OV - exec - Loop 3660

0x4a4b00 CMP	X0, X19

0x4a4b04 STR	D0, [X13, X20,LSL #3]

0x4a4b08 ORR	X20, XZR, X0

0x4a4b0c B.EQ	4a55bc

0x4a4b10 LDR	D0, [X8, X20,LSL #3]

0x4a4b14 ADD	X0, X20, #1

0x4a4b18 ORR	X5, XZR, X16

0x4a4b1c LDR	X16, [X9, X0,LSL #3]

0x4a4b20 SUBS	X2, X16, X5

0x4a4b24 B.LE	4a4b00

0x4a4b28 CMP	X2, #2

0x4a4b2c B.CS	4a4b40

0x4a4b30 ORR	X1, XZR, X5

0x4a4b34 B	4a4b94

0x4a4b94 SUB	W2, W16, W1

0x4a4b98 ORR	X3, XZR, X1

0x4a4b9c ANDS	X2, X2, #0x3

0x4a4ba0 B.EQ	4a4bc0

  (3663) 0x4a4ba4 LDR	X4, [X12, X3,LSL #3]

  (3663) 0x4a4ba8 LDR	D1, [X10, X3,LSL #3]

  (3663) 0x4a4bac ADD	X3, X3, #1

  (3663) 0x4a4bb0 SUBS	X2, X2, #1

  (3663) 0x4a4bb4 LDR	D2, [X11, X4,LSL #3]

  (3663) 0x4a4bb8 FMSUB	D0, D2, D1, D0

  (3663) 0x4a4bbc B.NE	4a4ba4

0x4a4bc0 SUB	X1, X1, X16

0x4a4bc4 CMN	X1, #4

0x4a4bc8 B.HI	4a4b00

0x4a4bcc SUB	X1, X16, X3

0x4a4bd0 ADD	X2, X17, X3,LSL #3

0x4a4bd4 ADD	X3, X18, X3,LSL #3

0x4a4bd8 HINT	#0

0x4a4bdc HINT	#0

  (3662) 0x4a4be0 LDP	X4, X5, [X2, #1008]

  (3662) 0x4a4be4 LDP	D2, D3, [X3, #1008]

  (3662) 0x4a4be8 SUBS	X1, X1, #4

  (3662) 0x4a4bec LDR	D4, [X11, X5,LSL #3]

  (3662) 0x4a4bf0 LDR	D1, [X11, X4,LSL #3]

  (3662) 0x4a4bf4 FMUL	D3, D4, D3

  (3662) 0x4a4bf8 FMADD	D1, D1, D2, D3

  (3662) 0x4a4bfc LDP	X4, X5, [X2], #32

  (3662) 0x4a4c00 LDR	D4, [X11, X4,LSL #3]

  (3662) 0x4a4c04 LDP	D2, D3, [X3], #32

  (3662) 0x4a4c08 FMADD	D1, D4, D2, D1

  (3662) 0x4a4c0c LDR	D2, [X11, X5,LSL #3]

  (3662) 0x4a4c10 FMADD	D1, D2, D3, D1

  (3662) 0x4a4c14 FSUB	D0, D0, S1

  (3662) 0x4a4c18 B.NE	4a4be0

0x4a4c1c B	4a4b00

/home/eoseret/qaas/qaas_runs/178-188-3659/intel/AMG/build/AMG/AMG/seq_mv/csr_matvec.c: 307 - 314

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

307:             for (i = iBegin; i < iEnd; i++)

308:             {

309:                tempx = b_data[i];

310:                for (jj = A_i[i]; jj < A_i[i+1]; jj++)

311:                {

312:                   tempx -= A_data[jj] * x_data[A_j[jj]];

313:                }

314:                y_data[i] = tempx;

Coverage (%)	Name	Module
►99.22+	__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

