OV - exec - Loop 69

	Loop Id: 69	Module: exec	Source: advec_cell_kernel.f90:165-170	Coverage: 3.49%

0x41a740 VMOVUPD	(%R11,%RDX,1),%ZMM14    [2]

0x41a747 VMULPD	(%R13,%RDX,1),%ZMM14,%ZMM1    [3]

0x41a74f VADDPD	(%RSI,%RDX,1),%ZMM14,%ZMM6    [7]

0x41a756 VMOVUPD	(%RDI,%RDX,1),%ZMM13    [9]

0x41a75d VSUBPD	(%R14,%RDX,1),%ZMM6,%ZMM4    [4]

0x41a764 VSUBPD	(%RCX,%RDX,1),%ZMM13,%ZMM0    [6]

0x41a76b VSUBPD	(%R12,%RDX,1),%ZMM1,%ZMM2    [5]

0x41a772 VFMADD132PD	(%R15,%RDX,1),%ZMM0,%ZMM1    [1]

0x41a779 VADDPD	(%R8,%RDX,1),%ZMM2,%ZMM3    [10]

0x41a780 VDIVPD	%ZMM4,%ZMM3,%ZMM9

0x41a786 VDIVPD	%ZMM3,%ZMM1,%ZMM14

0x41a78c VMOVUPD	%ZMM9,(%R13,%RDX,1)    [3]

0x41a794 VMOVUPD	%ZMM14,(%R15,%RDX,1)    [1]

0x41a79b VMOVUPD	0x40(%R11,%RDX,1),%ZMM3    [2]

0x41a7a3 VMULPD	0x40(%R13,%RDX,1),%ZMM3,%ZMM1    [3]

0x41a7ab VADDPD	0x40(%RSI,%RDX,1),%ZMM3,%ZMM4    [7]

0x41a7b3 VSUBPD	0x40(%R14,%RDX,1),%ZMM4,%ZMM9    [4]

0x41a7bb VMOVUPD	0x40(%RDI,%RDX,1),%ZMM13    [9]

0x41a7c3 VSUBPD	0x40(%RCX,%RDX,1),%ZMM13,%ZMM0    [6]

0x41a7cb VSUBPD	0x40(%R12,%RDX,1),%ZMM1,%ZMM2    [5]

0x41a7d3 VFMADD132PD	0x40(%R15,%RDX,1),%ZMM0,%ZMM1    [1]

0x41a7db VADDPD	0x40(%R8,%RDX,1),%ZMM2,%ZMM6    [10]

0x41a7e3 VDIVPD	%ZMM9,%ZMM6,%ZMM14

0x41a7e9 VDIVPD	%ZMM6,%ZMM1,%ZMM3

0x41a7ef VMOVUPD	%ZMM14,0x40(%R13,%RDX,1)    [3]

0x41a7f7 VMOVUPD	%ZMM3,0x40(%R15,%RDX,1)    [1]

0x41a7ff SUB	$-0x80,%RDX

0x41a803 CMP	%RDX,0xf0(%RSP)    [8]

0x41a80b JNE	41a740

/home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90: 165 - 170

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

165:           pre_mass_s=density1(j,k)*pre_vol(j,k)

166:           post_mass_s=pre_mass_s+mass_flux_x(j,k)-mass_flux_x(j+1,k)

167:           post_ener_s=(energy1(j,k)*pre_mass_s+ener_flux(j,k)-ener_flux(j+1,k))/post_mass_s

168:           advec_vol_s=pre_vol(j,k)+vol_flux_x(j,k)-vol_flux_x(j+1,k)

