierrez de72e36619 gpu-compute: support in-order data delivery in GM pipe 
this patch adds an ordered response buffer to the GM pipeline
to ensure in-order data delivery. the buffer is implemented as
a stl ordered map, which sorts the request in program order by
using their sequence ID. when requests return to the GM pipeline
they are marked as done. only the oldest request may be serviced
from the ordered buffer, and only if is marked as done.

the FIFO response buffers are kept and used in OoO delivery mode
2016-10-26 22:48:28 -04:00

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#
# Copyright (c) 2015 Advanced Micro Devices, Inc.
# All rights reserved.
#
# For use for simulation and test purposes only
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its contributors
# may be used to endorse or promote products derived from this software
# without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
# Author: Sooraj Puthoor
#
import optparse, os, re
import math
import glob
import inspect
import m5
from m5.objects import *
from m5.util import addToPath
addToPath('../')
from ruby import Ruby
from common import Options
from common import Simulation
from common import GPUTLBOptions, GPUTLBConfig
########################## Script Options ########################
def setOption(parser, opt_str, value = 1):
# check to make sure the option actually exists
if not parser.has_option(opt_str):
raise Exception("cannot find %s in list of possible options" % opt_str)
opt = parser.get_option(opt_str)
# set the value
exec("parser.values.%s = %s" % (opt.dest, value))
def getOption(parser, opt_str):
# check to make sure the option actually exists
if not parser.has_option(opt_str):
raise Exception("cannot find %s in list of possible options" % opt_str)
opt = parser.get_option(opt_str)
# get the value
exec("return_value = parser.values.%s" % opt.dest)
return return_value
# Adding script options
parser = optparse.OptionParser()
Options.addCommonOptions(parser)
Options.addSEOptions(parser)
parser.add_option("--cpu-only-mode", action="store_true", default=False,
help="APU mode. Used to take care of problems in "\
"Ruby.py while running APU protocols")
parser.add_option("-k", "--kernel-files",
help="file(s) containing GPU kernel code (colon separated)")
parser.add_option("-u", "--num-compute-units", type="int", default=1,
help="number of GPU compute units"),
parser.add_option("--num-cp", type="int", default=0,
help="Number of GPU Command Processors (CP)")
parser.add_option("--benchmark-root", help="Root of benchmark directory tree")
# not super important now, but to avoid putting the number 4 everywhere, make
# it an option/knob
parser.add_option("--cu-per-sqc", type="int", default=4, help="number of CUs" \
"sharing an SQC (icache, and thus icache TLB)")
parser.add_option("--simds-per-cu", type="int", default=4, help="SIMD units" \
"per CU")
parser.add_option("--wf-size", type="int", default=64,
help="Wavefront size(in workitems)")
parser.add_option("--sp-bypass-path-length", type="int", default=4, \
help="Number of stages of bypass path in vector ALU for Single Precision ops")
parser.add_option("--dp-bypass-path-length", type="int", default=4, \
help="Number of stages of bypass path in vector ALU for Double Precision ops")
# issue period per SIMD unit: number of cycles before issuing another vector
parser.add_option("--issue-period", type="int", default=4, \
help="Number of cycles per vector instruction issue period")
parser.add_option("--glbmem-wr-bus-width", type="int", default=32, \
help="VGPR to Coalescer (Global Memory) data bus width in bytes")
parser.add_option("--glbmem-rd-bus-width", type="int", default=32, \
help="Coalescer to VGPR (Global Memory) data bus width in bytes")
# Currently we only support 1 local memory pipe
parser.add_option("--shr-mem-pipes-per-cu", type="int", default=1, \
help="Number of Shared Memory pipelines per CU")