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	4.50
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	4.80
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.07
Bottlenecks	P2, P3, P4, P5,
Function	hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14
Source	csr_matvec.c:307-310,csr_matvec.c:314-314
Source loop unroll info	NA
Source loop unroll confidence level	NA
Unroll/vectorization loop type	NA
Unroll factor	NA
CQA cycles	3.75
CQA cycles if no scalar integer	0.83
CQA cycles if FP arith vectorized	3.75
CQA cycles if fully vectorized	0.78
Front-end cycles	3.13
P0 cycles	3.50
P1 cycles	3.50
P2 cycles	3.75
P3 cycles	3.75
P4 cycles	3.75
P5 cycles	3.75
P6 cycles	0.50
P7 cycles	0.50
P8 cycles	0.00
P9 cycles	0.00
P10 cycles	1.17
P11 cycles	0.83
P12 cycles	1.00
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	27.00
Nb uops	25.00
Nb loads	NA
Nb stores	1.00
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	0.00
Vectorization ratio mul	NA
Vectorization ratio add_sub	0.00
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	0.00
Vector-efficiency ratio all	24.11
Vector-efficiency ratio load	25.00
Vector-efficiency ratio store	25.00
Vector-efficiency ratio mul	NA
Vector-efficiency ratio add_sub	22.50
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	4.50
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	4.80
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.07
Bottlenecks	P2, P3, P4, P5,
Function	hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14
Source	csr_matvec.c:307-310,csr_matvec.c:314-314
Source loop unroll info	NA
Source loop unroll confidence level	NA
Unroll/vectorization loop type	NA
Unroll factor	NA
CQA cycles	3.75
CQA cycles if no scalar integer	0.83
CQA cycles if FP arith vectorized	3.75
CQA cycles if fully vectorized	0.78
Front-end cycles	3.13
P0 cycles	3.50
P1 cycles	3.50
P2 cycles	3.75
P3 cycles	3.75
P4 cycles	3.75
P5 cycles	3.75
P6 cycles	0.50
P7 cycles	0.50
P8 cycles	0.00
P9 cycles	0.00
P10 cycles	1.17
P11 cycles	0.83
P12 cycles	1.00
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	27.00
Nb uops	25.00
Nb loads	NA
Nb stores	1.00
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	0.00
Vectorization ratio mul	NA
Vectorization ratio add_sub	0.00
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	0.00
Vector-efficiency ratio all	24.11
Vector-efficiency ratio load	25.00
Vector-efficiency ratio store	25.00
Vector-efficiency ratio mul	NA
Vector-efficiency ratio add_sub	22.50
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_CSRMatrixMatvecOutOfPlace.omp_outlined.14
Source file and lines	csr_matvec.c:307-314
Module	exec

The loop is defined in /home/eoseret/qaas/qaas_runs/178-188-3659/intel/AMG/build/AMG/AMG/seq_mv/csr_matvec.c:307-314.

Analyzed code is defined in /home/eoseret/qaas/qaas_runs/178-188-3659/intel/AMG/build/AMG/AMG/seq_mv/csr_matvec.c:307-310,314.

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 3.75 to 0.83 cycles (4.50x 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. Only 24% of vector register length is used (average across all VPU instructions). By vectorizing your loop, you can lower the cost of an iteration from 3.75 to 0.78 cycles (4.80x 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	27
nb uops	25
loop length	108
used w registers	3
used x registers	14
used b registers	0
used h registers	0
used s registers	0
used d registers	1
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	3.13 cycles
front end	3.13 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14
uops	3.50	3.50	3.75	3.75	3.75	3.75	0.50	0.50	0.00	0.00	1.17	0.83	1.00	0.00	0.00
cycles	3.50	3.50	3.75	3.75	3.75	3.75	0.50	0.50	0.00	0.00	1.17	0.83	1.00	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

NA

Cycles summary

Front-end	3.13
Dispatch	3.75
Overall L1	3.75

Vectorization ratios

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

Vector efficiency ratios

all	24%
load	25%
store	25%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	22%
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 3.75 cycles.

Front-end bottlenecks

Found no such bottlenecks.