169:           density1(j,k)=post_mass_s/advec_vol_s

170:           energy1(j,k)=post_ener_s

Coverage (%)	Name	Source Location	Module
►95.75+	gomp_thread_start	team.c:130	libgomp.so.1.0.0
○	start_thread		libc.so.6
○	__GI___clone3		libc.so.6
►1.80+	GOMP_parallel	libgomp.h:982	libgomp.so.1.0.0
○	advec_cell_kernel	advec_cell_kernel.f90:270	exec
○	advec_cell_driver	advec_cell_driver.f90:57	exec
○	advection	advection.f90:57	exec
○	hydro	hydro.f90:64	exec
○	main	clover_leaf.f90:41	exec
○	__libc_start_call_main		libc.so.6
○	__libc_start_main		libc.so.6
○	_start	clover_leaf.f90:41	exec
►1.74+	GOMP_parallel	libgomp.h:982	libgomp.so.1.0.0
○	advec_cell_kernel	advec_cell_kernel.f90:270	exec
○	advec_cell_driver	advec_cell_driver.f90:57	exec
○	advection	advection.f90:88	exec
○	hydro	hydro.f90:64	exec
○	main	clover_leaf.f90:41	exec
○	__libc_start_call_main		libc.so.6
○	__libc_start_main		libc.so.6
○	_start	clover_leaf.f90:41	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	1.00
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	1.00
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	2.78
Bottlenecks	P10, P11,
Function	__advec_cell_kernel_module_MOD_advec_cell_kernel._omp_fn.0
Source	advec_cell_kernel.f90:165-170
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	16.00
CQA cycles if no scalar integer	16.00
CQA cycles if FP arith vectorized	16.00
CQA cycles if fully vectorized	16.00
Front-end cycles	3.50
P0 cycles	0.33
P1 cycles	0.33
P2 cycles	0.33
P3 cycles	0.33
P4 cycles	0.33
P5 cycles	0.33
P6 cycles	5.75
P7 cycles	5.75
P8 cycles	5.75
P9 cycles	5.75
P10 cycles	4.00
P11 cycles	4.00
P12 cycles	5.00
P13 cycles	5.00
P14 cycles	2.00
P15 cycles	2.00
DIV/SQRT cycles	16.00
Inter-iter dependencies cycles	1
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	29.00
Nb uops	28.00
Nb loads	19.00
Nb stores	4.00
Nb stack references	1.00
FLOP/cycle	10.00
Nb FLOP add-sub	80.00
Nb FLOP mul	16.00
Nb FLOP fma	16.00
Nb FLOP div	32.00
Nb FLOP rcp	0.00
Nb FLOP sqrt	0.00
Nb FLOP rsqrt	0.00
Bytes/cycle	88.50
Bytes prefetched	0.00
Bytes loaded	1160.00
Bytes stored	256.00
Stride 0	1.00
Stride 1	9.00
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	100.00
Vectorization ratio add_sub	100.00
Vectorization ratio fma	100.00
Vectorization ratio div_sqrt	100.00
Vectorization ratio other	NA
Vector-efficiency ratio all	100.00
Vector-efficiency ratio load	100.00
Vector-efficiency ratio store	100.00
Vector-efficiency ratio mul	100.00
Vector-efficiency ratio add_sub	100.00
Vector-efficiency ratio fma	100.00
Vector-efficiency ratio div_sqrt	100.00
Vector-efficiency ratio other	NA

Metric	Value
CQA speedup if no scalar integer	1.00
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	1.00
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	2.78
Bottlenecks	P10, P11,
Function	__advec_cell_kernel_module_MOD_advec_cell_kernel._omp_fn.0
Source	advec_cell_kernel.f90:165-170
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	16.00
CQA cycles if no scalar integer	16.00
CQA cycles if FP arith vectorized	16.00
CQA cycles if fully vectorized	16.00
Front-end cycles	3.50
P0 cycles	0.33
P1 cycles	0.33
P2 cycles	0.33
P3 cycles	0.33
P4 cycles	0.33
P5 cycles	0.33
P6 cycles	5.75
P7 cycles	5.75
P8 cycles	5.75
P9 cycles	5.75
P10 cycles	4.00
P11 cycles	4.00
P12 cycles	5.00
P13 cycles	5.00
P14 cycles	2.00
P15 cycles	2.00
DIV/SQRT cycles	16.00
Inter-iter dependencies cycles	1
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	29.00
Nb uops	28.00
Nb loads	19.00
Nb stores	4.00
Nb stack references	1.00
FLOP/cycle	10.00
Nb FLOP add-sub	80.00
Nb FLOP mul	16.00
Nb FLOP fma	16.00
Nb FLOP div	32.00
Nb FLOP rcp	0.00
Nb FLOP sqrt	0.00
Nb FLOP rsqrt	0.00
Bytes/cycle	88.50
Bytes prefetched	0.00
Bytes loaded	1160.00
Bytes stored	256.00
Stride 0	1.00
Stride 1	9.00
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	100.00
Vectorization ratio add_sub	100.00
Vectorization ratio fma	100.00
Vectorization ratio div_sqrt	100.00
Vectorization ratio other	NA
Vector-efficiency ratio all	100.00
Vector-efficiency ratio load	100.00
Vector-efficiency ratio store	100.00
Vector-efficiency ratio mul	100.00
Vector-efficiency ratio add_sub	100.00
Vector-efficiency ratio fma	100.00
Vector-efficiency ratio div_sqrt	100.00
Vector-efficiency ratio other	NA

Path /

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

Function	__advec_cell_kernel_module_MOD_advec_cell_kernel._omp_fn.0
Source file and lines	advec_cell_kernel.f90:165-170
Module	exec

The loop is defined in /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:165-170.

