OV - exec - Loop 65

0x406200 LDUR	D0, [X11, #496]    [4]

0x406204 LDR	W14, [X8, X13,LSL #2]    [1]

0x406208 STUR	W14, [X10, #488]    [3]

0x40620c LDR	W14, [X9, X13,LSL #2]    [2]

0x406210 ADD	X13, X13, #1

0x406214 STUR	D0, [X10, #496]    [3]

0x406218 LDUR	D0, [X11, #504]    [4]

0x40621c STUR	W14, [X10, #492]    [3]

0x406220 STUR	D0, [X10, #504]    [3]

0x406224 LDR	D0, [X11], #24    [4]

0x406228 STR	D0, [X10]    [3]

0x40622c LDUR	D0, [X12, #496]    [5]

0x406230 STR	D0, [X10, #8]    [3]

0x406234 LDUR	D0, [X12, #504]    [5]

0x406238 STR	D0, [X10, #16]    [3]

0x40623c LDR	D0, [X12], #24    [5]

0x406240 STR	D0, [X10, #24]    [3]

0x406244 ADD	X10, X10, #56

0x406248 CMP	X13, X25

0x40624c B.LT	406200

/home/hbollore/qaas/qaas-runs/174-108-7908/intel/CoMD/build/CoMD/CoMD/src-openmp/haloExchange.c: 621 - 630

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

621:    for (int ii=begin, iTmp=0; ii<end; ++ii, ++iTmp)

622:    {

623:       tmp[iTmp].gid  = atoms->gid[ii];

624:       tmp[iTmp].type = atoms->iSpecies[ii];

625:       tmp[iTmp].rx =   atoms->r[ii][0];

626:       tmp[iTmp].ry =   atoms->r[ii][1];

627:       tmp[iTmp].rz =   atoms->r[ii][2];

628:       tmp[iTmp].px =   atoms->p[ii][0];

629:       tmp[iTmp].py =   atoms->p[ii][1];

630:       tmp[iTmp].pz =   atoms->p[ii][2];

Coverage (%)	Name	Source Location	Module
►100.00+	redistributeAtoms.omp_outlined	timestep.c:153	exec
○	__kmp_invoke_microtask		libomp.so

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	2.21
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.78
Bottlenecks	P12, P13, P14,
Function	sortAtomsInCell
Source	haloExchange.c:621-630
Source loop unroll info	not unrolled or unrolled with no peel/tail loop
Source loop unroll confidence level	max
Unroll/vectorization loop type	NA
Unroll factor	NA
CQA cycles	5.33
CQA cycles if no scalar integer	4.00
CQA cycles if FP arith vectorized	5.33
CQA cycles if fully vectorized	2.42
Front-end cycles	2.50
P0 cycles	0.50
P1 cycles	0.50
P2 cycles	0.92
P3 cycles	0.92
P4 cycles	0.83
P5 cycles	0.83
P6 cycles	0.75
P7 cycles	0.75
P8 cycles	3.00
P9 cycles	3.00
P10 cycles	0.00
P11 cycles	0.00
P12 cycles	5.33
P13 cycles	5.33
P14 cycles	5.33
P15 cycles	1.00
P16 cycles	1.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	1
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	20.00
Nb uops	20.00
Nb loads	NA
Nb stores	8.00
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	21.00
Bytes prefetched	0.00
Bytes loaded	56.00
Bytes stored	56.00
Stride 0	2.00
Stride 1	0.00
Stride n	0.00
Stride unknown	0.00
Stride indirect	0.00
Vectorization ratio all	0.00
Vectorization ratio load	0.00
Vectorization ratio store	0.00
Vectorization ratio mul	NA
Vectorization ratio add_sub	NA
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	NA
Vector-efficiency ratio all	43.75
Vector-efficiency ratio load	43.75
Vector-efficiency ratio store	43.75
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	NA

