OV - exec - Loop 233

	Loop Id: 233	Module: exec	Source: flux_calc_kernel.f90:57-61	Coverage: 4.26%

0x233f10 MOV	0x68(%RSP),%R8    [10]

0x233f15 VMOVUPD	(%R14,%RCX,8),%ZMM2    [4]

0x233f1c VMOVUPD	(%RBX,%RCX,8),%ZMM3    [5]

0x233f23 VADDPD	(%R8,%RCX,8),%ZMM2,%ZMM2    [2]

0x233f2a MOV	0x70(%RSP),%R8    [10]

0x233f2f VADDPD	(%R8,%RCX,8),%ZMM3,%ZMM3    [1]

0x233f36 MOV	0x78(%RSP),%R8    [10]

0x233f3b VMULPD	(%R8,%RCX,8),%ZMM1,%ZMM5    [9]

0x233f42 MOV	0x18(%RSP),%R8    [10]

0x233f47 VADDPD	%ZMM3,%ZMM2,%ZMM2

0x233f4d VMULPD	%ZMM5,%ZMM2,%ZMM2

0x233f53 VMOVUPD	%ZMM2,(%R8,%RCX,8)    [8]

0x233f5a VMOVUPD	(%R13,%RCX,8),%ZMM2    [6]

0x233f62 VMOVUPD	(%R15,%RCX,8),%ZMM3    [7]

0x233f69 VMULPD	(%RAX,%RCX,8),%ZMM1,%ZMM4    [3]

0x233f70 VADDPD	-0x8(%R13,%RCX,8),%ZMM2,%ZMM2    [6]

0x233f7b VADDPD	-0x8(%R15,%RCX,8),%ZMM3,%ZMM3    [7]

0x233f86 VADDPD	%ZMM3,%ZMM2,%ZMM2

0x233f8c VMULPD	%ZMM4,%ZMM2,%ZMM2

0x233f92 VMOVUPD	%ZMM2,(%RDX,%RCX,8)    [11]

0x233f99 ADD	$0x8,%RCX

0x233f9d CMP	%RCX,%RDI

0x233fa0 JNE	233f10

/home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90: 57 - 61

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

57:         vol_flux_x(j,k)=0.25_8*dt*xarea(j,k)                  &

58:           *(xvel0(j,k)+xvel0(j,k+1)+xvel1(j,k)+xvel1(j,k+1))

59:         vol_flux_y(j,k)=0.25_8*dt*yarea(j,k)                  &

60:           *(yvel0(j,k)+yvel0(j+1,k)+yvel1(j,k)+yvel1(j+1,k))

61:       ENDDO

Coverage (%)	Name	Source Location	Module

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	1.00
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.33
Bottlenecks	P6, P7, P8, P9,
Function	__nv_flux_calc_kernel_module_flux_calc_kernel__PARALLEL_F2L49_1
Source	flux_calc_kernel.f90:57-61
Source loop unroll info	unrolled by 8
Source loop unroll confidence level	max
Unroll/vectorization loop type	main
Unroll factor	8
CQA cycles	4.00
CQA cycles if no scalar integer	3.00
CQA cycles if FP arith vectorized	4.00
CQA cycles if fully vectorized	4.00
Front-end cycles	2.75
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	4.00
P7 cycles	4.00
P8 cycles	4.00
P9 cycles	4.00
P10 cycles	2.00
P11 cycles	2.00
P12 cycles	3.00
P13 cycles	3.00
P14 cycles	1.00
P15 cycles	1.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	1
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	23.00
Nb uops	22.00
Nb loads	14.00
Nb stores	2.00
Nb stack references	4.00
FLOP/cycle	20.00
Nb FLOP add-sub	48.00
Nb FLOP mul	32.00
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	200.00
Bytes prefetched	0.00
Bytes loaded	672.00
Bytes stored	128.00
Stride 0	1.00
Stride 1	8.00
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	NA
Vectorization ratio div_sqrt	NA
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	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	1.00
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.33
Bottlenecks	P6, P7, P8, P9,
Function	__nv_flux_calc_kernel_module_flux_calc_kernel__PARALLEL_F2L49_1
Source	flux_calc_kernel.f90:57-61
Source loop unroll info	unrolled by 8
Source loop unroll confidence level	max
Unroll/vectorization loop type	main
Unroll factor	8
CQA cycles	4.00
CQA cycles if no scalar integer	3.00
CQA cycles if FP arith vectorized	4.00
CQA cycles if fully vectorized	4.00
Front-end cycles	2.75
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	4.00
P7 cycles	4.00
P8 cycles	4.00
P9 cycles	4.00
P10 cycles	2.00
P11 cycles	2.00
P12 cycles	3.00
P13 cycles	3.00
P14 cycles	1.00
P15 cycles	1.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	1
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	23.00
Nb uops	22.00
Nb loads	14.00
Nb stores	2.00
Nb stack references	4.00
FLOP/cycle	20.00
Nb FLOP add-sub	48.00
Nb FLOP mul	32.00
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	200.00
Bytes prefetched	0.00
Bytes loaded	672.00
Bytes stored	128.00
Stride 0	1.00
Stride 1	8.00
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	NA
Vectorization ratio div_sqrt	NA
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	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	__nv_flux_calc_kernel_module_flux_calc_kernel__PARALLEL_F2L49_1
Source file and lines	flux_calc_kernel.f90:57-61
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/flux_calc_kernel.f90:57-61.