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

gain
potential
hint
expert

Vectorization

Your loop is fully vectorized, using full register length.

Details

All SSE/AVX instructions are used in vector version (process two or more data elements in vector registers).

Execution units bottlenecks

Performance is limited by execution of divide and square root operations (the divide/square root unit is a bottleneck). By removing all these bottlenecks, you can lower the cost of an iteration from 16.00 to 5.75 cycles (2.78x speedup).

Workaround

Reduce the number of division or square root instructions:
- If denominator is constant over iterations, use reciprocal (replace x/y with x*(1/y)). Check precision impact. This will be done by your compiler with ffast-math or Ofast
Check whether you really need double precision. If not, switch to single precision to speedup execution

Expensive FP math instructions/calls

Detected performance impact from expensive FP math instructions/calls. By removing/reexpressing them, you can lower the cost of an iteration from 16.00 to 7.00 cycles (2.29x speedup).

FMA

Detected 16 FMA (fused multiply-add) operations. Presence of both ADD/SUB and MUL operations.

Workaround

Try to change order in which elements are evaluated (using parentheses) in arithmetic expressions containing both ADD/SUB and MUL operations to enable your compiler to generate FMA instructions wherever possible. For instance a + b*c is a valid FMA (MUL then ADD). However (a+b)* c cannot be translated into an FMA (ADD then MUL).

Vector unaligned load/store instructions

Detected 8 optimal vector unaligned load/store instructions.

Details

VMOVUPD: 8 occurrences►
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:165
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:167
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:169
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:170
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:165
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:167
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:169
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:170

Workaround

Use vector aligned instructions:

The GNU Fortran compiler does not support allocation alignment and does not feature directives to benefit from aligned data.
Use another compiler or locally use C code (for instance via libraries)

Type of elements and instruction set

18 AVX-512 instructions are processing arithmetic or math operations on double precision FP elements in vector mode (eight at a time).

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

The binary loop is composed of 160 FP arithmetical operations:

96: addition or subtraction (16 inside FMA instructions)
32: multiply (16 inside FMA instructions)
32: divide

The binary loop is loading 1160 bytes (145 double precision FP elements). The binary loop is storing 256 bytes (32 double precision FP elements).

Arithmetic intensity

Arithmetic intensity is 0.11 FP operations per loaded or stored byte.

General properties

nb instructions	29
nb uops	28
loop length	209
used x86 registers	11
used mmx registers	0
used xmm registers	0
used ymm registers	0
used zmm registers	9
nb stack references	1
ADD-SUB / MUL ratio	5.00

Front-end

ASSUMED MACRO FUSION FIT IN UOP CACHE

micro-operation queue	3.50 cycles
front end	3.50 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15
uops	0.33	0.33	0.33	0.33	0.33	0.33	5.75	5.75	5.75	5.75	4.00	4.00	5.00	5.00	2.00	2.00
cycles	0.33	0.33	0.33	0.33	0.33	0.33	5.75	5.75	5.75	5.75	4.00	4.00	5.00	5.00	2.00	2.00

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	16.00
Longest recurrence chain latency (RecMII)	1.00

Cycles summary

Front-end	3.50
Dispatch	5.75
DIV/SQRT	16.00
Data deps.	1.00
Overall L1	16.00

Vectorization ratios

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

Vector efficiency ratios

all	100%
load	100%
store	100%
mul	100%
add-sub	100%
fma	100%
div/sqrt	100%
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 16.00 cycles. At this rate:

28% of peak load performance is reached (72.50 out of 256.00 bytes loaded per cycle (GB/s @ 1GHz))
12% of peak store performance is reached (16.00 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: 41a740

