# Copyright (c) 2015 Advanced Micro Devices, Inc. # All rights reserved. # # 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. import argparse import getpass import glob import inspect import math import os import re import m5 from m5.objects import * from m5.util import addToPath from gem5.isas import ISA from gem5.runtime import get_supported_isas addToPath("../") import hsaTopology from common import ( FileSystemConfig, GPUTLBConfig, GPUTLBOptions, Options, Simulation, ) from ruby import Ruby # Adding script options parser = argparse.ArgumentParser() Options.addCommonOptions(parser) Options.addSEOptions(parser) parser.add_argument( "--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_argument( "-u", "--num-compute-units", type=int, default=4, help="number of GPU compute units", ), parser.add_argument( "--num-cp", type=int, default=0, help="Number of GPU Command Processors (CP)", ) parser.add_argument( "--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_argument( "--cu-per-sqc", type=int, default=4, help="number of CUssharing an SQC (icache, and thus icache TLB)", ) parser.add_argument( "--cu-per-scalar-cache", type=int, default=4, help="Number of CUs sharing a scalar cache", ) parser.add_argument( "--simds-per-cu", type=int, default=4, help="SIMD unitsper CU" ) parser.add_argument( "--cu-per-sa", type=int, default=4, help="Number of CUs per shader array. This must be a " "multiple of options.cu-per-sqc and options.cu-per-scalar", ) parser.add_argument( "--sa-per-complex", type=int, default=1, help="Number of shader arrays per complex", ) parser.add_argument( "--num-gpu-complexes", type=int, default=1, help="Number of GPU complexes" ) parser.add_argument( "--wf-size", type=int, default=64, help="Wavefront size(in workitems)" ) parser.add_argument( "--sp-bypass-path-length", type=int, default=4, help="Number of stages of bypass path in vector ALU for " "Single Precision ops", ) parser.add_argument( "--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_argument( "--issue-period", type=int, default=4, help="Number of cycles per vector instruction issue period", ) parser.add_argument( "--glbmem-wr-bus-width", type=int, default=32, help="VGPR to Coalescer (Global Memory) data bus width in bytes", ) parser.add_argument( "--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_argument( "--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_argument( "--glb-mem-pipes-per-cu", type=int, default=1, help="Number of Global Memory pipelines per CU", ) parser.add_argument( "--wfs-per-simd", type=int, default=10, help="Number of WF slots per SIMD", ) parser.add_argument( "--registerManagerPolicy", type=str, default="static", help="Register manager policy", ) parser.add_argument( "--vreg-file-size", type=int, default=2048, help="number of physical vector registers per SIMD", ) parser.add_argument( "--vreg-min-alloc", type=int, default=4, help="Minimum number of registers that can be allocated " "from the VRF. The total number of registers will be " "aligned to this value.", ) parser.add_argument( "--sreg-file-size", type=int, default=2048, help="number of physical vector registers per SIMD", ) parser.add_argument( "--sreg-min-alloc", type=int, default=4, help="Minimum number of registers that can be allocated " "from the SRF. The total number of registers will be " "aligned to this value.", ) parser.add_argument( "--bw-scalor", type=int, default=0, help="bandwidth scalor for scalability analysis", ) parser.add_argument("--CPUClock", type=str, default="2GHz", help="CPU clock") parser.add_argument("--gpu-clock", type=str, default="1GHz", help="GPU clock") parser.add_argument( "--cpu-voltage", action="store", type=str, default="1.0V", help="""CPU