OV - exec - Loop 242

	Loop Id: 242	Module: exec	Source: par_coarsen.c:2356-2372	Coverage: 0.03%

0x422060 LDUR	X17, [X29, #504]

0x422064 CMP	X8, X17

0x422068 ADD	X8, X8, #1

0x42206c B.GE	421ffc

0x422070 LDR	X17, [X11, X8,LSL #3]

0x422074 LDR	D1, [X12, X17,LSL #3]

0x422078 FCMP	D1, D0

0x42207c B.LE	422060

0x422080 ADD	X18, X17, #1

0x422084 LDR	X0, [X13, X17,LSL #3]

0x422088 LDR	X1, [X13, X18,LSL #3]

0x42208c CMP	X0, X1

0x422090 B.GE	4220e0

0x422094 LDR	X1, [X19]

0x422098 B	4220b4

  (245) 0x4220a0 STR	XZR, [X1, X2,LSL #3]

  (245) 0x4220a4 LDR	X2, [X13, X18,LSL #3]

  (245) 0x4220a8 ADD	X0, X0, #1

  (245) 0x4220ac CMP	X0, X2

  (245) 0x4220b0 B.GE	4220e0

  (245) 0x4220b4 LDR	X2, [X14, X0,LSL #3]

  (245) 0x4220b8 LDR	D2, [X12, X2,LSL #3]

  (245) 0x4220bc FCMP	D2, D0

  (245) 0x4220c0 B.LE	4220a4

  (245) 0x4220c4 FCMP	D1, D2

  (245) 0x4220c8 B.GT	4220a0

  (245) 0x4220cc FCMP	D2, D1

  (245) 0x4220d0 B.LE	4220a4

  (245) 0x4220d4 STR	XZR, [X1, X17,LSL #3]

  (245) 0x4220d8 B	4220a4

0x4220e0 LDR	X0, [X15, X17,LSL #3]

0x4220e4 LDR	X1, [X15, X18,LSL #3]

0x4220e8 CMP	X0, X1

0x4220ec B.GE	422060

/home/eoseret/qaas/qaas_runs/178-188-3659/intel/AMG/build/AMG/AMG/parcsr_ls/par_coarsen.c: 2356 - 2372

--------------------------------------------------------------------------------

2356:         for (ig = 0; ig < graph_size; ig++)

2357:         {

2358:            i = graph_array[ig];

2359:            if (measure_array[i] > 1)

2360:            {

2361:               for (jS = S_diag_i[i]; jS < S_diag_i[i+1]; jS++)

2362:               {

2363:                  j = S_diag_j[jS];

2364:                  if (measure_array[j] > 1)

2365:                  {

2366:                     if (measure_array[i] > measure_array[j])

2367:                        CF_marker[j] = 0;

2368:                     else if (measure_array[j] > measure_array[i])

2369:                        CF_marker[i] = 0;

2370:                  }

2371:               } /* for each local neighbor j of i */

2372:               for (jS = S_offd_i[i]; jS < S_offd_i[i+1]; jS++)

Coverage (%)	Name	Source Location	Module
►98.05+	__kmp_invoke_microtask		libomp.so
○	__kmp_invoke_task_func		libomp.so
○	__kmp_launch_thread		libomp.so
○	__kmp_launch_worker(void*)		libomp.so
○	start_thread		libc.so.6
○	thread_start		libc.so.6
►1.30+	__kmp_invoke_microtask		libomp.so
○	__kmp_invoke_task_func		libomp.so
○	__kmp_fork_call		libomp.so
○	__kmpc_fork_call		libomp.so
○	hypre_BoomerAMGCoarsenPMIS	par_coarsen.c:2393	exec
○	hypre_BoomerAMGSetup	par_amg_setup.c:598	exec
○	hypre_PCGSetup	pcg.c:234	exec
○	main	amg.c:398	exec
○	__libc_start_call_main		libc.so.6
○	__libc_start_main		libc.so.6
○	_start		exec