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15	Latency	Recip. throughput	Vectorization
VMOVUPD (%R11,%RDX,1),%ZMM14	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 (100.0%)
VMULPD (%R13,%RDX,1),%ZMM14,%ZMM1	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0.50	0.50	0	0	0	0	3	0.50	vect (100.0%)
VADDPD (%RSI,%RDX,1),%ZMM14,%ZMM6	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VMOVUPD (%RDI,%RDX,1),%ZMM13	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 (100.0%)
VSUBPD (%R14,%RDX,1),%ZMM6,%ZMM4	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VSUBPD (%RCX,%RDX,1),%ZMM13,%ZMM0	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VSUBPD (%R12,%RDX,1),%ZMM1,%ZMM2	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VFMADD132PD (%R15,%RDX,1),%ZMM0,%ZMM1	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 (100.0%)
VADDPD (%R8,%RDX,1),%ZMM2,%ZMM3	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VDIVPD %ZMM4,%ZMM3,%ZMM9	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	13	4	vect (100.0%)
VDIVPD %ZMM3,%ZMM1,%ZMM14	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	13	4	vect (100.0%)
VMOVUPD %ZMM9,(%R13,%RDX,1)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	1	vect (100.0%)
VMOVUPD %ZMM14,(%R15,%RDX,1)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	1	vect (100.0%)
VMOVUPD 0x40(%R11,%RDX,1),%ZMM3	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 (100.0%)
VMULPD 0x40(%R13,%RDX,1),%ZMM3,%ZMM1	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0.50	0.50	0	0	0	0	3	0.50	vect (100.0%)
VADDPD 0x40(%RSI,%RDX,1),%ZMM3,%ZMM4	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VSUBPD 0x40(%R14,%RDX,1),%ZMM4,%ZMM9	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VMOVUPD 0x40(%RDI,%RDX,1),%ZMM13	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 (100.0%)
VSUBPD 0x40(%RCX,%RDX,1),%ZMM13,%ZMM0	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VSUBPD 0x40(%R12,%RDX,1),%ZMM1,%ZMM2	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VFMADD132PD 0x40(%R15,%RDX,1),%ZMM0,%ZMM1	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 (100.0%)
VADDPD 0x40(%R8,%RDX,1),%ZMM2,%ZMM6	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VDIVPD %ZMM9,%ZMM6,%ZMM14	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	13	4	vect (100.0%)
VDIVPD %ZMM6,%ZMM1,%ZMM3	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	13	4	vect (100.0%)
VMOVUPD %ZMM14,0x40(%R13,%RDX,1)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	1	vect (100.0%)
VMOVUPD %ZMM3,0x40(%R15,%RDX,1)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	1	vect (100.0%)
SUB $-0x80,%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
CMP %RDX,0xf0(%RSP)	1	0.17	0.17	0.17	0.17	0.17	0.17	0.25	0.25	0.25	0.25	0	0	0	0	0	0	1	0.25	N/A
JNE 41a740 <__advec_cell_kernel_module_MOD_advec_cell_kernel._omp_fn.0+0x17f0>	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	__advec_cell_kernel_module_MOD_advec_cell_kernel._omp_fn.0
Source file and lines	advec_cell_kernel.f90:165-170
Module	exec

gain
potential
hint
expert

Vectorization

Your loop is fully vectorized, using full register length.

Details

All SSE/AVX instructions are used in vector version (process two or more data elements in vector registers).

Execution units bottlenecks

Workaround

Reduce the number of division or square root instructions:
- If denominator is constant over iterations, use reciprocal (replace x/y with x*(1/y)). Check precision impact. This will be done by your compiler with ffast-math or Ofast
Check whether you really need double precision. If not, switch to single precision to speedup execution

Expensive FP math instructions/calls

Detected performance impact from expensive FP math instructions/calls. By removing/reexpressing them, you can lower the cost of an iteration from 16.00 to 7.00 cycles (2.29x speedup).

FMA

Detected 16 FMA (fused multiply-add) operations. Presence of both ADD/SUB and MUL operations.

Workaround

Vector unaligned load/store instructions

Detected 8 optimal vector unaligned load/store instructions.

Details

VMOVUPD: 8 occurrences►
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:165
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:167
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:169
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:170
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:165
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:167
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:169
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/advec_cell_kernel.f90:170

Workaround

Use vector aligned instructions:

The GNU Fortran compiler does not support allocation alignment and does not feature directives to benefit from aligned data.
Use another compiler or locally use C code (for instance via libraries)

Type of elements and instruction set

18 AVX-512 instructions are processing arithmetic or math operations on double precision FP elements in vector mode (eight at a time).

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

The binary loop is composed of 160 FP arithmetical operations:

96: addition or subtraction (16 inside FMA instructions)
32: multiply (16 inside FMA instructions)
32: divide

The binary loop is loading 1160 bytes (145 double precision FP elements). The binary loop is storing 256 bytes (32 double precision FP elements).

Arithmetic intensity

Arithmetic intensity is 0.11 FP operations per loaded or stored byte.