voltage domain""", ) parser.add_argument( "--gpu-voltage", action="store", type=str, default="1.0V", help="""CPU voltage domain""", ) parser.add_argument( "--CUExecPolicy", type=str, default="OLDEST-FIRST", help="WF exec policy (OLDEST-FIRST, ROUND-ROBIN)", ) parser.add_argument( "--SegFaultDebug", action="store_true", help="checks for GPU seg fault before TLB access", ) parser.add_argument( "--FunctionalTLB", action="store_true", help="Assumes TLB has no latency" ) parser.add_argument( "--LocalMemBarrier", action="store_true", help="Barrier does not wait for writethroughs to complete", ) parser.add_argument( "--countPages", action="store_true", help="Count Page Accesses and output in per-CU output files", ) parser.add_argument( "--max-cu-tokens", type=int, default=4, help="Number of coalescer tokens per CU", ) parser.add_argument( "--vrf_lm_bus_latency", type=int, default=1, help="Latency while accessing shared memory", ) parser.add_argument( "--mem-req-latency", type=int, default=50, help="Latency for requests from the cu to ruby.", ) parser.add_argument( "--mem-resp-latency", type=int, default=50, help="Latency for responses from ruby to the cu.", ) parser.add_argument( "--scalar-mem-req-latency", type=int, default=50, help="Latency for scalar requests from the cu to ruby.", ) parser.add_argument( "--scalar-mem-resp-latency", type=int, # Set to 0 as the scalar cache response path does not model # response latency yet and this parameter is currently not used default=0, help="Latency for scalar responses from ruby to the cu.", ) parser.add_argument("--TLB-prefetch", type=int, help="prefetch depth for TLBs") parser.add_argument( "--pf-type", type=str, help="type of prefetch: PF_CU, PF_WF, PF_PHASE, PF_STRIDE", ) parser.add_argument("--pf-stride", type=int, help="set prefetch stride") parser.add_argument( "--numLdsBanks", type=int, default=32, help="number of physical banks per LDS module", ) parser.add_argument( "--ldsBankConflictPenalty", type=int, default=1, help="number of cycles per LDS bank conflict", ) parser.add_argument( "--lds-size", type=int, default=65536, help="Size of the LDS in bytes" ) parser.add_argument( "--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_argument( "--num-hw-queues", type=int, default=10, help="number of hw queues in packet processor", ) parser.add_argument( "--reg-alloc-policy", type=str, default="dynamic", help="register allocation policy (simple/dynamic)", ) parser.add_argument( "--dgpu", action="store_true", default=False, help="Configure the system as a dGPU instead of an APU. " "The dGPU config has its own local memory pool and is not " "coherent with the host through hardware. Data is " "transfered from host to device memory using runtime calls " "that copy data over a PCIe-like IO bus.", ) # Mtype option # -- 1 1 1 C_RW_S (Cached-ReadWrite-Shared) # -- 1 1 0 C_RW_US (Cached-ReadWrite-Unshared) # -- 1 0 1 C_RO_S (Cached-ReadOnly-Shared) # -- 1 0 0 C_RO_US (Cached-ReadOnly-Unshared) # -- 0 1 x UC_L2 (Uncached_GL2) # -- 0 0 x UC_All (Uncached_All_Load) # default value: 5/C_RO_S (only allow caching in GL2 for read. Shared) parser.add_argument( "--m-type", type=int, default=5, help="Default Mtype for GPU memory accesses. This is the " "value used for all memory accesses on an APU and is the " "default mode for dGPU unless explicitly overwritten by " "the driver on a per-page basis. Valid values are " "between 0-7", ) parser.add_argument( "--gfx-version", type=str, default="gfx801", choices=GfxVersion.vals, help="Gfx version for gpuNote: gfx902 is not fully supported by ROCm", ) Ruby.define_options(parser) # add TLB options to the parser GPUTLBOptions.tlb_options(parser) args = parser.parse_args() # The GPU cache coherence protocols only work with the backing store args.access_backing_store = True # if benchmark root is specified explicitly, that overrides the search path if args.benchmark_root: benchmark_path = [args.