OV - exec - Loop 878

	Loop Id: 878	Module: exec	Source: inner_product.hpp:155-155 [...]	Coverage: 0.06%

0x266a20 VMOVUPD	(%RDI),%XMM4    [3]

0x266a24 VMOVUPD	0x10(%RDI),%XMM5    [3]

0x266a29 VMOVUPD	0x30(%RDI),%XMM7    [3]

0x266a2e VMOVUPD	0x40(%RDI),%XMM8    [3]

0x266a33 VMOVUPD	0x60(%RDI),%XMM9    [3]

0x266a38 VMOVUPD	0x90(%RDI),%XMM11    [3]

0x266a40 VMOVUPD	0x50(%RDI),%XMM28    [3]

0x266a47 VMOVUPD	0x80(%RDI),%XMM2    [3]

0x266a4f VMOVUPD	0xb0(%RDI),%XMM3    [3]

0x266a57 VMOVUPD	0x20(%RDI),%XMM6    [3]

0x266a5c VMOVUPD	-0x30(%R13,%RDX,1),%XMM12    [2]

0x266a63 VMOVUPD	-0x20(%R13,%RDX,1),%XMM13    [2]

0x266a6a VMOVUPD	-0x10(%R13,%RDX,1),%XMM14    [2]

0x266a71 VMOVUPD	(%R13,%RDX,1),%XMM15    [2]

0x266a78 ADD	$0x40,%RDX

0x266a7c VBLENDPD	$0x1,%XMM4,%XMM5,%XMM0

0x266a82 VSHUFPD	$0x1,%XMM6,%XMM4,%XMM4

0x266a87 VBLENDPD	$0x1,%XMM5,%XMM6,%XMM5

0x266a8d VMOVAPD	%XMM0,-0x60(%RBP)    [1]

0x266a92 VBLENDPD	$0x1,%XMM7,%XMM8,%XMM0

0x266a98 VSHUFPD	$0x1,%XMM28,%XMM7,%XMM7

0x266a9f VFMADD231PD	%XMM4,%XMM12,%XMM20

0x266aa5 VFMADD231PD	%XMM5,%XMM12,%XMM24

0x266aab VMOVAPD	%XMM0,%XMM29

0x266ab1 VMOVUPD	0x70(%RDI),%XMM0    [3]

0x266ab6 VFMADD231PD	-0x60(%RBP),%XMM12,%XMM16    [1]

0x266abd VFMADD231PD	%XMM29,%XMM13,%XMM17

0x266ac3 VFMADD231PD	%XMM7,%XMM13,%XMM21

0x266ac9 VBLENDPD	$0x1,%XMM9,%XMM0,%XMM10

0x266acf VSHUFPD	$0x1,%XMM2,%XMM9,%XMM9

0x266ad4 VBLENDPD	$0x1,%XMM0,%XMM2,%XMM0

0x266ada VMOVAPD	%XMM10,%XMM30

0x266ae0 VMOVUPD	0xa0(%RDI),%XMM10    [3]

0x266ae8 VFMADD231PD	%XMM30,%XMM14,%XMM18

0x266aee VFMADD231PD	%XMM9,%XMM14,%XMM22

0x266af4 VFMADD231PD	%XMM0,%XMM14,%XMM26

0x266afa ADD	$0xc0,%RDI

0x266b01 VBLENDPD	$0x1,%XMM11,%XMM10,%XMM1

0x266b07 VSHUFPD	$0x1,%XMM3,%XMM11,%XMM11

0x266b0c VBLENDPD	$0x1,%XMM10,%XMM3,%XMM2

0x266b12 VMOVAPD	%XMM1,%XMM31

0x266b18 VMOVAPD	%XMM28,%XMM1

0x266b1e VBLENDPD	$0x1,%XMM8,%XMM1,%XMM1

0x266b24 VFMADD231PD	%XMM31,%XMM15,%XMM19

0x266b2a VFMADD231PD	%XMM11,%XMM15,%XMM23

0x266b30 VFMADD231PD	%XMM2,%XMM15,%XMM27

0x266b36 VFMADD231PD	%XMM1,%XMM13,%XMM25

0x266b3c CMP	%RDX,%R12

0x266b3f JNE	266a20

/home/eoseret/qaas_runs_ZEN5/173-938-0042/intel/miniqmc/build/miniqmc/src/Platforms/CPU/SIMD/inner_product.hpp: 155 - 155