General properties

nb instructions	29
nb uops	28
loop length	209
used x86 registers	11
used mmx registers	0
used xmm registers	0
used ymm registers	0
used zmm registers	9
nb stack references	1
ADD-SUB / MUL ratio	5.00

Front-end

ASSUMED MACRO FUSION FIT IN UOP CACHE

micro-operation queue	3.50 cycles
front end	3.50 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15
uops	0.33	0.33	0.33	0.33	0.33	0.33	5.75	5.75	5.75	5.75	4.00	4.00	5.00	5.00	2.00	2.00
cycles	0.33	0.33	0.33	0.33	0.33	0.33	5.75	5.75	5.75	5.75	4.00	4.00	5.00	5.00	2.00	2.00

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	16.00
Longest recurrence chain latency (RecMII)	1.00

Cycles summary

Front-end	3.50
Dispatch	5.75
DIV/SQRT	16.00
Data deps.	1.00
Overall L1	16.00

Vectorization ratios

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

Vector efficiency ratios

all	100%
load	100%
store	100%
mul	100%
add-sub	100%
fma	100%
div/sqrt	100%
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 16.00 cycles. At this rate:

28% of peak load performance is reached (72.50 out of 256.00 bytes loaded per cycle (GB/s @ 1GHz))
12% of peak store performance is reached (16.00 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: 41a740

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15	Latency	Recip. throughput	Vectorization
VMOVUPD (%R11,%RDX,1),%ZMM14	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 (100.0%)
VMULPD (%R13,%RDX,1),%ZMM14,%ZMM1	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0.50	0.50	0	0	0	0	3	0.50	vect (100.0%)
VADDPD (%RSI,%RDX,1),%ZMM14,%ZMM6	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VMOVUPD (%RDI,%RDX,1),%ZMM13	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 (100.0%)
VSUBPD (%R14,%RDX,1),%ZMM6,%ZMM4	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VSUBPD (%RCX,%RDX,1),%ZMM13,%ZMM0	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VSUBPD (%R12,%RDX,1),%ZMM1,%ZMM2	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VFMADD132PD (%R15,%RDX,1),%ZMM0,%ZMM1	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 (100.0%)
VADDPD (%R8,%RDX,1),%ZMM2,%ZMM3	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VDIVPD %ZMM4,%ZMM3,%ZMM9	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	13	4	vect (100.0%)
VDIVPD %ZMM3,%ZMM1,%ZMM14	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	13	4	vect (100.0%)
VMOVUPD %ZMM9,(%R13,%RDX,1)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	1	vect (100.0%)
VMOVUPD %ZMM14,(%R15,%RDX,1)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	1	vect (100.0%)
VMOVUPD 0x40(%R11,%RDX,1),%ZMM3	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 (100.0%)
VMULPD 0x40(%R13,%RDX,1),%ZMM3,%ZMM1	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0.50	0.50	0	0	0	0	3	0.50	vect (100.0%)
VADDPD 0x40(%RSI,%RDX,1),%ZMM3,%ZMM4	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VSUBPD 0x40(%R14,%RDX,1),%ZMM4,%ZMM9	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VMOVUPD 0x40(%RDI,%RDX,1),%ZMM13	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 (100.0%)
VSUBPD 0x40(%RCX,%RDX,1),%ZMM13,%ZMM0	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VSUBPD 0x40(%R12,%RDX,1),%ZMM1,%ZMM2	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VFMADD132PD 0x40(%R15,%RDX,1),%ZMM0,%ZMM1	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 (100.0%)
VADDPD 0x40(%R8,%RDX,1),%ZMM2,%ZMM6	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VDIVPD %ZMM9,%ZMM6,%ZMM14	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	13	4	vect (100.0%)
VDIVPD %ZMM6,%ZMM1,%ZMM3	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	13	4	vect (100.0%)
VMOVUPD %ZMM14,0x40(%R13,%RDX,1)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	1	vect (100.0%)
VMOVUPD %ZMM3,0x40(%R15,%RDX,1)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0.50	0.50	4	1	vect (100.0%)
SUB $-0x80,%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
CMP %RDX,0xf0(%RSP)	1	0.17	0.17	0.17	0.17	0.17	0.17	0.25	0.25	0.25	0.25	0	0	0	0	0	0	1	0.25	N/A
JNE 41a740 <__advec_cell_kernel_module_MOD_advec_cell_kernel._omp_fn.0+0x17f0>	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

Execution units bottlenecks

Workaround

Expensive FP math instructions/calls

FMA

Workaround

Vector unaligned load/store instructions

Details

Workaround

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

Execution units bottlenecks

Workaround

Expensive FP math instructions/calls

FMA

Workaround

Vector unaligned load/store instructions

Details

Workaround

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