# -*- coding: latin-1 -*- # # auto generated TopDown/TMA 4 description for Intel scalable Xeon 6 (code name Sierra Forest) with Crestmont # Please see http://ark.intel.com for more details on these CPUs. # # References: # http://bit.ly/tma-ispass14 # http://halobates.de/blog/p/262 # https://sites.google.com/site/analysismethods/yasin-pubs # https://download.01.org/perfmon/ # https://github.com/andikleen/pmu-tools/wiki/toplev-manual # # Helpers print_error = lambda msg: False version = "4" base_frequency = -1.0 Memory = 0 Average_Frequency = 0.0 num_cores = 1 num_threads = 1 num_sockets = 1 def handle_error(obj, msg): print_error(msg) obj.errcount += 1 obj.val = 0 obj.thresh = False def handle_error_metric(obj, msg): print_error(msg) obj.errcount += 1 obj.val = 0 # Constants Pipeline_Width = 6 # Aux. formulas def CLKS(self, EV, level): return EV("CPU_CLK_UNHALTED.CORE", level) def SLOTS(self, EV, level): return Pipeline_Width * CLKS(self, EV, level) def DurationTimeInSeconds(self, EV, level): return EV("interval-ms", 0) / 1000 # Percentage of time that retirement is stalled by the Memory Cluster due to a pipeline stall. See Info.Mem_Exec_Bound def PCT_Mem_Exec_Bound_Cycles(self, EV, level): return 100 * EV("LD_HEAD.ANY_AT_RET", level) / CLKS(self, EV, level) # Percentage of time that retirement is stalled due to an L1 miss. See Info.Load_Miss_Bound def PCT_Load_Miss_Bound_Cycles(self, EV, level): return 100 * EV("MEM_BOUND_STALLS_LOAD.ALL", level) / CLKS(self, EV, level) # Percentage of time that retirement is stalled due to a first level data TLB miss def PCT_DTLB_Miss_Bound_Cycles(self, EV, level): return 100 *(EV("LD_HEAD.DTLB_MISS_AT_RET", level) + EV("LD_HEAD.PGWALK_AT_RET", level)) / CLKS(self, EV, level) # Percentage of time that allocation and retirement is stalled by the Frontend Cluster due to an Ifetch Miss, either Icache or ITLB Miss. See Info.Ifetch_Bound def PCT_IFetch_Miss_Bound_Cycles(self, EV, level): return 100 * EV("MEM_BOUND_STALLS_IFETCH.ALL", level) / CLKS(self, EV, level) # Instructions Per Cycle def IPC(self, EV, level): return EV("INST_RETIRED.ANY", level) / CLKS(self, EV, level) # Cycles Per Instruction def CPI(self, EV, level): return CLKS(self, EV, level) / EV("INST_RETIRED.ANY", level) # Uops Per Instruction def UPI(self, EV, level): return EV("TOPDOWN_RETIRING.ALL_P", level) / EV("INST_RETIRED.ANY", level) # Floating Point Operations Per Cycle def FLOPc(self, EV, level): return EV("FP_FLOPS_RETIRED.ALL", level) / CLKS(self, EV, level) # Instructions per Branch (lower number means higher occurrence rate) def IpBranch(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("BR_INST_RETIRED.ALL_BRANCHES", level) # Instruction per (near) call (lower number means higher occurrence rate) def IpCall(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("BR_INST_RETIRED.NEAR_CALL", level) # Instructions per Far Branch ( Far Branches apply upon transition from application to operating system, handling interrupts, exceptions) [lower number means higher occurrence rate] def IpFarBranch(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("BR_INST_RETIRED.FAR_BRANCH:USER", level) # Instructions per retired Branch Misprediction def IpMispredict(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("BR_MISP_RETIRED.ALL_BRANCHES", level) # Instructions per retired conditional Branch Misprediction where the branch was not taken def IpMisp_Cond_Ntaken(self, EV, level): return EV("INST_RETIRED.ANY", level) / (EV("BR_MISP_RETIRED.COND", level) - EV("BR_MISP_RETIRED.COND_TAKEN", level)) # Instructions per retired conditional Branch Misprediction where the branch was taken def IpMisp_Cond_Taken(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("BR_MISP_RETIRED.COND_TAKEN", level) # Instructions per retired return Branch Misprediction def IpMisp_Ret(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("BR_MISP_RETIRED.RETURN", level) # Instructions per retired indirect call or jump Branch Misprediction def IpMisp_Indirect(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("BR_MISP_RETIRED.INDIRECT", level) # Instructions per Floating Point (FP) Operation def IpFLOP(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("FP_FLOPS_RETIRED.ALL", level) # Instructions per FP Arithmetic Scalar Single-Precision instruction def IpFPArith_Scalar_SP(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("FP_INST_RETIRED.32B_SP", level) # Instructions per FP Arithmetic Scalar Double-Precision instruction def IpFPArith_Scalar_DP(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("FP_INST_RETIRED.64B_DP", level) # Instructions per FP Arithmetic AVX/SSE 128-bit instruction def IpFPArith_AVX128(self, EV, level): return EV("INST_RETIRED.ANY", level) / (EV("FP_INST_RETIRED.128B_DP", level) + EV("FP_INST_RETIRED.128B_SP", level)) # Percentage of all uops which are microcode ops def Microcode_Uop_Ratio(self, EV, level): return 100 * EV("UOPS_RETIRED.MS", level) / EV("TOPDOWN_RETIRING.ALL_P", level) # Percentage of all uops which are FPDiv uops def FPDiv_Uop_Ratio(self, EV, level): return 100 * EV("UOPS_RETIRED.FPDIV", level) / EV("TOPDOWN_RETIRING.ALL_P", level) # Percentage of all uops which are IDiv uops def IDiv_Uop_Ratio(self, EV, level): return 100 * EV("UOPS_RETIRED.IDIV", level) / EV("TOPDOWN_RETIRING.ALL_P", level) # Percentage of all uops which are x87 uops def X87_Uop_Ratio(self, EV, level): return 100 * EV("UOPS_RETIRED.X87", level) / EV("TOPDOWN_RETIRING.ALL_P", level) # Instructions per Load def IpLoad(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("MEM_UOPS_RETIRED.ALL_LOADS", level) # Instructions per Store def IpStore(self, EV, level): return EV("INST_RETIRED.ANY", level) / EV("MEM_UOPS_RETIRED.ALL_STORES", level) # Ratio of mem load uops to all uops def MemLoad_Ratio(self, EV, level): return 1000 * EV("MEM_UOPS_RETIRED.ALL_LOADS", level) / EV("TOPDOWN_RETIRING.ALL_P", level) # Percentage of total non-speculative loads that are splits def Load_Splits_Ratio(self, EV, level): return 100 * EV("MEM_UOPS_RETIRED.SPLIT_LOADS", level) / EV("MEM_UOPS_RETIRED.ALL_LOADS", level) # Percentage of total non-speculative loads that perform one or more locks def Load_Locks_Ratio(self, EV, level): return 100 * EV("MEM_UOPS_RETIRED.LOCK_LOADS", level) / EV("MEM_UOPS_RETIRED.ALL_LOADS", level) # Percentage of total non-speculative loads with a store forward or unknown store address block def PCT_Loads_with_StoreFwdBlk(self, EV, level): return 100 * EV("LD_BLOCKS.DATA_UNKNOWN", level) / EV("MEM_UOPS_RETIRED.ALL_LOADS", level) # Percentage of total non-speculative loads with an address aliasing block def PCT_Loads_with_AdressAliasing(self, EV, level): return 100 * EV("LD_BLOCKS.ADDRESS_ALIAS", level) / EV("MEM_UOPS_RETIRED.ALL_LOADS", level) # Percentage of Memory Execution