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

155:   for (int i = 0; i < n; i++)

/home/eoseret/qaas_runs_ZEN5/173-938-0042/intel/miniqmc/build/miniqmc/src/Numerics/PETE/OperatorTags.h: 63 - 94

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

63:     return (a * b);

[...]

94:     (const_cast<T1&>(a) += b);

Coverage (%)	Name	Source Location	Module
►67.40+	qmcplusplus::WaveFunction::eva[...]	WaveFunction.cpp:170	exec
○	main.omp_outlined	miniqmc.cpp:379	exec
○	__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
○	__GI___clone3		libc.so.6
►29.25+	qmcplusplus::WaveFunction::eva[...]	WaveFunction.cpp:171	exec
○	main.omp_outlined	miniqmc.cpp:379	exec
○	__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
○	__GI___clone3		libc.so.6
►2.32+	qmcplusplus::WaveFunction::eva[...]	WaveFunction.cpp:170	exec
○	main.omp_outlined	miniqmc.cpp:379	exec
○	__kmp_invoke_microtask		libomp.so
○	__kmp_invoke_task_func		libomp.so
○	__kmp_fork_call		libomp.so
○	__kmpc_fork_call		libomp.so
○	main	miniqmc.cpp:378	exec
○	__libc_start_call_main		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	1.00
CQA speedup if FP arith vectorized	1.82
CQA speedup if fully vectorized	4.00
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.67
Bottlenecks	P10, P11,
Function	miniqmcreference::DiracDeterminantRef >::evaluateLog(qmcplusplus::ParticleSet&, qmcplusplus::ParticleAttrib, std::allocator > >&, qmcplusplus::ParticleAttrib >&)
Source	inner_product.hpp:155-155,OperatorTags.h:63-63,OperatorTags.h:94-94
Source loop unroll info	unrolled by 8
Source loop unroll confidence level	max
Unroll/vectorization loop type	main
Unroll factor	8
CQA cycles	10.00
CQA cycles if no scalar integer	10.00
CQA cycles if FP arith vectorized	5.50
CQA cycles if fully vectorized	2.50
Front-end cycles	6.00
P0 cycles	0.50
P1 cycles	0.50
P2 cycles	0.50
P3 cycles	0.50
P4 cycles	0.50
P5 cycles	0.50
P6 cycles	4.50
P7 cycles	4.50
P8 cycles	4.50
P9 cycles	4.50
P10 cycles	10.00
P11 cycles	10.00
P12 cycles	2.00
P13 cycles	2.00
P14 cycles	0.50
P15 cycles	0.50
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	4
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	49.00
Nb uops	48.00
Nb loads	17.00
Nb stores	1.00
Nb stack references	1.00
FLOP/cycle	4.80
Nb FLOP add-sub	0.00
Nb FLOP mul	0.00
Nb FLOP fma	24.00
Nb FLOP div	0.00
Nb FLOP rcp	0.00
Nb FLOP sqrt	0.00
Nb FLOP rsqrt	0.00
Bytes/cycle	28.80
Bytes prefetched	0.00
Bytes loaded	272.00
Bytes stored	16.00
Stride 0	1.00
Stride 1	2.00
Stride n	0.00
Stride unknown	0.00
Stride indirect	0.00
Vectorization ratio all	100.00
Vectorization ratio load	100.00
Vectorization ratio store	100.00
Vectorization ratio mul	NA
Vectorization ratio add_sub	NA
Vectorization ratio fma	100.00
Vectorization ratio div_sqrt	NA
Vectorization ratio other	100.00
Vector-efficiency ratio all	25.00
Vector-efficiency ratio load	25.00
Vector-efficiency ratio store	25.00
Vector-efficiency ratio mul	NA
Vector-efficiency ratio add_sub	NA
Vector-efficiency ratio fma	25.00
Vector-efficiency ratio div_sqrt	NA
Vector-efficiency ratio other	25.00