It is main loop of related source loop which is unrolled by 8 (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 4.00 to 3.00 cycles (1.33x speedup).

Workaround

Try to reorganize arrays of structures to structures of arrays
Consider to permute loops (see vectorization gain report)
To reference allocatable arrays, use "allocatable" instead of "pointer" pointers or qualify them with the "contiguous" attribute (Fortran 2008)
For structures, limit to one indirection. For example, use a_b%c instead of a%b%c with a_b set to a%b before this loop

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:

reading data from caches/RAM (load units are a bottleneck)
writing data to caches/RAM (the store unit is a bottleneck)

By removing all these bottlenecks, you can lower the cost of an iteration from 4.00 to 3.00 cycles (1.33x speedup).

Workaround

Read less array elements
Write less array elements
Provide more information to your compiler:
- hardcode the bounds of the corresponding 'for' loop

FMA

Presence of both ADD/SUB and MUL operations.

Workaround

Pass to your compiler a micro-architecture specialization option:
- Please look into your compiler manual for march=native or equivalent
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 6 optimal vector unaligned load/store instructions.

Details

VMOVUPD: 6 occurrences►
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:57
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:57
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:57
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:59
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:59
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:59

Workaround

Use vector aligned instructions:

align your arrays on 64 bytes boundaries
inform your compiler that your arrays are vector aligned: read your compiler manual.

Type of elements and instruction set

10 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 80 FP arithmetical operations:

48: addition or subtraction
32: multiply

The binary loop is loading 672 bytes (84 double precision FP elements). The binary loop is storing 128 bytes (16 double precision FP elements).

Arithmetic intensity

Arithmetic intensity is 0.10 FP operations per loaded or stored byte.

General properties

nb instructions	23
nb uops	22
loop length	150
used x86 registers	10
used mmx registers	0
used xmm registers	0
used ymm registers	0
used zmm registers	5
nb stack references	4
ADD-SUB / MUL ratio	1.50

Front-end

ASSUMED MACRO FUSION FIT IN UOP CACHE

micro-operation queue	2.75 cycles
front end	2.75 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	4.00	4.00	4.00	4.00	2.00	2.00	3.00	3.00	1.00	1.00
cycles	0.33	0.33	0.33	0.33	0.33	0.33	4.00	4.00	4.00	4.00	2.00	2.00	3.00	3.00	1.00	1.00

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	NA
Longest recurrence chain latency (RecMII)	1.00

Cycles summary

Front-end	2.75
Dispatch	4.00
Data deps.	1.00
Overall L1	4.00

Vectorization ratios

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

Vector efficiency ratios

all	100%
load	100%
store	100%
mul	100%
add-sub	100%
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 4.00 cycles. At this rate:

65% of peak load performance is reached (168.00 out of 256.00 bytes loaded per cycle (GB/s @ 1GHz))
25% of peak store performance is reached (32.00 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: 233f10

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15	Latency	Recip. throughput	Vectorization
MOV 0x68(%RSP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.25	N/A
VMOVUPD (%R14,%RCX,8),%ZMM2	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%)
VMOVUPD (%RBX,%RCX,8),%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%)
VADDPD (%R8,%RCX,8),%ZMM2,%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%)
MOV 0x70(%RSP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.25	N/A
VADDPD (%R8,%RCX,8),%ZMM3,%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%)
MOV 0x78(%RSP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.25	N/A
VMULPD (%R8,%RCX,8),%ZMM1,%ZMM5	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%)
MOV 0x18(%RSP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.25	N/A
VADDPD %ZMM3,%ZMM2,%ZMM2	1	0	0	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VMULPD %ZMM5,%ZMM2,%ZMM2	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	3	0.50	vect (100.0%)
VMOVUPD %ZMM2,(%R8,%RCX,8)	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 (%R13,%RCX,8),%ZMM2	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%)
VMOVUPD (%R15,%RCX,8),%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 (%RAX,%RCX,8),%ZMM1,%ZMM4	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 -0x8(%R13,%RCX,8),%ZMM2,%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%)
VADDPD -0x8(%R15,%RCX,8),%ZMM3,%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%)
VADDPD %ZMM3,%ZMM2,%ZMM2	1	0	0	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VMULPD %ZMM4,%ZMM2,%ZMM2	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	3	0.50	vect (100.0%)
VMOVUPD %ZMM2,(%RDX,%RCX,8)	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%)
ADD $0x8,%RCX	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 %RCX,%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
JNE 233f10 <__nv_flux_calc_kernel_module_flux_calc_kernel__PARALLEL_F2L49_1_+0x470>	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	__nv_flux_calc_kernel_module_flux_calc_kernel__PARALLEL_F2L49_1
Source file and lines	flux_calc_kernel.f90:57-61
Module	exec

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 4.00 to 3.00 cycles (1.33x speedup).