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 (args.cpu_type == "TimingSimpleCPU" or args.cpu_type == "DerivO3CPU"): fatal("GPU model requires TimingSimpleCPU or DerivO3CPU") # This file can support multiple compute units assert args.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 = args.num_compute_units num_sqc = int(math.ceil(float(n_cu) / args.cu_per_sqc)) args.num_sqc = num_sqc # pass this to Ruby num_scalar_cache = int(math.ceil(float(n_cu) / args.cu_per_scalar_cache)) args.num_scalar_cache = num_scalar_cache print( "Num SQC = ", num_sqc, "Num scalar caches = ", num_scalar_cache, "Num CU = ", n_cu, ) ########################## Creating the GPU system ######################## # shader is the GPU shader = Shader( n_wf=args.wfs_per_simd, clk_domain=SrcClockDomain( clock=args.gpu_clock, voltage_domain=VoltageDomain(voltage=args.gpu_voltage), ), ) # VIPER GPU protocol implements release consistency at GPU side. So, # we 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 # these impl_kern_launch_rel and impl_kern_end_rel flags. The flag=true # means pipeline initiates a acquire/release operation at kernel launch/end. # VIPER protocol is write-through based, and thus only impl_kern_launch_acq # needs to set. if buildEnv["PROTOCOL"] == "GPU_VIPER": shader.impl_kern_launch_acq = True shader.impl_kern_end_rel = False else: shader.impl_kern_launch_acq = True shader.impl_kern_end_rel = True # Switching off per-lane TLB by default per_lane = False if args.TLB_config == "perLane": per_lane = True # List of compute units; one GPU can have multiple compute units compute_units = [] for i in range(n_cu): compute_units.append( ComputeUnit( cu_id=i, perLaneTLB=per_lane, num_SIMDs=args.simds_per_cu, wf_size=args.wf_size, spbypass_pipe_length=args.sp_bypass_path_length, dpbypass_pipe_length=args.dp_bypass_path_length, issue_period=args.issue_period, coalescer_to_vrf_bus_width=args.glbmem_rd_bus_width, vrf_to_coalescer_bus_width=args.glbmem_wr_bus_width, num_global_mem_pipes=args.glb_mem_pipes_per_cu, num_shared_mem_pipes=args.shr_mem_pipes_per_cu, n_wf=args.wfs_per_simd, execPolicy=args.CUExecPolicy, debugSegFault=args.SegFaultDebug, functionalTLB=args.FunctionalTLB, localMemBarrier=args.LocalMemBarrier, countPages=args.countPages, max_cu_tokens=args.max_cu_tokens, vrf_lm_bus_latency=args.vrf_lm_bus_latency, mem_req_latency=args.mem_req_latency, mem_resp_latency=args.mem_resp_latency, scalar_mem_req_latency=args.scalar_mem_req_latency, scalar_mem_resp_latency=args.scalar_mem_resp_latency, localDataStore=LdsState( banks=args.numLdsBanks, bankConflictPenalty=args.ldsBankConflictPenalty, size=args.lds_size, ), ) ) wavefronts = [] vrfs = [] vrf_pool_mgrs = [] srfs = [] srf_pool_mgrs = [] for j in range(args.simds_per_cu): for k in range(shader.n_wf): wavefronts.append( Wavefront(simdId=j, wf_slot_id=k, wf_size=args.wf_size) ) if args.reg_alloc_policy == "simple": vrf_pool_mgrs.append( SimplePoolManager( pool_size=args.vreg_file_size, min_alloc=args.vreg_min_alloc, ) ) srf_pool_mgrs.append( SimplePoolManager( pool_size=args.sreg_file_size, min_alloc=args.vreg_min_alloc, ) ) elif args.reg_alloc_policy == "dynamic": vrf_pool_mgrs.append( DynPoolManager( pool_size=args.vreg_file_size, min_alloc=args.vreg_min_alloc, ) ) srf_pool_mgrs.append( DynPoolManager( pool_size=args.sreg_file_size, min_alloc=args.vreg_min_alloc, ) ) vrfs.append( VectorRegisterFile( simd_id=j, wf_size=args.wf_size, num_regs=args.vreg_file_size ) ) srfs.append( ScalarRegisterFile( simd_id=j, wf_size=args.wf_size, num_regs=args.sreg_file_size ) ) compute_units[-1].wavefronts = wavefronts compute_units[-1].vector_register_file = vrfs compute_units[-1].scalar_register_file = srfs compute_units[-1].register_manager = RegisterManager( policy=args.registerManagerPolicy, vrf_pool_managers=vrf_pool_mgrs, srf_pool_managers=srf_pool_mgrs, ) if args.TLB_prefetch: compute_units[-1].prefetch_depth = args.TLB_prefetch compute_units[-1].prefetch_prev_type = args.pf_type # attach the LDS and the CU to the bus (actually a Bridge) compute_units[-1].ldsPort = compute_units[-1].ldsBus.cpu_side_port compute_units[-1].ldsBus.mem_side_port = compute_units[ -1 ].localDataStore.cuPort # Attach compute units to GPU shader.CUs = compute_units ########################## Creating the CPU system ######################## # The shader core will be whatever is after the CPU cores are accounted for shader_idx = args.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(args.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 args.fast_forward and args.fast_forward_pseudo_op: fatal( "Cannot fast-forward based both on the number of instructions and" " on pseudo-ops" ) fast_forward = args.fast_forward or args.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 range(args.num_cpus): cpu = CpuClass( cpu_id=i, clk_domain=SrcClockDomain( clock=args.CPUClock, voltage_domain=VoltageDomain(voltage=args.cpu_voltage), ), ) cpu_list.append(cpu) if args.fast_forward: cpu.max_insts_any_thread = int(args.fast_forward) if fast_forward: MainCpuClass = FutureCpuClass else: MainCpuClass = CpuClass # CPs to be used throughout the simulation. for i in range(args.num_cp): cp = MainCpuClass( cpu_id=args.num_cpus + i, clk_domain=SrcClockDomain( clock=args.CPUClock, voltage_domain=VoltageDomain(voltage=args.cpu_voltage), ), ) cp_list.append(cp) # Main CPUs (to be used after fast-forwarding if fast-forwarding is specified). for i in range(args.num_cpus): cpu = MainCpuClass( cpu_id=i, clk_domain=SrcClockDomain( clock=args.CPUClock, voltage_domain=VoltageDomain(voltage=args.cpu_voltage), ), ) if fast_forward: cpu.switched_out = True future_cpu_list.append(cpu) else: cpu_list.append(cpu) host_cpu = cpu_list[0] hsapp_gpu_map_vaddr = 0x200000000 hsapp_gpu_map_size = 0x1000 hsapp_gpu_map_paddr = int(Addr(args.mem_size)) if args.dgpu: # Default --m-type for dGPU is write-back gl2 with system coherence # (coherence at the level of the system directory between other dGPUs and # CPUs) managed by kernel boundary flush operations targeting the gl2. args.m_type = 6 # HSA kernel mode driver # dGPUPoolID is 0 because we only have one memory pool gpu_driver = GPUComputeDriver( filename="kfd", isdGPU=args.dgpu, gfxVersion=args.gfx_version, dGPUPoolID=0, m_type=args.m_type, ) renderDriNum = 128 render_driver = GPURenderDriver(filename=f"dri/renderD{renderDriNum}") # Creating the GPU kernel launching components: that is the HSA # packet processor (HSAPP), GPU command processor (CP), and the # dispatcher. gpu_hsapp = HSAPacketProcessor( pioAddr=hsapp_gpu_map_paddr, numHWQueues=args.num_hw_queues ) dispatcher = GPUDispatcher() gpu_cmd_proc = GPUCommandProcessor(hsapp=gpu_hsapp, dispatcher=dispatcher) gpu_driver.device = gpu_cmd_proc shader.dispatcher = dispatcher shader.gpu_cmd_proc = gpu_cmd_proc # 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(f"{rel_path} not found in {base_list}") def find_file(base_list, rel_path): return find_path(base_list, rel_path, os.path.isfile) executable = find_path(benchmark_path, args.