Metric	Value
CQA speedup if no scalar integer	1.00
CQA speedup if FP arith vectorized	1.82
CQA speedup if fully vectorized	4.00
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.67
Bottlenecks	P10, P11,
Function	miniqmcreference::DiracDeterminantRef >::evaluateLog(qmcplusplus::ParticleSet&, qmcplusplus::ParticleAttrib, std::allocator > >&, qmcplusplus::ParticleAttrib >&)
Source	inner_product.hpp:155-155,OperatorTags.h:63-63,OperatorTags.h:94-94
Source loop unroll info	unrolled by 8
Source loop unroll confidence level	max
Unroll/vectorization loop type	main
Unroll factor	8
CQA cycles	10.00
CQA cycles if no scalar integer	10.00
CQA cycles if FP arith vectorized	5.50
CQA cycles if fully vectorized	2.50
Front-end cycles	6.00
P0 cycles	0.50
P1 cycles	0.50
P2 cycles	0.50
P3 cycles	0.50
P4 cycles	0.50
P5 cycles	0.50
P6 cycles	4.50
P7 cycles	4.50
P8 cycles	4.50
P9 cycles	4.50
P10 cycles	10.00
P11 cycles	10.00
P12 cycles	2.00
P13 cycles	2.00
P14 cycles	0.50
P15 cycles	0.50
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	4
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	49.00
Nb uops	48.00
Nb loads	17.00
Nb stores	1.00
Nb stack references	1.00
FLOP/cycle	4.80
Nb FLOP add-sub	0.00
Nb FLOP mul	0.00
Nb FLOP fma	24.00
Nb FLOP div	0.00
Nb FLOP rcp	0.00
Nb FLOP sqrt	0.00
Nb FLOP rsqrt	0.00
Bytes/cycle	28.80
Bytes prefetched	0.00
Bytes loaded	272.00
Bytes stored	16.00
Stride 0	1.00
Stride 1	2.00
Stride n	0.00
Stride unknown	0.00
Stride indirect	0.00
Vectorization ratio all	100.00
Vectorization ratio load	100.00
Vectorization ratio store	100.00
Vectorization ratio mul	NA
Vectorization ratio add_sub	NA
Vectorization ratio fma	100.00
Vectorization ratio div_sqrt	NA
Vectorization ratio other	100.00
Vector-efficiency ratio all	25.00
Vector-efficiency ratio load	25.00
Vector-efficiency ratio store	25.00
Vector-efficiency ratio mul	NA
Vector-efficiency ratio add_sub	NA
Vector-efficiency ratio fma	25.00
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	miniqmcreference::DiracDeterminantRef >::evaluateLog(qmcplusplus::ParticleSet&, qmcplusplus::ParticleAttrib, std::allocator > >&, qmcplusplus::ParticleAttrib >&)
Source file and lines	inner_product.hpp:155-155
Module	exec

The loop is defined in:

/home/eoseret/qaas_runs_ZEN5/173-938-0042/intel/miniqmc/build/miniqmc/src/Platforms/CPU/SIMD/inner_product.hpp:155
/home/eoseret/qaas_runs_ZEN5/173-938-0042/intel/miniqmc/build/miniqmc/src/Numerics/PETE/OperatorTags.h:63,94

It is main loop of related source loop which is unrolled by 8 (including vectorization).

gain
potential
hint
expert

Vectorization

Your loop is vectorized, but using only 128 out of 512 bits (SSE/AVX-128 instructions on AVX-512 processors).

By fully vectorizing your loop, you can lower the cost of an iteration from 10.00 to 2.50 cycles (4.00x speedup).