# Currently we only support 1 global memory pipe
parser.add_option("--glb-mem-pipes-per-cu", type="int", default=1, \
help="Number of Global Memory pipelines per CU")
parser.add_option("--wfs-per-simd", type="int", default=10, help="Number of " \
"WF slots per SIMD")
parser.add_option("--vreg-file-size", type="int", default=2048,
help="number of physical vector registers per SIMD")
parser.add_option("--bw-scalor", type="int", default=0,
help="bandwidth scalor for scalability analysis")
parser.add_option("--CPUClock", type="string", default="2GHz",
help="CPU clock")
parser.add_option("--GPUClock", type="string", default="1GHz",
help="GPU clock")
parser.add_option("--cpu-voltage", action="store", type="string",
default='1.0V',
help = """CPU voltage domain""")
parser.add_option("--gpu-voltage", action="store", type="string",
default='1.0V',
help = """CPU voltage domain""")
parser.add_option("--CUExecPolicy", type="string", default="OLDEST-FIRST",
help="WF exec policy (OLDEST-FIRST, ROUND-ROBIN)")
parser.add_option("--xact-cas-mode", action="store_true",
help="enable load_compare mode (transactional CAS)")
parser.add_option("--SegFaultDebug",action="store_true",
help="checks for GPU seg fault before TLB access")
parser.add_option("--FunctionalTLB",action="store_true",
help="Assumes TLB has no latency")
parser.add_option("--LocalMemBarrier",action="store_true",
help="Barrier does not wait for writethroughs to complete")
parser.add_option("--countPages", action="store_true",
help="Count Page Accesses and output in per-CU output files")
parser.add_option("--TLB-prefetch", type="int", help = "prefetch depth for"\
"TLBs")
parser.add_option("--pf-type", type="string", help="type of prefetch: "\
"PF_CU, PF_WF, PF_PHASE, PF_STRIDE")
parser.add_option("--pf-stride", type="int", help="set prefetch stride")
parser.add_option("--numLdsBanks", type="int", default=32,
help="number of physical banks per LDS module")
parser.add_option("--ldsBankConflictPenalty", type="int", default=1,
help="number of cycles per LDS bank conflict")
parser.add_option('--fast-forward-pseudo-op', action='store_true',
help = 'fast forward using kvm until the m5_switchcpu'
' pseudo-op is encountered, then switch cpus. subsequent'
' m5_switchcpu pseudo-ops will toggle back and forth')
parser.add_option('--outOfOrderDataDelivery', action='store_true',
default=False, help='enable OoO data delivery in the GM'
' pipeline')
Ruby.define_options(parser)
#add TLB options to the parser
GPUTLBOptions.tlb_options(parser)
(options, args) = parser.parse_args()
# The GPU cache coherence protocols only work with the backing store
setOption(parser, "--access-backing-store")
# if benchmark root is specified explicitly, that overrides the search path
if options.benchmark_root:
benchmark_path = [options.benchmark_root]
else:
# Set default benchmark search path to current dir
benchmark_path = ['.']
########################## Sanity Check ########################
# Currently the gpu model requires ruby
if buildEnv['PROTOCOL'] == 'None':
fatal("GPU model requires ruby")
# Currently the gpu model requires only timing or detailed CPU
if not (options.cpu_type == "timing" or
options.cpu_type == "detailed"):
fatal("GPU model requires timing or detailed CPU")
# This file can support multiple compute units
assert(options.num_compute_units >= 1)
# Currently, the sqc (I-Cache of GPU) is shared by
# multiple compute units(CUs). The protocol works just fine
# even if sqc is not shared. Overriding this option here
# so that the user need not explicitly set this (assuming
# sharing sqc is the common usage)
n_cu = options.num_compute_units
num_sqc = int(math.ceil(float(n_cu) / options.cu_per_sqc))
options.num_sqc = num_sqc # pass this to Ruby
########################## Creating the GPU system ########################
# shader is the GPU
shader = Shader(n_wf = options.wfs_per_simd,
clk_domain = SrcClockDomain(
clock = options.GPUClock,
voltage_domain = VoltageDomain(
voltage = options.gpu_voltage)))