min	med	avg	max

Percentile Index	10	20	30	40	50	60	70	80	90	100
Value

min	med	avg	max

Percentile Index	10	20	30	40	50	60	70	80	90	100
Value

Path /

Metric	Value
CQA speedup if no scalar integer	1.33
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	4.00
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.07
Bottlenecks	P10, P11, P12,
Function	hypre_BoomerAMGCoarsenPMIS.omp_outlined.18
Source	par_coarsen.c:2356-2361,par_coarsen.c:2372-2372
Source loop unroll info	NA
Source loop unroll confidence level	NA
Unroll/vectorization loop type	NA
Unroll factor	NA
CQA cycles	2.67
CQA cycles if no scalar integer	2.00
CQA cycles if FP arith vectorized	2.67
CQA cycles if fully vectorized	0.67
Front-end cycles	2.38
P0 cycles	2.50
P1 cycles	2.50
P2 cycles	1.25
P3 cycles	1.25
P4 cycles	1.25
P5 cycles	1.25
P6 cycles	1.00
P7 cycles	0.00
P8 cycles	0.00
P9 cycles	0.00
P10 cycles	2.67
P11 cycles	2.67
P12 cycles	2.67
P13 cycles	0.00
P14 cycles	0.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	NA
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	19.00
Nb uops	19.00
Nb loads	NA
Nb stores	0.00
Nb stack references	0.00
FLOP/cycle	0.00
Nb FLOP add-sub	0.00
Nb FLOP mul	0.00
Nb FLOP fma	0.00
Nb FLOP div	0.00
Nb FLOP rcp	0.00
Nb FLOP sqrt	0.00
Nb FLOP rsqrt	0.00
Bytes/cycle	0.00
Bytes prefetched	0.00
Bytes loaded	0.00
Bytes stored	0.00
Stride 0	NA
Stride 1	NA
Stride n	NA
Stride unknown	NA
Stride indirect	NA
Vectorization ratio all	0.00
Vectorization ratio load	0.00
Vectorization ratio store	NA
Vectorization ratio mul	NA
Vectorization ratio add_sub	NA
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	0.00
Vector-efficiency ratio all	25.00
Vector-efficiency ratio load	25.00
Vector-efficiency ratio store	NA
Vector-efficiency ratio mul	NA
Vector-efficiency ratio add_sub	NA
Vector-efficiency ratio fma	NA
Vector-efficiency ratio div_sqrt	NA
Vector-efficiency ratio other	25.00

Metric	Value
CQA speedup if no scalar integer	1.33
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	4.00
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.07
Bottlenecks	P10, P11, P12,
Function	hypre_BoomerAMGCoarsenPMIS.omp_outlined.18
Source	par_coarsen.c:2356-2361,par_coarsen.c:2372-2372
Source loop unroll info	NA
Source loop unroll confidence level	NA
Unroll/vectorization loop type	NA
Unroll factor	NA
CQA cycles	2.67
CQA cycles if no scalar integer	2.00
CQA cycles if FP arith vectorized	2.67
CQA cycles if fully vectorized	0.67
Front-end cycles	2.38
P0 cycles	2.50
P1 cycles	2.50
P2 cycles	1.25
P3 cycles	1.25
P4 cycles	1.25
P5 cycles	1.25
P6 cycles	1.00
P7 cycles	0.00
P8 cycles	0.00
P9 cycles	0.00
P10 cycles	2.67
P11 cycles	2.67
P12 cycles	2.67
P13 cycles	0.00
P14 cycles	0.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	NA
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	19.00
Nb uops	19.00
Nb loads	NA
Nb stores	0.00
Nb stack references	0.00
FLOP/cycle	0.00
Nb FLOP add-sub	0.00
Nb FLOP mul	0.00
Nb FLOP fma	0.00
Nb FLOP div	0.00
Nb FLOP rcp	0.00
Nb FLOP sqrt	0.00
Nb FLOP rsqrt	0.00
Bytes/cycle	0.00
Bytes prefetched	0.00
Bytes loaded	0.00
Bytes stored	0.00
Stride 0	NA
Stride 1	NA
Stride n	NA
Stride unknown	NA
Stride indirect	NA
Vectorization ratio all	0.00
Vectorization ratio load	0.00
Vectorization ratio store	NA
Vectorization ratio mul	NA
Vectorization ratio add_sub	NA
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	0.00
Vector-efficiency ratio all	25.00
Vector-efficiency ratio load	25.00
Vector-efficiency ratio store	NA
Vector-efficiency ratio mul	NA
Vector-efficiency ratio add_sub	NA
Vector-efficiency ratio fma	NA
Vector-efficiency ratio div_sqrt	NA
Vector-efficiency ratio other	25.00