Details

All SSE/AVX instructions are used in vector version (process two or more data elements in vector registers). Since your execution units are vector units, only a fully vectorized loop can use their full power.

Workaround

Pass to your compiler a micro-architecture specialization option:
- use march=native
Use vector aligned instructions:
1. align your arrays on 64 bytes boundaries: replace { void *p = malloc (size); } with { void *p; posix_memalign (&p, 64, size); }.
2. inform your compiler that your arrays are vector aligned: if array 'foo' is 64 bytes-aligned, define a pointer 'p_foo' as __builtin_assume_aligned (foo, 64) and use it instead of 'foo' in the loop.

Execution units bottlenecks

Performance is limited by execution of FP multiply or FMA (fused multiply-add) operations (the FP multiply/FMA unit is a bottleneck). By removing all these bottlenecks, you can lower the cost of an iteration from 10.00 to 6.00 cycles (1.67x speedup).

Workaround

Reduce the number of FP multiply/FMA instructions

FMA

Detected 24 FMA (fused multiply-add) operations.

Type of elements and instruction set

12 SSE or AVX instructions are processing arithmetic or math operations on double precision FP elements in vector mode (two at a time).

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

The binary loop is composed of 48 FP arithmetical operations:

24: addition or subtraction (all inside FMA instructions)
24: multiply (all inside FMA instructions)

The binary loop is loading 272 bytes (34 double precision FP elements). The binary loop is storing 16 bytes (2 double precision FP elements).

Arithmetic intensity

Arithmetic intensity is 0.17 FP operations per loaded or stored byte.

General properties

nb instructions	49
nb uops	48
loop length	293
used x86 registers	5
used mmx registers	0
used xmm registers	32
used ymm registers	0
used zmm registers	0
nb stack references	1

Front-end

ASSUMED MACRO FUSION FIT IN UOP CACHE

micro-operation queue	6.00 cycles
front end	6.00 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15
uops	0.50	0.50	0.50	0.50	0.50	0.50	4.50	4.50	4.50	4.50	10.00	10.00	2.00	2.00	0.50	0.50
cycles	0.50	0.50	0.50	0.50	0.50	0.50	4.50	4.50	4.50	4.50	10.00	10.00	2.00	2.00	0.50	0.50

Execution ports to units layout:

P0: ALU
P1: ALU
P2: ALU
P3: ALU, BRU
P4: ALU, BRU
P5: ALU, BRU
P6 (512 bits): store address, load
P7 (512 bits): store address, load
P8 (512 bits): store address, load
P9 (512 bits): store address, load
P10 (512 bits): VPU, DIV/SQRT
P11 (512 bits): VPU, DIV/SQRT
P12 (512 bits): VPU
P13 (512 bits): VPU
P14 (512 bits): FP store data
P15 (512 bits): FP store data

Cycles executing div or sqrt instructions	NA
Longest recurrence chain latency (RecMII)	4.00

Cycles summary

Front-end	6.00
Dispatch	10.00
Data deps.	4.00
Overall L1	10.00

Vectorization ratios

all	100%
load	100%
store	100%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	100%
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	100%

Vector efficiency ratios

all	25%
load	25%
store	25%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	25%
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 10.00 cycles. At this rate:

10% of peak load performance is reached (27.20 out of 256.00 bytes loaded per cycle (GB/s @ 1GHz))
1% of peak store performance is reached (1.60 out of 128.00 bytes stored per cycle (GB/s @ 1GHz))

Front-end bottlenecks

Found no such bottlenecks.