Bound due to a second level TLB miss def PCT_LoadHead_with_STLBHit(self, EV, level): return 100 * EV("LD_HEAD.DTLB_MISS_AT_RET", level) / EV("LD_HEAD.ANY_AT_RET", level) # Percentage of Memory Execution Bound due to a pagewalk def PCT_LoadHead_with_Pagewalk(self, EV, level): return 100 * EV("LD_HEAD.PGWALK_AT_RET", level) / EV("LD_HEAD.ANY_AT_RET", level) # Percentage of Memory Execution Bound due to a store forward address match def PCT_LoadHead_with_StoreFwding(self, EV, level): return 100 * EV("LD_HEAD.ST_ADDR_AT_RET", level) / EV("LD_HEAD.ANY_AT_RET", level) # Percentage of Memory Execution Bound due to other block cases, such as pipeline conflicts, fences, etc def PCT_LoadHead_with_OtherPipelineBlks(self, EV, level): return 100 * EV("LD_HEAD.OTHER_AT_RET", level) / EV("LD_HEAD.ANY_AT_RET", level) # Percentage of Memory Execution Bound due to a first level data cache miss def PCT_LoadHead_with_L1miss(self, EV, level): return 100 * EV("LD_HEAD.L1_MISS_AT_RET", level) / EV("LD_HEAD.ANY_AT_RET", level) # Counts the number of cycles the core is stalled due to store buffer full def Store_Bound(self, EV, level): return 100 *(EV("MEM_SCHEDULER_BLOCK.ST_BUF", level) / EV("MEM_SCHEDULER_BLOCK.ALL", level)) * (EV("TOPDOWN_BE_BOUND.MEM_SCHEDULER", level) / SLOTS(self, EV, level)) # Counts the number of cycles that the oldest load of the load buffer is stalled at retirement def Load_Bound(self, EV, level): return 100 *(EV("LD_HEAD.L1_BOUND_AT_RET", level) + EV("MEM_BOUND_STALLS_LOAD.ALL", level)) / CLKS(self, EV, level) # Counts the number of cycles that the oldest load of the load buffer is stalled at retirement due to a pipeline block def L1_Bound(self, EV, level): return 100 * EV("LD_HEAD.L1_BOUND_AT_RET", level) / CLKS(self, EV, level) # Percentage of memory bound stalls where retirement is stalled due to an L1 miss that hit the L2 def PCT_LoadMissBound_with_L2Hit(self, EV, level): return 100 * EV("MEM_BOUND_STALLS_LOAD.L2_HIT", level) / EV("MEM_BOUND_STALLS_LOAD.ALL", level) # Percentage of memory bound stalls where retirement is stalled due to an L1 miss that subsequently misses in the L2 def PCT_LoadMissBound_with_L2Miss(self, EV, level): return 100 *(EV("MEM_BOUND_STALLS_LOAD.LLC_HIT", level) + EV("MEM_BOUND_STALLS_LOAD.LLC_MISS", level)) / EV("MEM_BOUND_STALLS_LOAD.ALL", level) # Percentage of memory bound stalls where retirement is stalled due to an L1 miss that hit the L3 def PCT_LoadMissBound_with_L3Hit(self, EV, level): return 100 * EV("MEM_BOUND_STALLS_LOAD.LLC_HIT", level) / EV("MEM_BOUND_STALLS_LOAD.ALL", level) # Percentage of memory bound stalls where retirement is stalled due to an L1 miss that subsequently misses the L3 def PCT_LoadMissBound_with_L3Miss(self, EV, level): return 100 * EV("MEM_BOUND_STALLS_LOAD.LLC_MISS", level) / EV("MEM_BOUND_STALLS_LOAD.ALL", level) # Percentage of ifetch miss bound stalls, where the ifetch miss hits in the L2 def PCT_IfetchMissBound_with_L2Hit(self, EV, level): return 100 * EV("MEM_BOUND_STALLS_IFETCH.L2_HIT", level) / EV("MEM_BOUND_STALLS_IFETCH.ALL", level) # Percentage of ifetch miss bound stalls, where the ifetch miss doesn't hit in the L2 def PCT_IfetchMissBound_with_L2Miss(self, EV, level): return 100 *(EV("MEM_BOUND_STALLS_IFETCH.LLC_HIT", level) + EV("MEM_BOUND_STALLS_IFETCH.LLC_MISS", level)) / EV("MEM_BOUND_STALLS_IFETCH.ALL", level) # Percentage of ifetch miss bound stalls, where the ifetch miss hits in the L3 def PCT_IfetchMissBound_with_L3Hit(self, EV, level): return 100 * EV("MEM_BOUND_STALLS_IFETCH.LLC_HIT", level) / EV("MEM_BOUND_STALLS_IFETCH.ALL", level) # Percentage of ifetch miss bound stalls, where the ifetch miss subsequently misses in the L3 def PCT_IfetchMissBound_with_L3Miss(self, EV, level): return 100 * EV("MEM_BOUND_STALLS_IFETCH.LLC_MISS", level) / EV("MEM_BOUND_STALLS_IFETCH.ALL", level) # Ratio of all branches which mispredict def Branch_Mispredict_Ratio(self, EV, level): return EV("BR_MISP_RETIRED.ALL_BRANCHES", level) / EV("BR_INST_RETIRED.ALL_BRANCHES", level) # Ratio between Mispredicted branches and unknown branches def Branch_Mispredict_to_Unknown_Branch_Ratio(self, EV, level): return EV("BR_MISP_RETIRED.ALL_BRANCHES", level) / EV("BACLEARS.ANY", level) # Counts the number of machine clears relative to thousands of instructions retired, due to floating point assists def Machine_Clears_FP_Assist_PKI(self, EV, level): return 1000 * EV("MACHINE_CLEARS.FP_ASSIST", level) / EV("INST_RETIRED.ANY", level) # Counts the number of machine clears relative to thousands of instructions retired, due to page faults def Machine_Clears_Page_Fault_PKI(self, EV, level): return 1000 * EV("MACHINE_CLEARS.PAGE_FAULT", level) / EV("INST_RETIRED.ANY", level) # Counts the number of machine clears relative to thousands of instructions retired, due to self-modifying code def Machine_Clears_SMC_PKI(self, EV, level): return 1000 * EV("MACHINE_CLEARS.SMC", level) / EV("INST_RETIRED.ANY", level) # Percentage of time that allocation is stalled due to store buffer full def PCT_Store_Buffer_Stall_Cycles(self, EV, level): return 100 * EV("MEM_SCHEDULER_BLOCK.ST_BUF", level) / CLKS(self, EV, level) # Percentage of time that allocation is stalled due to load buffer full def PCT_Load_Buffer_Stall_Cycles(self, EV, level): return 100 * EV("MEM_SCHEDULER_BLOCK.LD_BUF", level) / CLKS(self, EV, level) # Percentage of time that allocation is stalled due to memory reservation stations full def PCT_Mem_RSV_Stall_Cycles(self, EV, level): return 100 * EV("MEM_SCHEDULER_BLOCK.RSV", level) / CLKS(self, EV, level) # Percentage of time that the core is stalled due to a TPAUSE or UMWAIT instruction def PCT_Tpause_Cycles(self, EV, level): return 100 * EV("SERIALIZATION.C01_MS_SCB", level) / SLOTS(self, EV, level) # Average Frequency Utilization relative nominal frequency def Turbo_Utilization(self, EV, level): return CLKS(self, EV, level) / EV("CPU_CLK_UNHALTED.REF_TSC", level) # Fraction of cycles spent in Kernel mode def Kernel_Utilization(self, EV, level): return EV("CPU_CLK_UNHALTED.CORE_P:sup", level) / CLKS(self, EV, level) # Average CPU Utilization def CPU_Utilization(self, EV, level): return EV("CPU_CLK_UNHALTED.REF_TSC", level) / EV("msr/tsc/", 0) # Giga Floating Point Operations Per Second. Aggregate across all supported options of: FP precisions, scalar and vector instructions, vector-width def GFLOPs(self, EV, level): return EV("FP_FLOPS_RETIRED.ALL", level) / (EV("interval-s", 0) * 1000000000 ) # Event groups class Frontend_Bound: name = "Frontend_Bound" domain = "Slots" area = "FE" level = 1 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.ALL_P", 1) / SLOTS(self, EV, 1) self.thresh = (self.val > 0.20) except ZeroDivisionError: handle_error(self, "Frontend_Bound zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to frontend