Workaround

Try to reorganize arrays of structures to structures of arrays
Consider to permute loops (see vectorization gain report)
To reference allocatable arrays, use "allocatable" instead of "pointer" pointers or qualify them with the "contiguous" attribute (Fortran 2008)
For structures, limit to one indirection. For example, use a_b%c instead of a%b%c with a_b set to a%b before this loop

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:

reading data from caches/RAM (load units are a bottleneck)
writing data to caches/RAM (the store unit is a bottleneck)

By removing all these bottlenecks, you can lower the cost of an iteration from 4.00 to 3.00 cycles (1.33x speedup).

Workaround

Read less array elements
Write less array elements
Provide more information to your compiler:
- hardcode the bounds of the corresponding 'for' loop

FMA

Presence of both ADD/SUB and MUL operations.

Workaround

Pass to your compiler a micro-architecture specialization option:
- Please look into your compiler manual for march=native or equivalent
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 6 optimal vector unaligned load/store instructions.

Details

VMOVUPD: 6 occurrences►
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:57
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:57
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:57
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:59
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:59
- /home/eoseret/qaas_runs_ZEN5/174-049-0948/intel/CloverLeaf1.3-FC/build/CloverLeaf1.3-FC/CloverLeaf_ref/kernels/flux_calc_kernel.f90:59

Workaround

Use vector aligned instructions:

align your arrays on 64 bytes boundaries
inform your compiler that your arrays are vector aligned: read your compiler manual.

Type of elements and instruction set

10 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 80 FP arithmetical operations:

48: addition or subtraction
32: multiply

The binary loop is loading 672 bytes (84 double precision FP elements). The binary loop is storing 128 bytes (16 double precision FP elements).

Arithmetic intensity

Arithmetic intensity is 0.10 FP operations per loaded or stored byte.

General properties

nb instructions	23
nb uops	22
loop length	150
used x86 registers	10
used mmx registers	0
used xmm registers	0
used ymm registers	0
used zmm registers	5
nb stack references	4
ADD-SUB / MUL ratio	1.50

Front-end

ASSUMED MACRO FUSION FIT IN UOP CACHE

micro-operation queue	2.75 cycles
front end	2.75 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	4.00	4.00	4.00	4.00	2.00	2.00	3.00	3.00	1.00	1.00
cycles	0.33	0.33	0.33	0.33	0.33	0.33	4.00	4.00	4.00	4.00	2.00	2.00	3.00	3.00	1.00	1.00

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	NA
Longest recurrence chain latency (RecMII)	1.00

Cycles summary

Front-end	2.75
Dispatch	4.00
Data deps.	1.00
Overall L1	4.00

Vectorization ratios

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

Vector efficiency ratios

all	100%
load	100%
store	100%
mul	100%
add-sub	100%
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 4.00 cycles. At this rate:

65% of peak load performance is reached (168.00 out of 256.00 bytes loaded per cycle (GB/s @ 1GHz))
25% of peak store performance is reached (32.00 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: 233f10

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15	Latency	Recip. throughput	Vectorization
MOV 0x68(%RSP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.25	N/A
VMOVUPD (%R14,%RCX,8),%ZMM2	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%)
VMOVUPD (%RBX,%RCX,8),%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%)
VADDPD (%R8,%RCX,8),%ZMM2,%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%)
MOV 0x70(%RSP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.25	N/A
VADDPD (%R8,%RCX,8),%ZMM3,%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%)
MOV 0x78(%RSP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.25	N/A
VMULPD (%R8,%RCX,8),%ZMM1,%ZMM5	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%)
MOV 0x18(%RSP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	0	0	0	0	0	0	3	0.25	N/A
VADDPD %ZMM3,%ZMM2,%ZMM2	1	0	0	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VMULPD %ZMM5,%ZMM2,%ZMM2	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	3	0.50	vect (100.0%)
VMOVUPD %ZMM2,(%R8,%RCX,8)	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 (%R13,%RCX,8),%ZMM2	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%)
VMOVUPD (%R15,%RCX,8),%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 (%RAX,%RCX,8),%ZMM1,%ZMM4	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 -0x8(%R13,%RCX,8),%ZMM2,%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%)
VADDPD -0x8(%R15,%RCX,8),%ZMM3,%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%)
VADDPD %ZMM3,%ZMM2,%ZMM2	1	0	0	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	2	0.50	vect (100.0%)
VMULPD %ZMM4,%ZMM2,%ZMM2	1	0	0	0	0	0	0	0	0	0	0	0.50	0.50	0	0	0	0	3	0.50	vect (100.0%)
VMOVUPD %ZMM2,(%RDX,%RCX,8)	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%)
ADD $0x8,%RCX	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 %RCX,%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
JNE 233f10 <__nv_flux_calc_kernel_module_flux_calc_kernel__PARALLEL_F2L49_1_+0x470>	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

Code clean check

Workaround

Vectorization

Details

Execution units bottlenecks

Workaround

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

Code clean check

Workaround

Vectorization

Details

Execution units bottlenecks

Workaround

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