ASM code

In the binary file, the address of the loop is: 266a20

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15	Latency	Recip. throughput	Vectorization
VMOVUPD (%RDI),%XMM4	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x10(%RDI),%XMM5	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x30(%RDI),%XMM7	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x40(%RDI),%XMM8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x60(%RDI),%XMM9	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x90(%RDI),%XMM11	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x50(%RDI),%XMM28	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x80(%RDI),%XMM2	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0xb0(%RDI),%XMM3	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x20(%RDI),%XMM6	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD -0x30(%R13,%RDX,1),%XMM12	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD -0x20(%R13,%RDX,1),%XMM13	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD -0x10(%R13,%RDX,1),%XMM14	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD (%R13,%RDX,1),%XMM15	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
ADD $0x40,%RDX	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	0	0	0	1	0.17	N/A
VBLENDPD $0x1,%XMM4,%XMM5,%XMM0	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VSHUFPD $0x1,%XMM6,%XMM4,%XMM4	1	0	0	0	0	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	1	0.25	vect (25.0%)
VBLENDPD $0x1,%XMM5,%XMM6,%XMM5	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VMOVAPD %XMM0,-0x60(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	0.50	vect (25.0%)
VBLENDPD $0x1,%XMM7,%XMM8,%XMM0	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VSHUFPD $0x1,%XMM28,%XMM7,%XMM7	1	0	0	0	0	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	1	0.25	vect (25.0%)
VFMADD231PD %XMM4,%XMM12,%XMM20	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM5,%XMM12,%XMM24	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VMOVAPD %XMM0,%XMM29	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.17	vect (25.0%)
VMOVUPD 0x70(%RDI),%XMM0	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VFMADD231PD -0x60(%RBP),%XMM12,%XMM16	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM29,%XMM13,%XMM17	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM7,%XMM13,%XMM21	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VBLENDPD $0x1,%XMM9,%XMM0,%XMM10	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VSHUFPD $0x1,%XMM2,%XMM9,%XMM9	1	0	0	0	0	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	1	0.25	vect (25.0%)
VBLENDPD $0x1,%XMM0,%XMM2,%XMM0	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VMOVAPD %XMM10,%XMM30	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.17	vect (25.0%)
VMOVUPD 0xa0(%RDI),%XMM10	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VFMADD231PD %XMM30,%XMM14,%XMM18	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM9,%XMM14,%XMM22	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM0,%XMM14,%XMM26	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
ADD $0xc0,%RDI	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	0	0	0	1	0.17	N/A
VBLENDPD $0x1,%XMM11,%XMM10,%XMM1	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VSHUFPD $0x1,%XMM3,%XMM11,%XMM11	1	0	0	0	0	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	1	0.25	vect (25.0%)
VBLENDPD $0x1,%XMM10,%XMM3,%XMM2	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VMOVAPD %XMM1,%XMM31	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.17	vect (25.0%)
VMOVAPD %XMM28,%XMM1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.17	vect (25.0%)
VBLENDPD $0x1,%XMM8,%XMM1,%XMM1	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VFMADD231PD %XMM31,%XMM15,%XMM19	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM11,%XMM15,%XMM23	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM2,%XMM15,%XMM27	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM1,%XMM13,%XMM25	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
CMP %RDX,%R12	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	0	0	0	1	0.17	N/A
JNE 266a20 <_ZN16miniqmcreference19DiracDeterminantRefIN11qmcplusplus13DelayedUpdateIddEEE11evaluateLogERNS1_11ParticleSetERNS1_14ParticleAttribINS1_10TinyVectorIdLj3EEESaIS9_EEERNS7_IdSaIdEEE+0x210>	1	0	0	0	0.33	0.33	0.33	0	0	0	0	0	0	0	0	0	0	1	0.50-1	N/A

Function	miniqmcreference::DiracDeterminantRef >::evaluateLog(qmcplusplus::ParticleSet&, qmcplusplus::ParticleAttrib, std::allocator > >&, qmcplusplus::ParticleAttrib >&)
Source file and lines	inner_product.hpp:155-155
Module	exec

The loop is defined in:

/home/eoseret/qaas_runs_ZEN5/173-938-0042/intel/miniqmc/build/miniqmc/src/Platforms/CPU/SIMD/inner_product.hpp:155
/home/eoseret/qaas_runs_ZEN5/173-938-0042/intel/miniqmc/build/miniqmc/src/Numerics/PETE/OperatorTags.h:63,94

It is main loop of related source loop which is unrolled by 8 (including vectorization).

gain
potential
hint
expert

Vectorization

Your loop is vectorized, but using only 128 out of 512 bits (SSE/AVX-128 instructions on AVX-512 processors).