stalls.""" class IFetch_Latency: name = "IFetch_Latency" domain = "Slots" area = "FE" level = 2 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.FRONTEND_LATENCY", 2) / SLOTS(self, EV, 2) self.thresh = (self.val > 0.15) and self.parent.thresh except ZeroDivisionError: handle_error(self, "IFetch_Latency zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to frontend latency restrictions due to icache misses, itlb misses, branch detection, and resteer limitations.""" class ICache_Misses: name = "ICache_Misses" domain = "Slots" area = "FE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.ICACHE", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "ICache_Misses zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to instruction cache misses.""" class ITLB_Misses: name = "ITLB_Misses" domain = "Slots" area = "FE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.ITLB_MISS", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "ITLB_Misses zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to Instruction Table Lookaside Buffer (ITLB) misses.""" class Branch_Detect: name = "Branch_Detect" domain = "Slots" area = "FE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.BRANCH_DETECT", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Branch_Detect zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to BACLEARS, which occurs when the Branch Target Buffer (BTB) prediction or lack thereof, was corrected by a later branch predictor in the frontend. Includes BACLEARS due to all branch types including conditional and unconditional jumps, returns, and indirect branches.""" class Branch_Resteer: name = "Branch_Resteer" domain = "Slots" area = "FE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.BRANCH_RESTEER", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Branch_Resteer zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to BTCLEARS, which occurs when the Branch Target Buffer (BTB) predicts a taken branch.""" class IFetch_Bandwidth: name = "IFetch_Bandwidth" domain = "Slots" area = "FE" level = 2 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.FRONTEND_BANDWIDTH", 2) / SLOTS(self, EV, 2) self.thresh = (self.val > 0.10) and self.parent.thresh except ZeroDivisionError: handle_error(self, "IFetch_Bandwidth zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to frontend bandwidth restrictions due to decode, predecode, cisc, and other limitations.""" class Cisc: name = "Cisc" domain = "Slots" area = "FE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.CISC", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Cisc zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to the microcode sequencer (MS).""" class Decode: name = "Decode" domain = "Slots" area = "FE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.DECODE", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Decode zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to decode stalls.""" class Predecode: name = "Predecode" domain = "Slots" area = "FE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.PREDECODE", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Predecode zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to wrong predecodes.""" class Other_FB: name = "Other_FB" domain = "Slots" area = "FE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_FE_BOUND.OTHER", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Other_FB zero division") return self.val desc = """ Counts the number of issue slots that were not delivered by the frontend due to other common frontend stalls not categorized.""" class Bad_Speculation: name = "Bad_Speculation" domain = "Slots" area = "BAD" level = 1 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BAD_SPECULATION.ALL_P", 1) / SLOTS(self, EV, 1) self.thresh = (self.val > 0.15) except ZeroDivisionError: handle_error(self, "Bad_Speculation zero division") return self.val desc = """ Counts the total number of issue slots that were not consumed by the backend because allocation is stalled due to a mispredicted jump or a machine clear. Only issue slots wasted due to fast nukes such as memory ordering nukes are counted. Other nukes are not accounted for. Counts all issue slots blocked during this recovery window including relevant microcode flows and while uops are not yet available in the instruction queue (IQ). Also includes the issue slots that were consumed by the backend but were thrown away because they were younger than the mispredict or machine clear.""" class Branch_Mispredicts: name = "Branch_Mispredicts" domain = "Slots" area = "BAD" level = 2 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BAD_SPECULATION.MISPREDICT", 2) / SLOTS(self, EV, 2) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Branch_Mispredicts zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to branch mispredicts""" class Machine_Clears: name = "Machine_Clears" domain = "Slots" area = "BAD" level = 2 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BAD_SPECULATION.MACHINE_CLEARS", 2) / SLOTS(self, EV, 2) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Machine_Clears zero division") return self.val desc = """ Counts the total number of issue slots that were not consumed by the backend because allocation is stalled due to a machine clear (nuke) of any kind including memory ordering and memory disambiguation""" class Nuke: name = "Nuke" domain = "Slots" area = "BAD" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BAD_SPECULATION.NUKE", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Nuke zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to a machine clear that requires the use of microcode (slow nuke)""" class Fast_Nuke: name = "Fast_Nuke" domain = "Slots" area = "BAD" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BAD_SPECULATION.FASTNUKE", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.05) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Fast_Nuke zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to a machine clear that does not require the use of microcode, classified as a fast nuke, due to memory ordering, memory disambiguation and memory renaming""" class Backend_Bound: name = "Backend_Bound" domain = "Slots" area = "BE" level = 1 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BE_BOUND.ALL_P", 1) / SLOTS(self, EV, 1) self.thresh = (self.val > 0.10) except ZeroDivisionError: handle_error(self, "Backend_Bound zero division") return self.val desc = """ Counts the total number of issue slots that were not consumed by the backend due to backend stalls. Note that uops must be available for consumption in order for this event to count. If a uop is not available (IQ is empty), this event will not count""" class Core_Bound: name = "Core_Bound" domain = "Slots" area = "BE" level = 2 