Path /

Average path: Display a virtual path defined by average values of all real paths

Function	hypre_BoomerAMGCoarsenPMIS.omp_outlined.18
Source file and lines	par_coarsen.c:2356-2372
Module	exec

The loop is defined in /home/eoseret/qaas/qaas_runs/178-188-3659/intel/AMG/build/AMG/AMG/parcsr_ls/par_coarsen.c:2356-2372.

Analyzed code is defined in /home/eoseret/qaas/qaas_runs/178-188-3659/intel/AMG/build/AMG/AMG/parcsr_ls/par_coarsen.c:2356-2361,2372.

Warnings:

Non-innermost loop: analyzing only self part (ignoring child loops).
Ignoring paths for analysis
Failed to get the number of paths
RecMII not computed since number of paths is unknown or > max_paths
Streams not analyzed since number of paths is unknown or > max_paths

gain
potential
hint
expert

Code clean check

Detected a slowdown caused by scalar integer instructions (typically used for address computation). By removing them, you can lower the cost of an iteration from 2.67 to 2.00 cycles (1.33x speedup).

Workaround

Try to reorganize arrays of structures to structures of arrays
Consider to permute loops (see vectorization gain report)

Vectorization

Your loop is not vectorized. 4 data elements could be processed at once in vector registers. By vectorizing your loop, you can lower the cost of an iteration from 2.67 to 0.67 cycles (4.00x speedup).

Details

All VPU instructions are used in scalar version (process only one data element in vector registers). Since your execution units are vector units, only a vectorized loop can use their full power.

Workaround

Try another compiler or update/tune your current one
Remove inter-iterations dependences from your loop and make it unit-stride:
- If your arrays have 2 or more dimensions, check whether elements are accessed contiguously and, otherwise, try to permute loops accordingly: C storage order is row-major: for(i) for(j) a[j][i] = b[j][i]; (slow, non stride 1) => for(i) for(j) a[i][j] = b[i][j]; (fast, stride 1)
- If your loop streams arrays of structures (AoS), try to use structures of arrays instead (SoA): for(i) a[i].x = b[i].x; (slow, non stride 1) => for(i) a.x[i] = b.x[i]; (fast, stride 1)

No data for this section

Matching between your loop (in the source code) and the binary loop

The binary loop does not contain any FP arithmetical operations. The binary loop does not load or store any data.

General properties

nb instructions	19
nb uops	19
loop length	76
used w registers	0
used x registers	11
used b registers	0
used h registers	0
used s registers	0
used d registers	2
used q registers	0
used v registers	0
used z registers	0
nb stack references	0

Front-end

MACRO FUSION NOT POSSIBLE FIT IN UOP CACHE

micro-operation queue	2.38 cycles
front end	2.38 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14
uops	2.50	2.50	1.25	1.25	1.25	1.25	1.00	0.00	0.00	0.00	2.67	2.67	2.67	0.00	0.00
cycles	2.50	2.50	1.25	1.25	1.25	1.25	1.00	0.00	0.00	0.00	2.67	2.67	2.67	0.00	0.00

Execution ports to units layout:

P0: BRU
P1: BRU
P2: ALU
P3: ALU
P4: ALU
P5: ALU
P6 (128 bits): VPU, FP store data, ALU, DIV/SQRT
P7 (128 bits): VPU, ALU, FP store data
P8 (128 bits): VPU, ALU, DIV/SQRT
P9 (128 bits): ALU, VPU
P10 (256 bits): store address, load
P11 (256 bits): store address, load
P12 (256 bits): load
P13 (64 bits): store data
P14 (64 bits): store data

Cycles executing div or sqrt instructions

Cycles summary

Front-end	2.38
Dispatch	2.67
Overall L1	2.67

Vectorization ratios

INT

all	0%
load	0%
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
other	0%

all	0%
load	NA (no load vectorizable/vectorized instructions)
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	0%

INT+FP

all	0%
load	0%
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	0%

Vector efficiency ratios

INT

all	25%
load	25%
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
other	25%

all	25%
load	NA (no load vectorizable/vectorized instructions)
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	25%

INT+FP

all	25%
load	25%
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	25%

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 2.67 cycles.

Front-end bottlenecks

Found no such bottlenecks.

ASM code

In the binary file, the address of the loop is: 422060

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P10	P11	P12	Latency	Recip. throughput	Vectorization
LDUR X17, [X29, #504]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
CMP X8, X17	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.33	scal (25.0%)
ADD X8, X8, #1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.25	N/A
B.GE 421ffc <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x9c>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A
LDR X17, [X11, X8,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
LDR D1, [X12, X17,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	6	0.33	scal (25.0%)
FCMP D1, D0	1	0	0	0	0	0	0	1	0	0	0	2	1	scal (25.0%)
B.LE 422060 <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x100>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A
ADD X18, X17, #1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.25	N/A
LDR X0, [X13, X17,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
LDR X1, [X13, X18,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
CMP X0, X1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.33	scal (25.0%)
B.GE 4220e0 <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x180>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A
LDR X1, [X19]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
B 4220b4 <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x154>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A
LDR X0, [X15, X17,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
LDR X1, [X15, X18,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
CMP X0, X1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.33	N/A
B.GE 422060 <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x100>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A

Function	hypre_BoomerAMGCoarsenPMIS.omp_outlined.18
Source file and lines	par_coarsen.c:2356-2372
Module	exec

Non-innermost loop: analyzing only self part (ignoring child loops).
Ignoring paths for analysis
Failed to get the number of paths
RecMII not computed since number of paths is unknown or > max_paths
Streams not analyzed since number of paths is unknown or > max_paths

gain
potential
hint
expert

Code clean check

Detected a slowdown caused by scalar integer instructions (typically used for address computation). By removing them, you can lower the cost of an iteration from 2.67 to 2.00 cycles (1.33x speedup).

Workaround

Try to reorganize arrays of structures to structures of arrays
Consider to permute loops (see vectorization gain report)

Vectorization

Your loop is not vectorized. 4 data elements could be processed at once in vector registers. By vectorizing your loop, you can lower the cost of an iteration from 2.67 to 0.67 cycles (4.00x speedup).

Details

All VPU instructions are used in scalar version (process only one data element in vector registers). Since your execution units are vector units, only a vectorized loop can use their full power.

Workaround

Try another compiler or update/tune your current one
Remove inter-iterations dependences from your loop and make it unit-stride:
- If your arrays have 2 or more dimensions, check whether elements are accessed contiguously and, otherwise, try to permute loops accordingly: C storage order is row-major: for(i) for(j) a[j][i] = b[j][i]; (slow, non stride 1) => for(i) for(j) a[i][j] = b[i][j]; (fast, stride 1)
- If your loop streams arrays of structures (AoS), try to use structures of arrays instead (SoA): for(i) a[i].x = b[i].x; (slow, non stride 1) => for(i) a.x[i] = b.x[i]; (fast, stride 1)

No data for this section

Matching between your loop (in the source code) and the binary loop

The binary loop does not contain any FP arithmetical operations. The binary loop does not load or store any data.