Metric	Value
CQA speedup if no scalar integer	1.33
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	2.21
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.78
Bottlenecks	P12, P13, P14,
Function	sortAtomsInCell
Source	haloExchange.c:621-630
Source loop unroll info	not unrolled or unrolled with no peel/tail loop
Source loop unroll confidence level	max
Unroll/vectorization loop type	NA
Unroll factor	NA
CQA cycles	5.33
CQA cycles if no scalar integer	4.00
CQA cycles if FP arith vectorized	5.33
CQA cycles if fully vectorized	2.42
Front-end cycles	2.50
P0 cycles	0.50
P1 cycles	0.50
P2 cycles	0.92
P3 cycles	0.92
P4 cycles	0.83
P5 cycles	0.83
P6 cycles	0.75
P7 cycles	0.75
P8 cycles	3.00
P9 cycles	3.00
P10 cycles	0.00
P11 cycles	0.00
P12 cycles	5.33
P13 cycles	5.33
P14 cycles	5.33
P15 cycles	1.00
P16 cycles	1.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	1
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	20.00
Nb uops	20.00
Nb loads	NA
Nb stores	8.00
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	21.00
Bytes prefetched	0.00
Bytes loaded	56.00
Bytes stored	56.00
Stride 0	2.00
Stride 1	0.00
Stride n	0.00
Stride unknown	0.00
Stride indirect	0.00
Vectorization ratio all	0.00
Vectorization ratio load	0.00
Vectorization ratio store	0.00
Vectorization ratio mul	NA
Vectorization ratio add_sub	NA
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	NA
Vector-efficiency ratio all	43.75
Vector-efficiency ratio load	43.75
Vector-efficiency ratio store	43.75
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	NA

Path /

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

Function	sortAtomsInCell
Source file and lines	haloExchange.c:621-630
Module	exec

The loop is defined in /home/hbollore/qaas/qaas-runs/174-108-7908/intel/CoMD/build/CoMD/CoMD/src-openmp/haloExchange.c:621-630.

The related source loop is not unrolled or unrolled with no peel/tail loop.

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 5.33 to 4.00 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. Only 43% of vector register length is used (average across all VPU instructions). By vectorizing your loop, you can lower the cost of an iteration from 5.33 to 2.42 cycles (2.21x 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 is loading 56 bytes. The binary loop is storing 56 bytes.

General properties

nb instructions	20
loop length	80
nb stack references	0

Front-end

FIT IN UOP CACHE

front end

2.50 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15	P16
uops	0.50	0.50	0.92	0.92	0.83	0.83	0.75	0.75	3.00	3.00	0.00	0.00	5.33	5.33	5.33	1.00	1.00
cycles	0.50	0.50	0.92	0.92	0.83	0.83	0.75	0.75	3.00	3.00	0.00	0.00	5.33	5.33	5.33	1.00	1.00

Execution ports to units layout:

P0: BRU
P1: BRU
P2: ALU
P3: ALU
P4: ALU
P5: ALU
P6: ALU
P7: ALU
P8 (128 bits): VPU, FP store data, ALU, DIV/SQRT
P9 (128 bits): VPU, ALU, FP store data
P10 (128 bits): VPU, ALU, DIV/SQRT
P11 (128 bits): ALU, VPU
P12 (256 bits): store address, load
P13 (256 bits): store address, load
P14 (256 bits): load
P15 (64 bits): store data
P16 (64 bits): store data

Cycles executing div or sqrt instructions	NA
Longest recurrence chain latency (RecMII)	1.00

Cycles summary

Front-end	2.50
Data deps.	1.00
Overall L1	5.33

Vectorization ratios

all	0%
load	0%
store	0%
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	NA (no other vectorizable/vectorized instructions)

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 5.33 cycles. At this rate:

10% of peak load performance is reached (10.50 out of 96.00 bytes loaded per cycle (GB/s @ 1GHz))
21% of peak store performance is reached (10.50 out of 48.00 bytes stored per cycle (GB/s @ 1GHz))

ASM code

In the binary file, the address of the loop is: 406200

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P12	P13	P14	P15	P16	Latency	Recip. throughput	Vectorization
LDUR D0, [X11, #496]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
LDR W14, [X8, X13,LSL #2]	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%)
STUR W14, [X10, #488]	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0.50	0.50	1	0.50	scal (25.0%)
LDR W14, [X9, X13,LSL #2]	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%)
ADD X13, X13, #1	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	1	0.17	N/A
STUR D0, [X10, #496]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDUR D0, [X11, #504]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STUR W14, [X10, #492]	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0.50	0.50	1	0.50	scal (25.0%)
STUR D0, [X10, #504]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDR D0, [X11], #24	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STR D0, [X10]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDUR D0, [X12, #496]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STR D0, [X10, #8]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDUR D0, [X12, #504]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STR D0, [X10, #16]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDR D0, [X12], #24	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STR D0, [X10, #24]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
ADD X10, X10, #56	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	1	0.17	N/A
CMP X13, X25	1	0	0	0.25	0.25	0	0	0.25	0.25	0	0	0	0	0	0	0	1	0.33	N/A
B.LT 406200 <sortAtomsInCell+0x80>	1	0.50	0.50	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0.50	N/A