# GPU_RfO(Read For Ownership) implements SC/TSO memory model.
# Other GPU protocols implement release consistency at GPU side.
# So, all GPU protocols other than GPU_RfO should make their writes
# visible to the global memory and should read from global memory
# during kernal boundary. The pipeline initiates(or do not initiate)
# the acquire/release operation depending on this impl_kern_boundary_sync
# flag. This flag=true means pipeline initiates a acquire/release operation
# at kernel boundary.
if buildEnv['PROTOCOL'] == 'GPU_RfO':
shader.impl_kern_boundary_sync = False
else:
shader.impl_kern_boundary_sync = True
# Switching off per-lane TLB by default
per_lane = False
if options.TLB_config == "perLane":
per_lane = True
# List of compute units; one GPU can have multiple compute units
compute_units = []
for i in xrange(n_cu):
compute_units.append(ComputeUnit(cu_id = i, perLaneTLB = per_lane,
num_SIMDs = options.simds_per_cu,
wfSize = options.wf_size,
spbypass_pipe_length = options.sp_bypass_path_length,
dpbypass_pipe_length = options.dp_bypass_path_length,
issue_period = options.issue_period,
coalescer_to_vrf_bus_width = \
options.glbmem_rd_bus_width,
vrf_to_coalescer_bus_width = \
options.glbmem_wr_bus_width,
num_global_mem_pipes = \
options.glb_mem_pipes_per_cu,
num_shared_mem_pipes = \
options.shr_mem_pipes_per_cu,
n_wf = options.wfs_per_simd,
execPolicy = options.CUExecPolicy,
xactCasMode = options.xact_cas_mode,
debugSegFault = options.SegFaultDebug,
functionalTLB = options.FunctionalTLB,
localMemBarrier = options.LocalMemBarrier,
countPages = options.countPages,
localDataStore = \
LdsState(banks = options.numLdsBanks,
bankConflictPenalty = \
options.ldsBankConflictPenalty),
out_of_order_data_delivery =
options.outOfOrderDataDelivery))
wavefronts = []
vrfs = []
for j in xrange(options.simds_per_cu):
for k in xrange(shader.n_wf):
wavefronts.append(Wavefront(simdId = j, wf_slot_id = k,
wfSize = options.wf_size))
vrfs.append(VectorRegisterFile(simd_id=j,
num_regs_per_simd=options.vreg_file_size))
compute_units[-1].wavefronts = wavefronts
compute_units[-1].vector_register_file = vrfs
if options.TLB_prefetch:
compute_units[-1].prefetch_depth = options.TLB_prefetch
compute_units[-1].prefetch_prev_type = options.pf_type
# attach the LDS and the CU to the bus (actually a Bridge)
compute_units[-1].ldsPort = compute_units[-1].ldsBus.slave
compute_units[-1].ldsBus.master = compute_units[-1].localDataStore.cuPort
# Attach compute units to GPU
shader.CUs = compute_units
########################## Creating the CPU system ########################
options.num_cpus = options.num_cpus
# The shader core will be whatever is after the CPU cores are accounted for
shader_idx = options.num_cpus
# The command processor will be whatever is after the shader is accounted for
cp_idx = shader_idx + 1
cp_list = []
# List of CPUs
cpu_list = []
CpuClass, mem_mode = Simulation.getCPUClass(options.cpu_type)
if CpuClass == AtomicSimpleCPU:
fatal("AtomicSimpleCPU is not supported")
if mem_mode != 'timing':
fatal("Only the timing memory mode is supported")
shader.timing = True
if options.fast_forward and options.fast_forward_pseudo_op:
fatal("Cannot fast-forward based both on the number of instructions and"
" on pseudo-ops")
fast_forward = options.fast_forward or options.fast_forward_pseudo_op
if fast_forward:
FutureCpuClass, future_mem_mode = CpuClass, mem_mode
CpuClass = X86KvmCPU
mem_mode = 'atomic_noncaching'
# Leave shader.timing untouched, because its value only matters at the
# start of the simulation and because we require switching cpus
# *before* the first kernel launch.
future_cpu_list = []
# Initial CPUs to be used during fast-forwarding.
for i in xrange(options.num_cpus):
cpu = CpuClass(cpu_id = i,
clk_domain = SrcClockDomain(
clock = options.CPUClock,
voltage_domain = VoltageDomain(
voltage = options.cpu_voltage)))
cpu_list.append(cpu)
if options.fast_forward:
cpu.max_insts_any_thread = int(options.fast_forward)
if fast_forward:
MainCpuClass = FutureCpuClass
else:
MainCpuClass = CpuClass
# CPs to be used throughout the simulation.
for i in xrange(options.num_cp):
cp = MainCpuClass(cpu_id = options.num_cpus + i,
clk_domain = SrcClockDomain(
clock = options.CPUClock,
voltage_domain = VoltageDomain(
voltage = options.cpu_voltage)))
cp_list.append(cp)