By fully vectorizing your loop, you can lower the cost of an iteration from 10.00 to 2.50 cycles (4.00x speedup).

Details

Workaround

Pass to your compiler a micro-architecture specialization option:
- use march=native
Use vector aligned instructions:
1. align your arrays on 64 bytes boundaries: replace { void *p = malloc (size); } with { void *p; posix_memalign (&p, 64, size); }.
2. inform your compiler that your arrays are vector aligned: if array 'foo' is 64 bytes-aligned, define a pointer 'p_foo' as __builtin_assume_aligned (foo, 64) and use it instead of 'foo' in the loop.

Execution units bottlenecks

Workaround

Reduce the number of FP multiply/FMA instructions

FMA

Detected 24 FMA (fused multiply-add) operations.

Type of elements and instruction set

12 SSE or AVX instructions are processing arithmetic or math operations on double precision FP elements in vector mode (two at a time).

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

The binary loop is composed of 48 FP arithmetical operations:

24: addition or subtraction (all inside FMA instructions)
24: multiply (all inside FMA instructions)

The binary loop is loading 272 bytes (34 double precision FP elements). The binary loop is storing 16 bytes (2 double precision FP elements).

Arithmetic intensity

Arithmetic intensity is 0.17 FP operations per loaded or stored byte.

General properties

nb instructions	49
nb uops	48
loop length	293
used x86 registers	5
used mmx registers	0
used xmm registers	32
used ymm registers	0
used zmm registers	0
nb stack references	1

Front-end

ASSUMED MACRO FUSION FIT IN UOP CACHE

micro-operation queue	6.00 cycles
front end	6.00 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15
uops	0.50	0.50	0.50	0.50	0.50	0.50	4.50	4.50	4.50	4.50	10.00	10.00	2.00	2.00	0.50	0.50
cycles	0.50	0.50	0.50	0.50	0.50	0.50	4.50	4.50	4.50	4.50	10.00	10.00	2.00	2.00	0.50	0.50

Execution ports to units layout:

P0: ALU
P1: ALU
P2: ALU
P3: ALU, BRU
P4: ALU, BRU
P5: ALU, BRU
P6 (512 bits): store address, load
P7 (512 bits): store address, load
P8 (512 bits): store address, load
P9 (512 bits): store address, load
P10 (512 bits): VPU, DIV/SQRT
P11 (512 bits): VPU, DIV/SQRT
P12 (512 bits): VPU
P13 (512 bits): VPU
P14 (512 bits): FP store data
P15 (512 bits): FP store data

Cycles executing div or sqrt instructions	NA
Longest recurrence chain latency (RecMII)	4.00

Cycles summary

Front-end	6.00
Dispatch	10.00
Data deps.	4.00
Overall L1	10.00

Vectorization ratios

all	100%
load	100%
store	100%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	100%
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	100%

Vector efficiency ratios

all	25%
load	25%
store	25%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	25%
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 10.00 cycles. At this rate:

10% of peak load performance is reached (27.20 out of 256.00 bytes loaded per cycle (GB/s @ 1GHz))
1% of peak store performance is reached (1.60 out of 128.00 bytes stored per cycle (GB/s @ 1GHz))

Front-end bottlenecks

Found no such bottlenecks.