Function	sortAtomsInCell
Source file and lines	haloExchange.c:621-630
Module	exec

The loop is defined in /home/hbollore/qaas/qaas-runs/174-108-7908/intel/CoMD/build/CoMD/CoMD/src-openmp/haloExchange.c:621-630.

The related source loop is not unrolled or unrolled with no peel/tail loop.

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 5.33 to 4.00 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. Only 43% of vector register length is used (average across all VPU instructions). By vectorizing your loop, you can lower the cost of an iteration from 5.33 to 2.42 cycles (2.21x 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 is loading 56 bytes. The binary loop is storing 56 bytes.

General properties

nb instructions	20
loop length	80
nb stack references	0

Front-end

FIT IN UOP CACHE

front end

2.50 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15	P16
uops	0.50	0.50	0.92	0.92	0.83	0.83	0.75	0.75	3.00	3.00	0.00	0.00	5.33	5.33	5.33	1.00	1.00
cycles	0.50	0.50	0.92	0.92	0.83	0.83	0.75	0.75	3.00	3.00	0.00	0.00	5.33	5.33	5.33	1.00	1.00

Execution ports to units layout:

P0: BRU
P1: BRU
P2: ALU
P3: ALU
P4: ALU
P5: ALU
P6: ALU
P7: ALU
P8 (128 bits): VPU, FP store data, ALU, DIV/SQRT
P9 (128 bits): VPU, ALU, FP store data
P10 (128 bits): VPU, ALU, DIV/SQRT
P11 (128 bits): ALU, VPU
P12 (256 bits): store address, load
P13 (256 bits): store address, load
P14 (256 bits): load
P15 (64 bits): store data
P16 (64 bits): store data

Cycles executing div or sqrt instructions	NA
Longest recurrence chain latency (RecMII)	1.00

Cycles summary

Front-end	2.50
Data deps.	1.00
Overall L1	5.33

Vectorization ratios

all	0%
load	0%
store	0%
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	NA (no other vectorizable/vectorized instructions)

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 5.33 cycles. At this rate:

10% of peak load performance is reached (10.50 out of 96.00 bytes loaded per cycle (GB/s @ 1GHz))
21% of peak store performance is reached (10.50 out of 48.00 bytes stored per cycle (GB/s @ 1GHz))

ASM code

In the binary file, the address of the loop is: 406200

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P12	P13	P14	P15	P16	Latency	Recip. throughput	Vectorization
LDUR D0, [X11, #496]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
LDR W14, [X8, X13,LSL #2]	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%)
STUR W14, [X10, #488]	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0.50	0.50	1	0.50	scal (25.0%)
LDR W14, [X9, X13,LSL #2]	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%)
ADD X13, X13, #1	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	1	0.17	N/A
STUR D0, [X10, #496]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDUR D0, [X11, #504]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STUR W14, [X10, #492]	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0.50	0.50	1	0.50	scal (25.0%)
STUR D0, [X10, #504]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDR D0, [X11], #24	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STR D0, [X10]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDUR D0, [X12, #496]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STR D0, [X10, #8]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDUR D0, [X12, #504]	1	0	0	0	0	0	0	0	0	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STR D0, [X10, #16]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDR D0, [X12], #24	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0.33	0.33	0.33	0	0	6	0.33	scal (50.0%)
STR D0, [X10, #24]	1	0	0	0	0	0	0	0	0	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
ADD X10, X10, #56	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	1	0.17	N/A
CMP X13, X25	1	0	0	0.25	0.25	0	0	0.25	0.25	0	0	0	0	0	0	0	1	0.33	N/A
B.LT 406200 <sortAtomsInCell+0x80>	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

Cycles and memory resources usage

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

Cycles and memory resources usage

ASM code