# Main CPUs (to be used after fast-forwarding if fast-forwarding is specified).
for i in xrange(options.num_cpus):
cpu = MainCpuClass(cpu_id = i,
clk_domain = SrcClockDomain(
clock = options.CPUClock,
voltage_domain = VoltageDomain(
voltage = options.cpu_voltage)))
if fast_forward:
cpu.switched_out = True
future_cpu_list.append(cpu)
else:
cpu_list.append(cpu)
########################## Creating the GPU dispatcher ########################
# Dispatcher dispatches work from host CPU to GPU
host_cpu = cpu_list[0]
dispatcher = GpuDispatcher()
########################## Create and assign the workload ########################
# Check for rel_path in elements of base_list using test, returning
# the first full path that satisfies test
def find_path(base_list, rel_path, test):
for base in base_list:
if not base:
# base could be None if environment var not set
continue
full_path = os.path.join(base, rel_path)
if test(full_path):
return full_path
fatal("%s not found in %s" % (rel_path, base_list))
def find_file(base_list, rel_path):
return find_path(base_list, rel_path, os.path.isfile)
executable = find_path(benchmark_path, options.cmd, os.path.exists)
# it's common for a benchmark to be in a directory with the same
# name as the executable, so we handle that automatically
if os.path.isdir(executable):
benchmark_path = [executable]
executable = find_file(benchmark_path, options.cmd)
if options.kernel_files:
kernel_files = [find_file(benchmark_path, f)
for f in options.kernel_files.split(':')]
else:
# if kernel_files is not set, see if there's a unique .asm file
# in the same directory as the executable
kernel_path = os.path.dirname(executable)
kernel_files = glob.glob(os.path.join(kernel_path, '*.asm'))
if kernel_files:
print "Using GPU kernel code file(s)", ",".join(kernel_files)
else:
fatal("Can't locate kernel code (.asm) in " + kernel_path)
# OpenCL driver
driver = ClDriver(filename="hsa", codefile=kernel_files)
for cpu in cpu_list:
cpu.workload = LiveProcess(executable = executable,
cmd = [options.cmd] + options.options.split(),
drivers = [driver])
for cp in cp_list:
cp.workload = host_cpu.workload
if fast_forward:
for i in xrange(len(future_cpu_list)):
future_cpu_list[i].workload = cpu_list[i].workload
########################## Create the overall system ########################
# List of CPUs that must be switched when moving between KVM and simulation
if fast_forward:
switch_cpu_list = \
[(cpu_list[i], future_cpu_list[i]) for i in xrange(options.num_cpus)]
# Full list of processing cores in the system. Note that
# dispatcher is also added to cpu_list although it is
# not a processing element
cpu_list = cpu_list + [shader] + cp_list + [dispatcher]
# creating the overall system
# notice the cpu list is explicitly added as a parameter to System
system = System(cpu = cpu_list,
mem_ranges = [AddrRange(options.mem_size)],
cache_line_size = options.cacheline_size,
mem_mode = mem_mode)
if fast_forward:
system.future_cpu = future_cpu_list
system.voltage_domain = VoltageDomain(voltage = options.sys_voltage)
system.clk_domain = SrcClockDomain(clock = options.sys_clock,
voltage_domain = system.voltage_domain)
if fast_forward:
have_kvm_support = 'BaseKvmCPU' in globals()
if have_kvm_support and buildEnv['TARGET_ISA'] == "x86":
system.vm = KvmVM()
for i in xrange(len(host_cpu.workload)):
host_cpu.workload[i].useArchPT = True
host_cpu.workload[i].kvmInSE = True
else:
fatal("KvmCPU can only be used in SE mode with x86")
# configure the TLB hierarchy
GPUTLBConfig.config_tlb_hierarchy(options, system, shader_idx)
# create Ruby system
system.piobus = IOXBar(width=32, response_latency=0,
frontend_latency=0, forward_latency=0)
Ruby.create_system(options, None, system)
system.ruby.clk_domain = SrcClockDomain(clock = options.ruby_clock,
voltage_domain = system.voltage_domain)
# attach the CPU ports to Ruby
for i in range(options.num_cpus):
ruby_port = system.ruby._cpu_ports[i]
# Create interrupt controller
system.cpu[i].createInterruptController()
# Connect cache port's to ruby
system.cpu[i].icache_port = ruby_port.slave
system.cpu[i].dcache_port = ruby_port.slave
ruby_port.mem_master_port = system.piobus.slave
if buildEnv['TARGET_ISA'] == "x86":
system.cpu[i].interrupts[0].pio = system.piobus.master
system.cpu[i].interrupts[0].int_master = system.piobus.slave
system.cpu[i].interrupts[0].int_slave = system.piobus.master
if fast_forward:
system.cpu[i].itb.walker.port = ruby_port.slave
system.cpu[i].dtb.walker.port = ruby_port.slave
# attach CU ports to Ruby
# Because of the peculiarities of the CP core, you may have 1 CPU but 2
# sequencers and thus 2 _cpu_ports created. Your GPUs shouldn't be
# hooked up until after the CP. To make this script generic, figure out
# the index as below, but note that this assumes there is one sequencer
# per compute unit and one sequencer per SQC for the math to work out
# correctly.
gpu_port_idx = len(system.ruby._cpu_ports) \
- options.num_compute_units - options.num_sqc
gpu_port_idx = gpu_port_idx - options.num_cp * 2
wavefront_size = options.wf_size
for i in xrange(n_cu):
# The pipeline issues wavefront_size number of uncoalesced requests
# in one GPU issue cycle. Hence wavefront_size mem ports.
for j in xrange(wavefront_size):
system.cpu[shader_idx].CUs[i].memory_port[j] = \
system.ruby._cpu_ports[gpu_port_idx].slave[j]
gpu_port_idx += 1
for i in xrange(n_cu):
if i > 0 and not i % options.cu_per_sqc:
print "incrementing idx on ", i
gpu_port_idx += 1
system.cpu[shader_idx].CUs[i].sqc_port = \
system.ruby._cpu_ports[gpu_port_idx].slave
gpu_port_idx = gpu_port_idx + 1
# attach CP ports to Ruby
for i in xrange(options.num_cp):
system.cpu[cp_idx].createInterruptController()
system.cpu[cp_idx].dcache_port = \
system.ruby._cpu_ports[gpu_port_idx + i * 2].slave
system.cpu[cp_idx].icache_port = \
system.ruby._cpu_ports[gpu_port_idx + i * 2 + 1].slave
system.cpu[cp_idx].interrupts[0].pio = system.piobus.master
system.cpu[cp_idx].interrupts[0].int_master = system.piobus.slave
system.cpu[cp_idx].interrupts[0].int_slave = system.piobus.master
cp_idx = cp_idx + 1
# connect dispatcher to the system.piobus
dispatcher.pio = system.piobus.master
dispatcher.dma = system.piobus.slave
################# Connect the CPU and GPU via GPU Dispatcher ###################
# CPU rings the GPU doorbell to notify a pending task
# using this interface.
# And GPU uses this interface to notify the CPU of task completion
# The communcation happens through emulated driver.
# Note this implicit setting of the cpu_pointer, shader_pointer and tlb array
# parameters must be after the explicit setting of the System cpu list
if fast_forward:
shader.cpu_pointer = future_cpu_list[0]
dispatcher.cpu = future_cpu_list[0]
else:
shader.cpu_pointer = host_cpu
dispatcher.cpu = host_cpu
dispatcher.shader_pointer = shader
dispatcher.cl_driver = driver
########################## Start simulation ########################
root = Root(system=system, full_system=False)
m5.ticks.setGlobalFrequency('1THz')
if options.abs_max_tick:
maxtick = options.abs_max_tick
else:
maxtick = m5.MaxTick
# Benchmarks support work item annotations
Simulation.setWorkCountOptions(system, options)
# Checkpointing is not supported by APU model
if (options.checkpoint_dir != None or
options.checkpoint_restore != None):
fatal("Checkpointing not supported by apu model")
checkpoint_dir = None
m5.instantiate(checkpoint_dir)
# Map workload to this address space
host_cpu.workload[0].map(0x10000000, 0x200000000, 4096)
if options.fast_forward:
print "Switch at instruction count: %d" % \
cpu_list[0].max_insts_any_thread
exit_event = m5.simulate(maxtick)
if options.fast_forward:
if exit_event.getCause() == "a thread reached the max instruction count":
m5.switchCpus(system, switch_cpu_list)
print "Switched CPUS @ tick %s" % (m5.curTick())
m5.stats.reset()
exit_event = m5.simulate(maxtick - m5.curTick())
elif options.fast_forward_pseudo_op:
while exit_event.getCause() == "switchcpu":
# If we are switching *to* kvm, then the current stats are meaningful
# Note that we don't do any warmup by default
if type(switch_cpu_list[0][0]) == FutureCpuClass:
print "Dumping stats..."
m5.stats.dump()
m5.switchCpus(system, switch_cpu_list)
print "Switched CPUS @ tick %s" % (m5.curTick())
m5.stats.reset()
# This lets us switch back and forth without keeping a counter
switch_cpu_list = [(x[1], x[0]) for x in switch_cpu_list]
exit_event = m5.simulate(maxtick - m5.curTick())
print "Ticks:", m5.curTick()
print 'Exiting because ', exit_event.getCause()
sys.exit(exit_event.getCode())
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