ASM code

In the binary file, the address of the loop is: 266a20

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15	Latency	Recip. throughput	Vectorization
VMOVUPD (%RDI),%XMM4	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x10(%RDI),%XMM5	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x30(%RDI),%XMM7	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x40(%RDI),%XMM8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x60(%RDI),%XMM9	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x90(%RDI),%XMM11	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x50(%RDI),%XMM28	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x80(%RDI),%XMM2	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0xb0(%RDI),%XMM3	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD 0x20(%RDI),%XMM6	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD -0x30(%R13,%RDX,1),%XMM12	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD -0x20(%R13,%RDX,1),%XMM13	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD -0x10(%R13,%RDX,1),%XMM14	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VMOVUPD (%R13,%RDX,1),%XMM15	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
ADD $0x40,%RDX	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	0	0	0	1	0.17	N/A
VBLENDPD $0x1,%XMM4,%XMM5,%XMM0	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VSHUFPD $0x1,%XMM6,%XMM4,%XMM4	1	0	0	0	0	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	1	0.25	vect (25.0%)
VBLENDPD $0x1,%XMM5,%XMM6,%XMM5	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VMOVAPD %XMM0,-0x60(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	0.50	vect (25.0%)
VBLENDPD $0x1,%XMM7,%XMM8,%XMM0	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VSHUFPD $0x1,%XMM28,%XMM7,%XMM7	1	0	0	0	0	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	1	0.25	vect (25.0%)
VFMADD231PD %XMM4,%XMM12,%XMM20	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM5,%XMM12,%XMM24	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VMOVAPD %XMM0,%XMM29	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.17	vect (25.0%)
VMOVUPD 0x70(%RDI),%XMM0	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VFMADD231PD -0x60(%RBP),%XMM12,%XMM16	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM29,%XMM13,%XMM17	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM7,%XMM13,%XMM21	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VBLENDPD $0x1,%XMM9,%XMM0,%XMM10	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VSHUFPD $0x1,%XMM2,%XMM9,%XMM9	1	0	0	0	0	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	1	0.25	vect (25.0%)
VBLENDPD $0x1,%XMM0,%XMM2,%XMM0	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VMOVAPD %XMM10,%XMM30	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.17	vect (25.0%)
VMOVUPD 0xa0(%RDI),%XMM10	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.50	vect (25.0%)
VFMADD231PD %XMM30,%XMM14,%XMM18	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM9,%XMM14,%XMM22	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM0,%XMM14,%XMM26	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
ADD $0xc0,%RDI	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	0	0	0	1	0.17	N/A
VBLENDPD $0x1,%XMM11,%XMM10,%XMM1	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VSHUFPD $0x1,%XMM3,%XMM11,%XMM11	1	0	0	0	0	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	1	0.25	vect (25.0%)
VBLENDPD $0x1,%XMM10,%XMM3,%XMM2	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VMOVAPD %XMM1,%XMM31	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.17	vect (25.0%)
VMOVAPD %XMM28,%XMM1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.17	vect (25.0%)
VBLENDPD $0x1,%XMM8,%XMM1,%XMM1	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	1	0.50	vect (25.0%)
VFMADD231PD %XMM31,%XMM15,%XMM19	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM11,%XMM15,%XMM23	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM2,%XMM15,%XMM27	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
VFMADD231PD %XMM1,%XMM13,%XMM25	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	4	0.50	vect (25.0%)
CMP %RDX,%R12	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	0	0	0	0	0	0	1	0.17	N/A
JNE 266a20 <_ZN16miniqmcreference19DiracDeterminantRefIN11qmcplusplus13DelayedUpdateIddEEE11evaluateLogERNS1_11ParticleSetERNS1_14ParticleAttribINS1_10TinyVectorIdLj3EEESaIS9_EEERNS7_IdSaIdEEE+0x210>	1	0	0	0	0.33	0.33	0.33	0	0	0	0	0	0	0	0	0	0	1	0.50-1	N/A

Report Configuration

Vectorization

Details

Workaround

Execution units bottlenecks

Workaround

FMA

Type of elements and instruction set

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

Arithmetic intensity

General properties

Front-end

Back-end

Cycles summary

Vectorization ratios

Vector efficiency ratios

Cycles and memory resources usage

Front-end bottlenecks

ASM code

Vectorization

Details

Workaround

Execution units bottlenecks

Workaround

FMA

Type of elements and instruction set

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

Arithmetic intensity

General properties

Front-end

Back-end

Cycles summary

Vectorization ratios

Vector efficiency ratios

Cycles and memory resources usage

Front-end bottlenecks

ASM code