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, args.cmd) if args.env: with open(args.env) as f: env = [line.rstrip() for line in f] else: env = [ "LD_LIBRARY_PATH=%s" % ":".join( [ os.getenv("ROCM_PATH", "/opt/rocm") + "/lib", os.getenv("HCC_HOME", "/opt/rocm/hcc") + "/lib", os.getenv("HSA_PATH", "/opt/rocm/hsa") + "/lib", os.getenv("HIP_PATH", "/opt/rocm/hip") + "/lib", os.getenv("ROCM_PATH", "/opt/rocm") + "/libhsakmt/lib", os.getenv("ROCM_PATH", "/opt/rocm") + "/miopen/lib", os.getenv("ROCM_PATH", "/opt/rocm") + "/miopengemm/lib", os.getenv("ROCM_PATH", "/opt/rocm") + "/hipblas/lib", os.getenv("ROCM_PATH", "/opt/rocm") + "/rocblas/lib", "/usr/lib/x86_64-linux-gnu", ] ), f"HOME={os.getenv('HOME', '/')}", # Disable the VM fault handler signal creation for dGPUs also # forces the use of DefaultSignals instead of driver-controlled # InteruptSignals throughout the runtime. DefaultSignals poll # on memory in the runtime, while InteruptSignals call into the # driver. "HSA_ENABLE_INTERRUPT=1", # We don't have an SDMA hardware model, so need to fallback to # vector copy kernels for dGPU memcopies to/from host and device. "HSA_ENABLE_SDMA=0", ] process = Process( executable=executable, cmd=[args.cmd] + args.options.split(), drivers=[gpu_driver, render_driver], env=env, ) for cpu in cpu_list: cpu.createThreads() cpu.workload = process for cp in cp_list: cp.workload = host_cpu.workload if fast_forward: for i in range(len(future_cpu_list)): future_cpu_list[i].workload = cpu_list[i].workload future_cpu_list[i].createThreads() ########################## 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 range(args.num_cpus) ] # Other CPU strings cause bad addresses in ROCm. Revert back to M5 Simulator. for i, cpu in enumerate(cpu_list): for j in range(len(cpu)): cpu.isa[j].vendor_string = "M5 Simulator" # Full list of processing cores in the system. cpu_list = cpu_list + [shader] + cp_list # creating the overall system # notice the cpu list is explicitly added as a parameter to System system = System( cpu=cpu_list, mem_ranges=[AddrRange(args.mem_size)], cache_line_size=args.cacheline_size, mem_mode=mem_mode, workload=SEWorkload.init_compatible(executable), ) if fast_forward: system.future_cpu = future_cpu_list system.voltage_domain = VoltageDomain(voltage=args.sys_voltage) system.clk_domain = SrcClockDomain( clock=args.sys_clock, voltage_domain=system.voltage_domain ) if fast_forward: have_kvm_support = "BaseKvmCPU" in globals() if have_kvm_support and get_supported_isas().contains(ISA.X86): system.vm = KvmVM() system.m5ops_base = 0xFFFF0000 for i in range(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(args, system, shader_idx) # create Ruby system system.piobus = IOXBar( width=32, response_latency=0, frontend_latency=0, forward_latency=0 ) dma_list = [gpu_hsapp, gpu_cmd_proc] Ruby.create_system(args, None, system, None, dma_list, None) system.ruby.clk_domain = SrcClockDomain( clock=args.ruby_clock, voltage_domain=system.voltage_domain ) gpu_cmd_proc.pio = system.piobus.mem_side_ports gpu_hsapp.pio = system.piobus.mem_side_ports for i, dma_device in enumerate(dma_list): exec("system.dma_cntrl%d.clk_domain = system.ruby.clk_domain" % i) # attach the CPU ports to Ruby for i in range(args.