OV - exec - Loop 66

0x4064a0 LDUR	D0, [X12, #496]    [5]

0x4064a4 LDUR	W15, [X12, #488]    [5]

0x4064a8 STR	W15, [X8, X13,LSL #2]    [1]

0x4064ac LDUR	W15, [X12, #492]    [5]

0x4064b0 STUR	D0, [X11, #496]    [4]

0x4064b4 LDUR	D0, [X12, #504]    [5]

0x4064b8 STR	W15, [X9, X13,LSL #2]    [2]

0x4064bc ADD	X13, X13, #1

0x4064c0 STUR	D0, [X11, #504]    [4]

0x4064c4 LDR	D0, [X12]    [5]

0x4064c8 STR	D0, [X11], #24    [4]

0x4064cc LDR	D0, [X12, #8]    [5]

0x4064d0 STUR	D0, [X10, #496]    [3]

0x4064d4 LDR	D0, [X12, #16]    [5]

0x4064d8 STUR	D0, [X10, #504]    [3]

0x4064dc LDR	D0, [X12, #24]    [5]

0x4064e0 ADD	X12, X12, #56

0x4064e4 STR	D0, [X10], #24    [3]

0x4064e8 CMP	X13, X14

0x4064ec B.LT	4064a0

/home/hbollore/qaas/qaas-runs/174-108-7908/intel/CoMD/build/CoMD/CoMD/src-openmp/haloExchange.c: 633 - 642

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

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

634:    {

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

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

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

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

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

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

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

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

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:633-642
Source loop unroll info	unrolled by 4
Source loop unroll confidence level	high
Unroll/vectorization loop type	NA
Unroll factor	1
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:633-642
Source loop unroll info	unrolled by 4
Source loop unroll confidence level	high
Unroll/vectorization loop type	NA
Unroll factor	1
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:633-642
Module	exec

The loop is defined in /home/hbollore/qaas/qaas-runs/174-108-7908/intel/CoMD/build/CoMD/CoMD/src-openmp/haloExchange.c:633-642.

The related source loop is unrolled by 4 (including vectorization).

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)

Unrolling/vectorization cost

This loop is peel/tail of a unrolled/vectorized loop. If its cost is not negligible compared to the main (unrolled/vectorized) loop, unrolling/vectorization is counterproductive due to low trip count.

Details

The more iterations the main loop is processing, the higher the trip count must be to amortize peel/tail overhead.

Workaround

recompile with -fprofile-instr-generate, execute ,merge raw profiles with 'llvm-profdata merge -o default.profdata default.profraw' and recompile with -fprofile-instr-use (profile-guided optimization)
hardcode most frequent values of loop bounds by adding specialized paths.:
- For instance, replace for (i=0; i<n; i++) foo(i) with: switch (n) { case (4): for (i=0; i<4; i++) foo(i); break; case (6): for (i=0; i<6; i++) foo(i); break; default : for (i=0; i<n; i++) foo(i); break; }

Vectorization

Your loop is not vectorized. Only 43% of vector register length is used (average across all VPU instructions).

Details

All VPU instructions are used in scalar version (process only one data element in vector registers).

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: 4064a0

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P12	P13	P14	P15	P16	Latency	Recip. throughput	Vectorization
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%)
LDUR W15, [X12, #488]	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%)
STR W15, [X8, X13,LSL #2]	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%)
LDUR W15, [X12, #492]	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 D0, [X11, #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, [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 W15, [X9, X13,LSL #2]	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%)
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, [X11, #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, [X12]	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, [X11], #24	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDR D0, [X12, #8]	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 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%)
LDR D0, [X12, #16]	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 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, [X12, #24]	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%)
ADD X12, X12, #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
STR D0, [X10], #24	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
CMP X13, X14	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 4064a0 <sortAtomsInCell+0x320>	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:633-642
Module	exec

The loop is defined in /home/hbollore/qaas/qaas-runs/174-108-7908/intel/CoMD/build/CoMD/CoMD/src-openmp/haloExchange.c:633-642.

The related source loop is unrolled by 4 (including vectorization).

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)

Unrolling/vectorization cost

This loop is peel/tail of a unrolled/vectorized loop. If its cost is not negligible compared to the main (unrolled/vectorized) loop, unrolling/vectorization is counterproductive due to low trip count.

Details

The more iterations the main loop is processing, the higher the trip count must be to amortize peel/tail overhead.

Workaround

recompile with -fprofile-instr-generate, execute ,merge raw profiles with 'llvm-profdata merge -o default.profdata default.profraw' and recompile with -fprofile-instr-use (profile-guided optimization)
hardcode most frequent values of loop bounds by adding specialized paths.:
- For instance, replace for (i=0; i<n; i++) foo(i) with: switch (n) { case (4): for (i=0; i<4; i++) foo(i); break; case (6): for (i=0; i<6; i++) foo(i); break; default : for (i=0; i<n; i++) foo(i); break; }

Vectorization

Your loop is not vectorized. Only 43% of vector register length is used (average across all VPU instructions).

Details

All VPU instructions are used in scalar version (process only one data element in vector registers).

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: 4064a0

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P12	P13	P14	P15	P16	Latency	Recip. throughput	Vectorization
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%)
LDUR W15, [X12, #488]	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%)
STR W15, [X8, X13,LSL #2]	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%)
LDUR W15, [X12, #492]	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 D0, [X11, #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, [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 W15, [X9, X13,LSL #2]	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%)
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, [X11, #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, [X12]	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, [X11], #24	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
LDR D0, [X12, #8]	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 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%)
LDR D0, [X12, #16]	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 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, [X12, #24]	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%)
ADD X12, X12, #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
STR D0, [X10], #24	1	0	0	0.17	0.17	0.17	0.17	0.17	0.17	0.50	0.50	0.50	0.50	0	0	0	2	0.50	scal (50.0%)
CMP X13, X14	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 4064a0 <sortAtomsInCell+0x320>	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

Unrolling/vectorization cost

Details

Workaround

Vectorization

Details

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

Unrolling/vectorization cost

Details

Workaround

Vectorization

Details

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