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BE_BOUND.ALLOC_RESTRICTIONS", 2) / SLOTS(self, EV, 2) self.thresh = (self.val > 0.10) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Core_Bound zero division") return self.val desc = """ Counts the number of cycles due to backend bound stalls that are bounded by core restrictions and not attributed to an outstanding load or stores, or resource limitation""" class Allocation_Restriction: name = "Allocation_Restriction" domain = "Slots" area = "BE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BE_BOUND.ALLOC_RESTRICTIONS", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.10) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Allocation_Restriction zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to certain allocation restrictions""" class Resource_Bound: name = "Resource_Bound" domain = "Slots" area = "BE" level = 2 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = ((EV("TOPDOWN_BE_BOUND.ALL_P", 2) / SLOTS(self, EV, 2)) - self.Core_Bound.compute(EV)) self.thresh = (self.val > 0.20) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Resource_Bound zero division") return self.val desc = """ Counts the number of cycles the core is stalled due to a resource limitation""" class Mem_Scheduler: name = "Mem_Scheduler" domain = "Slots" area = "BE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BE_BOUND.MEM_SCHEDULER", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.10) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Mem_Scheduler zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to memory reservation stalls in which a scheduler is not able to accept uops""" class Non_Mem_Scheduler: name = "Non_Mem_Scheduler" domain = "Slots" area = "BE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BE_BOUND.NON_MEM_SCHEDULER", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.10) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Non_Mem_Scheduler zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to IEC or FPC RAT stalls, which can be due to FIQ or IEC reservation stalls in which the integer, floating point or SIMD scheduler is not able to accept uops""" class Register: name = "Register" domain = "Slots" area = "BE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BE_BOUND.REGISTER", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.10) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Register zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to the physical register file unable to accept an entry (marble stalls)""" class Reorder_Buffer: name = "Reorder_Buffer" domain = "Slots" area = "BE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BE_BOUND.REORDER_BUFFER", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.10) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Reorder_Buffer zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to the reorder buffer being full (ROB stalls)""" class Serialization: name = "Serialization" domain = "Slots" area = "BE" level = 3 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_BE_BOUND.SERIALIZATION", 3) / SLOTS(self, EV, 3) self.thresh = (self.val > 0.10) and self.parent.thresh except ZeroDivisionError: handle_error(self, "Serialization zero division") return self.val desc = """ Counts the number of issue slots that were not consumed by the backend due to scoreboards from the instruction queue (IQ), jump execution unit (JEU), or microcode sequencer (MS)""" class Retiring: name = "Retiring" domain = "Slots" area = "RET" level = 1 htoff = False sample = [] errcount = 0 sibling = None metricgroup = frozenset([]) maxval = None def compute(self, EV): try: self.val = EV("TOPDOWN_RETIRING.ALL_P", 1) / SLOTS(self, EV, 1) self.thresh = (self.val > 0.75) except ZeroDivisionError: handle_error(self, "Retiring zero division") return self.val desc = """ Counts the number of issue slots that result in retirement slots""" class Metric_PCT_Mem_Exec_Bound_Cycles: name = "PCT_Mem_Exec_Bound_Cycles" domain = "Cycles" maxval = 0 errcount = 0 area = "Info.Bottleneck" metricgroup = frozenset(['Mem_Exec']) sibling = None def compute(self, EV): try: self.val = PCT_Mem_Exec_Bound_Cycles(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_Mem_Exec_Bound_Cycles zero division") desc = """ Percentage of time that retirement is stalled by the Memory Cluster due to a pipeline stall. See Info.Mem_Exec_Bound""" class Metric_PCT_Load_Miss_Bound_Cycles: name = "PCT_Load_Miss_Bound_Cycles" domain = "Cycles" maxval = 0 errcount = 0 area = "Info.Bottleneck" metricgroup = frozenset(['Load_Store_Miss']) sibling = None def compute(self, EV): try: self.val = PCT_Load_Miss_Bound_Cycles(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_Load_Miss_Bound_Cycles zero division") desc = """ Percentage of time that retirement is stalled due to an L1 miss. See Info.Load_Miss_Bound""" class Metric_PCT_DTLB_Miss_Bound_Cycles: name = "PCT_DTLB_Miss_Bound_Cycles" domain = "Cycles" maxval = 0 errcount = 0 area = "Info.Bottleneck" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_DTLB_Miss_Bound_Cycles(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_DTLB_Miss_Bound_Cycles zero division") desc = """ Percentage of time that retirement is stalled due to a first level data TLB miss""" class Metric_PCT_IFetch_Miss_Bound_Cycles: name = "PCT_IFetch_Miss_Bound_Cycles" domain = "Cycles" maxval = 0 errcount = 0 area = "Info.Bottleneck" metricgroup = frozenset(['Ifetch']) sibling = None def compute(self, EV): try: self.val = PCT_IFetch_Miss_Bound_Cycles(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_IFetch_Miss_Bound_Cycles zero division") desc = """ Percentage of time that allocation and retirement is stalled by the Frontend Cluster due to an Ifetch Miss, either Icache or ITLB Miss. See Info.Ifetch_Bound""" class Metric_IPC: name = "IPC" domain = "" maxval = 0 errcount = 0 area = "Info.Core" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IPC(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IPC zero division") desc = """ Instructions Per Cycle""" class Metric_CPI: name = "CPI" domain = "" maxval = 0 errcount = 0 area = "Info.Core" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = CPI(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "CPI zero division") desc = """ Cycles Per Instruction""" class Metric_UPI: name = "UPI" domain = "" maxval = 0 errcount = 0 area = "Info.Core" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = UPI(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "UPI zero division") desc = """ Uops Per Instruction""" class Metric_FLOPc: name = "FLOPc" domain = "" maxval = 0 errcount = 0 area = "Info.Core" metricgroup = frozenset(['Flops']) sibling = None def compute(self, EV): try: self.val = FLOPc(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "FLOPc zero division") desc = """ Floating Point Operations Per Cycle""" class Metric_IpBranch: name = "IpBranch" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Inst_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpBranch(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpBranch zero division") desc = """ Instructions per Branch (lower number means higher occurrence rate)""" class Metric_IpCall: name = "IpCall" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Inst_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpCall(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpCall zero division") desc = """ Instruction per (near) call (lower number means higher occurrence rate)""" class Metric_IpFarBranch: name = "IpFarBranch" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Inst_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpFarBranch(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpFarBranch zero division") desc = """ Instructions per Far Branch ( Far Branches apply upon transition from application to operating system, handling interrupts, exceptions) [lower number means higher occurrence rate]""" class Metric_IpMispredict: name = "IpMispredict" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Inst_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpMispredict(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpMispredict zero division") desc = """ Instructions per retired Branch Misprediction""" class Metric_IpMisp_Cond_Ntaken: name = "IpMisp_Cond_Ntaken" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Inst_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpMisp_Cond_Ntaken(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpMisp_Cond_Ntaken zero division") desc = """ Instructions per retired conditional Branch Misprediction where the branch was not taken""" class Metric_IpMisp_Cond_Taken: name = "IpMisp_Cond_Taken" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Inst_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpMisp_Cond_Taken(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpMisp_Cond_Taken zero division") desc = """ Instructions per retired conditional Branch Misprediction where the branch was taken""" class Metric_IpMisp_Ret: name = "IpMisp_Ret" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Inst_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpMisp_Ret(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpMisp_Ret zero division") desc = """ Instructions per retired return Branch Misprediction""" class Metric_IpMisp_Indirect: name = "IpMisp_Indirect" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Inst_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpMisp_Indirect(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpMisp_Indirect zero division") desc = """ Instructions per retired indirect call or jump Branch Misprediction""" class Metric_IpFLOP: name = "IpFLOP" domain = "" maxval = 0 errcount = 0 area = "Info.Arith_Inst_Mix" metricgroup = frozenset(['Flops']) sibling = None def compute(self, EV): try: self.val = IpFLOP(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpFLOP zero division") desc = """ Instructions per Floating Point (FP) Operation""" class Metric_IpFPArith_Scalar_SP: name = "IpFPArith_Scalar_SP" domain = "" maxval = 0 errcount = 0 area = "Info.Arith_Inst_Mix" metricgroup = frozenset(['Flops']) sibling = None def compute(self, EV): try: self.val = IpFPArith_Scalar_SP(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpFPArith_Scalar_SP zero division") desc = """ Instructions per FP Arithmetic Scalar Single-Precision instruction""" class Metric_IpFPArith_Scalar_DP: name = "IpFPArith_Scalar_DP" domain = "" maxval = 0 errcount = 0 area = "Info.Arith_Inst_Mix" metricgroup = frozenset(['Flops']) sibling = None def compute(self, EV): try: self.val = IpFPArith_Scalar_DP(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpFPArith_Scalar_DP zero division") desc = """ Instructions per FP Arithmetic Scalar Double-Precision instruction""" class Metric_IpFPArith_AVX128: name = "IpFPArith_AVX128" domain = "" maxval = 0 errcount = 0 area = "Info.Arith_Inst_Mix" metricgroup = frozenset(['Flops']) sibling = None def compute(self, EV): try: self.val = IpFPArith_AVX128(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpFPArith_AVX128 zero division") desc = """ Instructions per FP Arithmetic AVX/SSE 128-bit instruction""" class Metric_Microcode_Uop_Ratio: name = "Microcode_Uop_Ratio" domain = "" maxval = 0 errcount = 0 area = "Info.Uop_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Microcode_Uop_Ratio(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Microcode_Uop_Ratio zero division") desc = """ Percentage of all uops which are microcode ops""" class Metric_FPDiv_Uop_Ratio: name = "FPDiv_Uop_Ratio" domain = "" maxval = 0 errcount = 0 area = "Info.Uop_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = FPDiv_Uop_Ratio(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "FPDiv_Uop_Ratio zero division") desc = """ Percentage of all uops which are FPDiv uops""" class Metric_IDiv_Uop_Ratio: name = "IDiv_Uop_Ratio" domain = "" maxval = 0 errcount = 0 area = "Info.Uop_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IDiv_Uop_Ratio(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IDiv_Uop_Ratio zero division") desc = """ Percentage of all uops which are IDiv uops""" class Metric_X87_Uop_Ratio: name = "X87_Uop_Ratio" domain = "" maxval = 0 errcount = 0 area = "Info.Uop_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = X87_Uop_Ratio(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "X87_Uop_Ratio zero division") desc = """ Percentage of all uops which are x87 uops""" class Metric_IpLoad: name = "IpLoad" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpLoad(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpLoad zero division") desc = """ Instructions per Load""" class Metric_IpStore: name = "IpStore" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = IpStore(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "IpStore zero division") desc = """ Instructions per Store""" class Metric_MemLoad_Ratio: name = "MemLoad_Ratio" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = MemLoad_Ratio(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "MemLoad_Ratio zero division") desc = """ Ratio of mem load uops to all uops""" class Metric_Load_Splits_Ratio: name = "Load_Splits_Ratio" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Load_Splits_Ratio(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Load_Splits_Ratio zero division") desc = """ Percentage of total non-speculative loads that are splits""" class Metric_Load_Locks_Ratio: name = "Load_Locks_Ratio" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Mix" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Load_Locks_Ratio(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Load_Locks_Ratio