General properties

nb instructions	19
nb uops	19
loop length	76
used w registers	0
used x registers	11
used b registers	0
used h registers	0
used s registers	0
used d registers	2
used q registers	0
used v registers	0
used z registers	0
nb stack references	0

Front-end

MACRO FUSION NOT POSSIBLE FIT IN UOP CACHE

micro-operation queue	2.38 cycles
front end	2.38 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14
uops	2.50	2.50	1.25	1.25	1.25	1.25	1.00	0.00	0.00	0.00	2.67	2.67	2.67	0.00	0.00
cycles	2.50	2.50	1.25	1.25	1.25	1.25	1.00	0.00	0.00	0.00	2.67	2.67	2.67	0.00	0.00

Execution ports to units layout:

P0: BRU
P1: BRU
P2: ALU
P3: ALU
P4: ALU
P5: ALU
P6 (128 bits): VPU, FP store data, ALU, DIV/SQRT
P7 (128 bits): VPU, ALU, FP store data
P8 (128 bits): VPU, ALU, DIV/SQRT
P9 (128 bits): ALU, VPU
P10 (256 bits): store address, load
P11 (256 bits): store address, load
P12 (256 bits): load
P13 (64 bits): store data
P14 (64 bits): store data

Cycles executing div or sqrt instructions

Cycles summary

Front-end	2.38
Dispatch	2.67
Overall L1	2.67

Vectorization ratios

INT

all	0%
load	0%
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
other	0%

all	0%
load	NA (no load vectorizable/vectorized instructions)
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	0%

INT+FP

all	0%
load	0%
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	0%

Vector efficiency ratios

INT

all	25%
load	25%
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
other	25%

all	25%
load	NA (no load vectorizable/vectorized instructions)
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	25%

INT+FP

all	25%
load	25%
store	NA (no store vectorizable/vectorized instructions)
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	25%

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 2.67 cycles.

Front-end bottlenecks

Found no such bottlenecks.

ASM code

In the binary file, the address of the loop is: 422060

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P10	P11	P12	Latency	Recip. throughput	Vectorization
LDUR X17, [X29, #504]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
CMP X8, X17	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.33	scal (25.0%)
ADD X8, X8, #1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.25	N/A
B.GE 421ffc <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x9c>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A
LDR X17, [X11, X8,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
LDR D1, [X12, X17,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	6	0.33	scal (25.0%)
FCMP D1, D0	1	0	0	0	0	0	0	1	0	0	0	2	1	scal (25.0%)
B.LE 422060 <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x100>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A
ADD X18, X17, #1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.25	N/A
LDR X0, [X13, X17,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
LDR X1, [X13, X18,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
CMP X0, X1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.33	scal (25.0%)
B.GE 4220e0 <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x180>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A
LDR X1, [X19]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
B 4220b4 <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x154>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A
LDR X0, [X15, X17,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
LDR X1, [X15, X18,LSL #3]	1	0	0	0	0	0	0	0	0.33	0.33	0.33	4	0.33	N/A
CMP X0, X1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	1	0.33	N/A
B.GE 422060 <hypre_BoomerAMGCoarsenPMIS.omp_outlined.18+0x100>	1	0.50	0.50	0	0	0	0	0	0	0	0	1	0.50	N/A

Report Configuration

Code clean check

Workaround

Vectorization

Details

Workaround

Matching between your loop (in the source code) and the binary loop

General properties

Front-end

Back-end

Cycles summary

Vectorization ratios

Vector efficiency ratios

Cycles and memory resources usage

Front-end bottlenecks

ASM code

Code clean check

Workaround

Vectorization

Details

Workaround

Matching between your loop (in the source code) and the binary loop

General properties

Front-end

Back-end

Cycles summary

Vectorization ratios

Vector efficiency ratios

Cycles and memory resources usage

Front-end bottlenecks

ASM code