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.in_ports system.cpu[i].dcache_port = ruby_port.in_ports ruby_port.mem_request_port = system.piobus.cpu_side_ports if get_supported_isas().contains(ISA.X86): system.cpu[i].interrupts[0].pio = system.piobus.mem_side_ports system.cpu[i].interrupts[ 0 ].int_requestor = system.piobus.cpu_side_ports system.cpu[i].interrupts[ 0 ].int_responder = system.piobus.mem_side_ports if fast_forward: system.cpu[i].mmu.connectWalkerPorts( ruby_port.in_ports, ruby_port.in_ports ) # 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) - args.num_compute_units - args.num_sqc - args.num_scalar_cache ) gpu_port_idx = gpu_port_idx - args.num_cp * 2 # Connect token ports. For this we need to search through the list of all # sequencers, since the TCP coalescers will not necessarily be first. Only # TCP coalescers use a token port for back pressure. token_port_idx = 0 for i in range(len(system.ruby._cpu_ports)): if isinstance(system.ruby._cpu_ports[i], VIPERCoalescer): system.cpu[shader_idx].CUs[ token_port_idx ].gmTokenPort = system.ruby._cpu_ports[i].gmTokenPort token_port_idx += 1 wavefront_size = args.wf_size for i in range(n_cu): # The pipeline issues wavefront_size number of uncoalesced requests # in one GPU issue cycle. Hence wavefront_size mem ports. for j in range(wavefront_size): system.cpu[shader_idx].CUs[i].memory_port[j] = system.ruby._cpu_ports[ gpu_port_idx ].in_ports[j] gpu_port_idx += 1 for i in range(n_cu): if i > 0 and not i % args.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 ].in_ports gpu_port_idx = gpu_port_idx + 1 for i in range(n_cu): if i > 0 and not i % args.cu_per_scalar_cache: print("incrementing idx on ", i) gpu_port_idx += 1 system.cpu[shader_idx].CUs[i].scalar_port = system.ruby._cpu_ports[ gpu_port_idx ].in_ports gpu_port_idx = gpu_port_idx + 1 # attach CP ports to Ruby for i in range(args.num_cp): system.cpu[cp_idx].createInterruptController() system.cpu[cp_idx].dcache_port = system.ruby._cpu_ports[ gpu_port_idx + i * 2 ].in_ports system.cpu[cp_idx].icache_port = system.ruby._cpu_ports[ gpu_port_idx + i * 2 + 1 ].in_ports system.cpu[cp_idx].interrupts[0].pio = system.piobus.mem_side_ports system.cpu[cp_idx].interrupts[ 0 ].int_requestor = system.piobus.cpu_side_ports system.cpu[cp_idx].interrupts[ 0 ].int_responder = system.piobus.mem_side_ports cp_idx = cp_idx + 1 ################# 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] else: shader.cpu_pointer = host_cpu ########################## Start simulation ######################## redirect_paths = [ RedirectPath( app_path="/proc", host_paths=[f"{m5.options.outdir}/fs/proc"] ), RedirectPath(app_path="/sys", host_paths=[f"{m5.options.outdir}/fs/sys"]), RedirectPath(app_path="/tmp", host_paths=[f"{m5.options.outdir}/fs/tmp"]), ] system.redirect_paths = redirect_paths root = Root(system=system, full_system=False) # Create the /sys/devices filesystem for the simulator so that the HSA Runtime # knows what type of GPU hardware we are simulating if args.dgpu: assert args.gfx_version in [ "gfx803", "gfx900", ], "Incorrect gfx version for dGPU" if args.gfx_version == "gfx803": hsaTopology.createFijiTopology(args) elif args.gfx_version == "gfx900": hsaTopology.createVegaTopology(args) else: assert args.gfx_version in [ "gfx801", "gfx902", ], "Incorrect gfx version for APU" hsaTopology.createCarrizoTopology(args) m5.ticks.setGlobalFrequency("1THz") if args.abs_max_tick: maxtick = args.abs_max_tick else: maxtick = m5.MaxTick # Benchmarks support work item annotations Simulation.setWorkCountOptions(system, args) # Checkpointing is not supported by APU model if args.checkpoint_dir != None or args.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 args.fast_forward: print("Switch at instruction count: %d" % cpu_list[0].max_insts_any_thread) exit_event = m5.simulate(maxtick) if args.fast_forward: if exit_event.getCause() == "a thread reached the max instruction count": m5.switchCpus(system, switch_cpu_list) print(f"Switched CPUS @ tick {m5.curTick()}") m5.stats.reset() exit_event = m5.simulate(maxtick - m5.curTick()) elif args.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(f"Switched CPUS @ tick {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())