zero division") desc = """ Percentage of total non-speculative loads that perform one or more locks""" class Metric_PCT_Loads_with_StoreFwdBlk: name = "PCT_Loads_with_StoreFwdBlk" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Exec_Blocks" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_Loads_with_StoreFwdBlk(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_Loads_with_StoreFwdBlk zero division") desc = """ Percentage of total non-speculative loads with a store forward or unknown store address block""" class Metric_PCT_Loads_with_AdressAliasing: name = "PCT_Loads_with_AdressAliasing" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Exec_Blocks" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_Loads_with_AdressAliasing(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_Loads_with_AdressAliasing zero division") desc = """ Percentage of total non-speculative loads with an address aliasing block""" class Metric_PCT_LoadHead_with_STLBHit: name = "PCT_LoadHead_with_STLBHit" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Exec_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_LoadHead_with_STLBHit(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_LoadHead_with_STLBHit zero division") desc = """ Percentage of Memory Execution Bound due to a second level TLB miss""" class Metric_PCT_LoadHead_with_Pagewalk: name = "PCT_LoadHead_with_Pagewalk" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Exec_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_LoadHead_with_Pagewalk(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_LoadHead_with_Pagewalk zero division") desc = """ Percentage of Memory Execution Bound due to a pagewalk""" class Metric_PCT_LoadHead_with_StoreFwding: name = "PCT_LoadHead_with_StoreFwding" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Exec_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_LoadHead_with_StoreFwding(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_LoadHead_with_StoreFwding zero division") desc = """ Percentage of Memory Execution Bound due to a store forward address match""" class Metric_PCT_LoadHead_with_OtherPipelineBlks: name = "PCT_LoadHead_with_OtherPipelineBlks" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Exec_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_LoadHead_with_OtherPipelineBlks(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_LoadHead_with_OtherPipelineBlks zero division") desc = """ Percentage of Memory Execution Bound due to other block cases, such as pipeline conflicts, fences, etc""" class Metric_PCT_LoadHead_with_L1miss: name = "PCT_LoadHead_with_L1miss" domain = "" maxval = 0 errcount = 0 area = "Info.Mem_Exec_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_LoadHead_with_L1miss(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_LoadHead_with_L1miss zero division") desc = """ Percentage of Memory Execution Bound due to a first level data cache miss""" class Metric_Store_Bound: name = "Store_Bound" domain = "" maxval = 0 errcount = 0 area = "Info.Load_Store_Bound" metricgroup = frozenset(['load_store_bound']) sibling = None def compute(self, EV): try: self.val = Store_Bound(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Store_Bound zero division") desc = """ Counts the number of cycles the core is stalled due to store buffer full""" class Metric_Load_Bound: name = "Load_Bound" domain = "" maxval = 0 errcount = 0 area = "Info.Load_Store_Bound" metricgroup = frozenset(['load_store_bound']) sibling = None def compute(self, EV): try: self.val = Load_Bound(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Load_Bound zero division") desc = """ Counts the number of cycles that the oldest load of the load buffer is stalled at retirement""" class Metric_L1_Bound: name = "L1_Bound" domain = "" maxval = 0 errcount = 0 area = "Info.Load_Store_Bound" metricgroup = frozenset(['load_store_bound']) sibling = None def compute(self, EV): try: self.val = L1_Bound(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "L1_Bound zero division") desc = """ Counts the number of cycles that the oldest load of the load buffer is stalled at retirement due to a pipeline block""" class Metric_PCT_LoadMissBound_with_L2Hit: name = "PCT_LoadMissBound_with_L2Hit" domain = "" maxval = 0 errcount = 0 area = "Info.Load_Miss_Bound" metricgroup = frozenset(['load_store_bound']) sibling = None def compute(self, EV): try: self.val = PCT_LoadMissBound_with_L2Hit(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_LoadMissBound_with_L2Hit zero division") desc = """ Percentage of memory bound stalls where retirement is stalled due to an L1 miss that hit the L2""" class Metric_PCT_LoadMissBound_with_L2Miss: name = "PCT_LoadMissBound_with_L2Miss" domain = "" maxval = 0 errcount = 0 area = "Info.Load_Miss_Bound" metricgroup = frozenset(['load_store_bound']) sibling = None def compute(self, EV): try: self.val = PCT_LoadMissBound_with_L2Miss(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_LoadMissBound_with_L2Miss zero division") desc = """ Percentage of memory bound stalls where retirement is stalled due to an L1 miss that subsequently misses in the L2""" class Metric_PCT_LoadMissBound_with_L3Hit: name = "PCT_LoadMissBound_with_L3Hit" domain = "" maxval = 0 errcount = 0 area = "Info.Load_Miss_Bound" metricgroup = frozenset(['load_store_bound']) sibling = None def compute(self, EV): try: self.val = PCT_LoadMissBound_with_L3Hit(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_LoadMissBound_with_L3Hit zero division") desc = """ Percentage of memory bound stalls where retirement is stalled due to an L1 miss that hit the L3""" class Metric_PCT_LoadMissBound_with_L3Miss: name = "PCT_LoadMissBound_with_L3Miss" domain = "" maxval = 0 errcount = 0 area = "Info.Load_Miss_Bound" metricgroup = frozenset(['load_store_bound']) sibling = None def compute(self, EV): try: self.val = PCT_LoadMissBound_with_L3Miss(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_LoadMissBound_with_L3Miss zero division") desc = """ Percentage of memory bound stalls where retirement is stalled due to an L1 miss that subsequently misses the L3""" class Metric_PCT_IfetchMissBound_with_L2Hit: name = "PCT_IfetchMissBound_with_L2Hit" domain = "" maxval = 0 errcount = 0 area = "Info.Ifetch_Miss_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_IfetchMissBound_with_L2Hit(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_IfetchMissBound_with_L2Hit zero division") desc = """ Percentage of ifetch miss bound stalls, where the ifetch miss hits in the L2""" class Metric_PCT_IfetchMissBound_with_L2Miss: name = "PCT_IfetchMissBound_with_L2Miss" domain = "" maxval = 0 errcount = 0 area = "Info.Ifetch_Miss_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_IfetchMissBound_with_L2Miss(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_IfetchMissBound_with_L2Miss zero division") desc = """ Percentage of ifetch miss bound stalls, where the ifetch miss doesn't hit in the L2""" class Metric_PCT_IfetchMissBound_with_L3Hit: name = "PCT_IfetchMissBound_with_L3Hit" domain = "" maxval = 0 errcount = 0 area = "Info.Ifetch_Miss_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_IfetchMissBound_with_L3Hit(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_IfetchMissBound_with_L3Hit zero division") desc = """ Percentage of ifetch miss bound stalls, where the ifetch miss hits in the L3""" class Metric_PCT_IfetchMissBound_with_L3Miss: name = "PCT_IfetchMissBound_with_L3Miss" domain = "" maxval = 0 errcount = 0 area = "Info.Ifetch_Miss_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_IfetchMissBound_with_L3Miss(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_IfetchMissBound_with_L3Miss zero division") desc = """ Percentage of ifetch miss bound stalls, where the ifetch miss subsequently misses in the L3""" class Metric_Branch_Mispredict_Ratio: name = "Branch_Mispredict_Ratio" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Mispredict_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Branch_Mispredict_Ratio(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Branch_Mispredict_Ratio zero division") desc = """ Ratio of all branches which mispredict""" class Metric_Branch_Mispredict_to_Unknown_Branch_Ratio: name = "Branch_Mispredict_to_Unknown_Branch_Ratio" domain = "" maxval = 0 errcount = 0 area = "Info.Br_Mispredict_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Branch_Mispredict_to_Unknown_Branch_Ratio(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Branch_Mispredict_to_Unknown_Branch_Ratio zero division") desc = """ Ratio between Mispredicted branches and unknown branches""" class Metric_Machine_Clears_FP_Assist_PKI: name = "Machine_Clears_FP_Assist_PKI" domain = "" maxval = 0 errcount = 0 area = "Info.Machine_Clear_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Machine_Clears_FP_Assist_PKI(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Machine_Clears_FP_Assist_PKI zero division") desc = """ Counts the number of machine clears relative to thousands of instructions retired, due to floating point assists""" class Metric_Machine_Clears_Page_Fault_PKI: name = "Machine_Clears_Page_Fault_PKI" domain = "" maxval = 0 errcount = 0 area = "Info.Machine_Clear_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Machine_Clears_Page_Fault_PKI(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Machine_Clears_Page_Fault_PKI zero division") desc = """ Counts the number of machine clears relative to thousands of instructions retired, due to page faults""" class Metric_Machine_Clears_SMC_PKI: name = "Machine_Clears_SMC_PKI" domain = "" maxval = 0 errcount = 0 area = "Info.Machine_Clear_Bound" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Machine_Clears_SMC_PKI(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Machine_Clears_SMC_PKI zero division") desc = """ Counts the number of machine clears relative to thousands of instructions retired, due to self-modifying code""" class Metric_PCT_Store_Buffer_Stall_Cycles: name = "PCT_Store_Buffer_Stall_Cycles" domain = "" maxval = 0 errcount = 0 area = "Info.Buffer_Stalls" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_Store_Buffer_Stall_Cycles(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_Store_Buffer_Stall_Cycles zero division") desc = """ Percentage of time that allocation is stalled due to store buffer full""" class Metric_PCT_Load_Buffer_Stall_Cycles: name = "PCT_Load_Buffer_Stall_Cycles" domain = "" maxval = 0 errcount = 0 area = "Info.Buffer_Stalls" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_Load_Buffer_Stall_Cycles(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_Load_Buffer_Stall_Cycles zero division") desc = """ Percentage of time that allocation is stalled due to load buffer full""" class Metric_PCT_Mem_RSV_Stall_Cycles: name = "PCT_Mem_RSV_Stall_Cycles" domain = "" maxval = 0 errcount = 0 area = "Info.Buffer_Stalls" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_Mem_RSV_Stall_Cycles(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_Mem_RSV_Stall_Cycles zero division") desc = """ Percentage of time that allocation is stalled due to memory reservation stations full""" class Metric_PCT_Tpause_Cycles: name = "PCT_Tpause_Cycles" domain = "" maxval = 0 errcount = 0 area = "Info.Serialization " metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = PCT_Tpause_Cycles(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "PCT_Tpause_Cycles zero division") desc = """ Percentage of time that the core is stalled due to a TPAUSE or UMWAIT instruction""" class Metric_Turbo_Utilization: name = "Turbo_Utilization" domain = "" maxval = 0 errcount = 0 area = "Info.System" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Turbo_Utilization(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Turbo_Utilization zero division") desc = """ Average Frequency Utilization relative nominal frequency""" class Metric_Kernel_Utilization: name = "Kernel_Utilization" domain = "" maxval = 0 errcount = 0 area = "Info.System" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = Kernel_Utilization(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "Kernel_Utilization zero division") desc = """ Fraction of cycles spent in Kernel mode""" class Metric_CPU_Utilization: name = "CPU_Utilization" domain = "" maxval = 0 errcount = 0 area = "Info.System" metricgroup = frozenset([]) sibling = None def compute(self, EV): try: self.val = CPU_Utilization(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "CPU_Utilization zero division") desc = """ Average CPU Utilization""" class Metric_GFLOPs: name = "GFLOPs" domain = "" maxval = 0 errcount = 0 area = "Info.System" metricgroup = frozenset(['Flops']) sibling = None def compute(self, EV): try: self.val = GFLOPs(self, EV, 0) self.thresh = True except ZeroDivisionError: handle_error_metric(self, "GFLOPs zero division") desc = """ Giga Floating Point Operations Per Second. Aggregate across all supported options of: FP precisions, scalar and vector instructions, vector-width""" # Schedule class Setup: def __init__(self, r): o = dict() n = Frontend_Bound() ; r.run(n) ; o["Frontend_Bound"] = n n = IFetch_Latency() ; r.run(n) ; o["IFetch_Latency"] = n n = ICache_Misses() ; r.run(n) ; o["ICache_Misses"] = n n = ITLB_Misses() ; r.run(n) ; o["ITLB_Misses"] = n n = Branch_Detect() ; r.run(n) ; o["Branch_Detect"] = n n = Branch_Resteer() ; r.run(n) ; o["Branch_Resteer"] = n n = IFetch_Bandwidth() ; r.run(n) ; o["IFetch_Bandwidth"] = n n = Cisc() ; r.run(n) ; o["Cisc"] = n n = Decode() ; r.run(n) ; o["Decode"] = n