ASM code

In the binary file, the address of the loop is: 4a4b00

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	Latency	Recip. throughput	Vectorization
CMP X0, X19	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
STR D0, [X13, X20,LSL #3]	1	0	0	0	0	0	0	0.50	0.50	0	0	0.50	0.50	0	0	0	2	0.50	scal (25.0%)
ORR X20, XZR, X0	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	N/A
B.EQ 4a55bc <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x11ec>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
LDR D0, [X8, X20,LSL #3]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (25.0%)
ADD X0, X20, #1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	N/A
ORR X5, XZR, X16	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
LDR X16, [X9, X0,LSL #3]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	4	0.33	scal (25.0%)
SUBS X2, X16, X5	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
B.LE 4a4b00 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x730>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
CMP X2, #2	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
B.CS 4a4b40 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x770>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
ORR X1, XZR, X5	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
B 4a4b94 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x7c4>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
SUB W2, W16, W1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (12.5%)
ORR X3, XZR, X1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	N/A
ANDS X2, X2, #0x3	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
B.EQ 4a4bc0 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x7f0>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
SUB X1, X1, X16	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
CMN X1, #4	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
B.HI 4a4b00 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x730>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
SUB X1, X16, X3	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
ADD X2, X17, X3,LSL #3	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
ADD X3, X18, X3,LSL #3	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	N/A
HINT #0																			N/A
HINT #0																			N/A
B 4a4b00 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x730>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A

Function	hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14
Source file and lines	csr_matvec.c:307-314
Module	exec

The loop is defined in /home/eoseret/qaas/qaas_runs/178-188-3659/intel/AMG/build/AMG/AMG/seq_mv/csr_matvec.c:307-314.

Analyzed code is defined in /home/eoseret/qaas/qaas_runs/178-188-3659/intel/AMG/build/AMG/AMG/seq_mv/csr_matvec.c:307-310,314.

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 3.75 to 0.83 cycles (4.50x 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. Only 24% of vector register length is used (average across all VPU instructions). By vectorizing your loop, you can lower the cost of an iteration from 3.75 to 0.78 cycles (4.80x 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	27
nb uops	25
loop length	108
used w registers	3
used x registers	14
used b registers	0
used h registers	0
used s registers	0
used d registers	1
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	3.13 cycles
front end	3.13 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14
uops	3.50	3.50	3.75	3.75	3.75	3.75	0.50	0.50	0.00	0.00	1.17	0.83	1.00	0.00	0.00
cycles	3.50	3.50	3.75	3.75	3.75	3.75	0.50	0.50	0.00	0.00	1.17	0.83	1.00	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

NA

Cycles summary

Front-end	3.13
Dispatch	3.75
Overall L1	3.75

Vectorization ratios

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

Vector efficiency ratios

all	24%
load	25%
store	25%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	22%
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 3.75 cycles.

Front-end bottlenecks

Found no such bottlenecks.

ASM code

In the binary file, the address of the loop is: 4a4b00

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	Latency	Recip. throughput	Vectorization
CMP X0, X19	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
STR D0, [X13, X20,LSL #3]	1	0	0	0	0	0	0	0.50	0.50	0	0	0.50	0.50	0	0	0	2	0.50	scal (25.0%)
ORR X20, XZR, X0	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	N/A
B.EQ 4a55bc <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x11ec>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
LDR D0, [X8, X20,LSL #3]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (25.0%)
ADD X0, X20, #1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	N/A
ORR X5, XZR, X16	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
LDR X16, [X9, X0,LSL #3]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	4	0.33	scal (25.0%)
SUBS X2, X16, X5	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
B.LE 4a4b00 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x730>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
CMP X2, #2	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
B.CS 4a4b40 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x770>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
ORR X1, XZR, X5	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
B 4a4b94 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x7c4>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
SUB W2, W16, W1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (12.5%)
ORR X3, XZR, X1	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	N/A
ANDS X2, X2, #0x3	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
B.EQ 4a4bc0 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x7f0>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
SUB X1, X1, X16	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
CMN X1, #4	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.33	scal (25.0%)
B.HI 4a4b00 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x730>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A
SUB X1, X16, X3	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
ADD X2, X17, X3,LSL #3	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	scal (25.0%)
ADD X3, X18, X3,LSL #3	1	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	0	0	0	1	0.25	N/A
HINT #0																			N/A
HINT #0																			N/A
B 4a4b00 <hypre_CSRMatrixMatvecOutOfPlace.omp_outlined.14+0x730>	1	0.50	0.50	0	0	0	0	0	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