n = Predecode() ; r.run(n) ; o["Predecode"] = n n = Other_FB() ; r.run(n) ; o["Other_FB"] = n n = Bad_Speculation() ; r.run(n) ; o["Bad_Speculation"] = n n = Branch_Mispredicts() ; r.run(n) ; o["Branch_Mispredicts"] = n n = Machine_Clears() ; r.run(n) ; o["Machine_Clears"] = n n = Nuke() ; r.run(n) ; o["Nuke"] = n n = Fast_Nuke() ; r.run(n) ; o["Fast_Nuke"] = n n = Backend_Bound() ; r.run(n) ; o["Backend_Bound"] = n n = Core_Bound() ; r.run(n) ; o["Core_Bound"] = n n = Allocation_Restriction() ; r.run(n) ; o["Allocation_Restriction"] = n n = Resource_Bound() ; r.run(n) ; o["Resource_Bound"] = n n = Mem_Scheduler() ; r.run(n) ; o["Mem_Scheduler"] = n n = Non_Mem_Scheduler() ; r.run(n) ; o["Non_Mem_Scheduler"] = n n = Register() ; r.run(n) ; o["Register"] = n n = Reorder_Buffer() ; r.run(n) ; o["Reorder_Buffer"] = n n = Serialization() ; r.run(n) ; o["Serialization"] = n n = Retiring() ; r.run(n) ; o["Retiring"] = n # parents o["IFetch_Latency"].parent = o["Frontend_Bound"] o["ICache_Misses"].parent = o["IFetch_Latency"] o["ITLB_Misses"].parent = o["IFetch_Latency"] o["Branch_Detect"].parent = o["IFetch_Latency"] o["Branch_Resteer"].parent = o["IFetch_Latency"] o["IFetch_Bandwidth"].parent = o["Frontend_Bound"] o["Cisc"].parent = o["IFetch_Bandwidth"] o["Decode"].parent = o["IFetch_Bandwidth"] o["Predecode"].parent = o["IFetch_Bandwidth"] o["Other_FB"].parent = o["IFetch_Bandwidth"] o["Branch_Mispredicts"].parent = o["Bad_Speculation"] o["Machine_Clears"].parent = o["Bad_Speculation"] o["Nuke"].parent = o["Machine_Clears"] o["Fast_Nuke"].parent = o["Machine_Clears"] o["Core_Bound"].parent = o["Backend_Bound"] o["Allocation_Restriction"].parent = o["Core_Bound"] o["Resource_Bound"].parent = o["Backend_Bound"] o["Mem_Scheduler"].parent = o["Resource_Bound"] o["Non_Mem_Scheduler"].parent = o["Resource_Bound"] o["Register"].parent = o["Resource_Bound"] o["Reorder_Buffer"].parent = o["Resource_Bound"] o["Serialization"].parent = o["Resource_Bound"] # user visible metrics n = Metric_PCT_Mem_Exec_Bound_Cycles() ; r.metric(n) ; o["PCT_Mem_Exec_Bound_Cycles"] = n n = Metric_PCT_Load_Miss_Bound_Cycles() ; r.metric(n) ; o["PCT_Load_Miss_Bound_Cycles"] = n n = Metric_PCT_DTLB_Miss_Bound_Cycles() ; r.metric(n) ; o["PCT_DTLB_Miss_Bound_Cycles"] = n n = Metric_PCT_IFetch_Miss_Bound_Cycles() ; r.metric(n) ; o["PCT_IFetch_Miss_Bound_Cycles"] = n n = Metric_IPC() ; r.metric(n) ; o["IPC"] = n n = Metric_CPI() ; r.metric(n) ; o["CPI"] = n n = Metric_UPI() ; r.metric(n) ; o["UPI"] = n n = Metric_FLOPc() ; r.metric(n) ; o["FLOPc"] = n n = Metric_IpBranch() ; r.metric(n) ; o["IpBranch"] = n n = Metric_IpCall() ; r.metric(n) ; o["IpCall"] = n n = Metric_IpFarBranch() ; r.metric(n) ; o["IpFarBranch"] = n n = Metric_IpMispredict() ; r.metric(n) ; o["IpMispredict"] = n n = Metric_IpMisp_Cond_Ntaken() ; r.metric(n) ; o["IpMisp_Cond_Ntaken"] = n n = Metric_IpMisp_Cond_Taken() ; r.metric(n) ; o["IpMisp_Cond_Taken"] = n n = Metric_IpMisp_Ret() ; r.metric(n) ; o["IpMisp_Ret"] = n n = Metric_IpMisp_Indirect() ; r.metric(n) ; o["IpMisp_Indirect"] = n n = Metric_IpFLOP() ; r.metric(n) ; o["IpFLOP"] = n n = Metric_IpFPArith_Scalar_SP() ; r.metric(n) ; o["IpFPArith_Scalar_SP"] = n n = Metric_IpFPArith_Scalar_DP() ; r.metric(n) ; o["IpFPArith_Scalar_DP"] = n n = Metric_IpFPArith_AVX128() ; r.metric(n) ; o["IpFPArith_AVX128"] = n n = Metric_Microcode_Uop_Ratio() ; r.metric(n) ; o["Microcode_Uop_Ratio"] = n n = Metric_FPDiv_Uop_Ratio() ; r.metric(n) ; o["FPDiv_Uop_Ratio"] = n n = Metric_IDiv_Uop_Ratio() ; r.metric(n) ; o["IDiv_Uop_Ratio"] = n n = Metric_X87_Uop_Ratio() ; r.metric(n) ; o["X87_Uop_Ratio"] = n n = Metric_IpLoad() ; r.metric(n) ; o["IpLoad"] = n n = Metric_IpStore() ; r.metric(n) ; o["IpStore"] = n n = Metric_MemLoad_Ratio() ; r.metric(n) ; o["MemLoad_Ratio"] = n n = Metric_Load_Splits_Ratio() ; r.metric(n) ; o["Load_Splits_Ratio"] = n n = Metric_Load_Locks_Ratio() ; r.metric(n) ; o["Load_Locks_Ratio"] = n n = Metric_PCT_Loads_with_StoreFwdBlk() ; r.metric(n) ; o["PCT_Loads_with_StoreFwdBlk"] = n n = Metric_PCT_Loads_with_AdressAliasing() ; r.metric(n) ; o["PCT_Loads_with_AdressAliasing"] = n n = Metric_PCT_LoadHead_with_STLBHit() ; r.metric(n) ; o["PCT_LoadHead_with_STLBHit"] = n n = Metric_PCT_LoadHead_with_Pagewalk() ; r.metric(n) ; o["PCT_LoadHead_with_Pagewalk"] = n n = Metric_PCT_LoadHead_with_StoreFwding() ; r.metric(n) ; o["PCT_LoadHead_with_StoreFwding"] = n n = Metric_PCT_LoadHead_with_OtherPipelineBlks() ; r.metric(n) ; o["PCT_LoadHead_with_OtherPipelineBlks"] = n n = Metric_PCT_LoadHead_with_L1miss() ; r.metric(n) ; o["PCT_LoadHead_with_L1miss"] = n n = Metric_Store_Bound() ; r.metric(n) ; o["Store_Bound"] = n n = Metric_Load_Bound() ; r.metric(n) ; o["Load_Bound"] = n n = Metric_L1_Bound() ; r.metric(n) ; o["L1_Bound"] = n n = Metric_PCT_LoadMissBound_with_L2Hit() ; r.metric(n) ; o["PCT_LoadMissBound_with_L2Hit"] = n n = Metric_PCT_LoadMissBound_with_L2Miss() ; r.metric(n) ; o["PCT_LoadMissBound_with_L2Miss"] = n n = Metric_PCT_LoadMissBound_with_L3Hit() ; r.metric(n) ; o["PCT_LoadMissBound_with_L3Hit"] = n n = Metric_PCT_LoadMissBound_with_L3Miss() ; r.metric(n) ; o["PCT_LoadMissBound_with_L3Miss"] = n n = Metric_PCT_IfetchMissBound_with_L2Hit() ; r.metric(n) ; o["PCT_IfetchMissBound_with_L2Hit"] = n n = Metric_PCT_IfetchMissBound_with_L2Miss() ; r.metric(n) ; o["PCT_IfetchMissBound_with_L2Miss"] = n n = Metric_PCT_IfetchMissBound_with_L3Hit() ; r.metric(n) ; o["PCT_IfetchMissBound_with_L3Hit"] = n n = Metric_PCT_IfetchMissBound_with_L3Miss() ; r.metric(n) ; o["PCT_IfetchMissBound_with_L3Miss"] = n n = Metric_Branch_Mispredict_Ratio() ; r.metric(n) ; o["Branch_Mispredict_Ratio"] = n n = Metric_Branch_Mispredict_to_Unknown_Branch_Ratio() ; r.metric(n) ; o["Branch_Mispredict_to_Unknown_Branch_Ratio"] = n n = Metric_Machine_Clears_FP_Assist_PKI() ; r.metric(n) ; o["Machine_Clears_FP_Assist_PKI"] = n n = Metric_Machine_Clears_Page_Fault_PKI() ; r.metric(n) ; o["Machine_Clears_Page_Fault_PKI"] = n n = Metric_Machine_Clears_SMC_PKI() ; r.metric(n) ; o["Machine_Clears_SMC_PKI"] = n n = Metric_PCT_Store_Buffer_Stall_Cycles() ; r.metric(n) ; o["PCT_Store_Buffer_Stall_Cycles"] = n n = Metric_PCT_Load_Buffer_Stall_Cycles() ; r.metric(n) ; o["PCT_Load_Buffer_Stall_Cycles"] = n n = Metric_PCT_Mem_RSV_Stall_Cycles() ; r.metric(n) ; o["PCT_Mem_RSV_Stall_Cycles"] = n n = Metric_PCT_Tpause_Cycles() ; r.metric(n) ; o["PCT_Tpause_Cycles"] = n n = Metric_Turbo_Utilization() ; r.metric(n) ; o["Turbo_Utilization"] = n n = Metric_Kernel_Utilization() ; r.metric(n) ; o["Kernel_Utilization"] = n n = Metric_CPU_Utilization() ; r.metric(n) ; o["CPU_Utilization"] = n n = Metric_GFLOPs() ; r.metric(n) ; o["GFLOPs"] = n # references between groups o["Resource_Bound"].Core_Bound = o["Core_Bound"] # siblings cross-tree