OV - exec - Loop 1308

	Loop Id: 1308	Module: exec	Source: For.hpp:137-137 [...]	Coverage: 0.02%

0x27aef0 MOV	-0x30(%RBP),%RDX

0x27aef4 INC	%RDX

0x27aef7 ADD	-0x68(%RBP),%R14

0x27aefb MOV	-0x70(%RBP),%RAX

0x27aeff MOV	-0x60(%RBP),%RSI

0x27af03 ADD	%RAX,%RSI

0x27af06 MOV	-0x58(%RBP),%R9

0x27af0a ADD	%RAX,%R9

0x27af0d MOV	-0x50(%RBP),%RCX

0x27af11 ADD	%RAX,%RCX

0x27af14 MOV	%RDX,%RAX

0x27af17 MOV	%RDX,-0x30(%RBP)

0x27af1b CMP	-0x1c0(%RBP),%RDX

0x27af22 MOV	%R9,%RAX

0x27af25 MOV	%RSI,%RDX

0x27af28 JE	27abc0

0x27af2e MOV	%RCX,-0x50(%RBP)

0x27af32 MOV	%RAX,-0x58(%RBP)

0x27af36 MOV	%RDX,-0x60(%RBP)

0x27af3a CMPQ	$0,-0x48(%RBP)

0x27af3f MOV	-0x1b8(%RBP),%RDX

0x27af46 MOV	-0x1b0(%RBP),%R9

0x27af4d MOV	-0x1a8(%RBP),%R12

0x27af54 MOV	-0x1a0(%RBP),%R13

0x27af5b MOV	-0x198(%RBP),%RSI

0x27af62 MOV	-0x190(%RBP),%R8

0x27af69 MOV	-0x40(%RBP),%RCX

0x27af6d JLE	27aef0

0x27af6f MOV	-0x30(%RBP),%R10

0x27af73 IMUL	-0xc0(%RBP),%R10

0x27af7b ADD	-0xc8(%RBP),%R10

0x27af82 MOV	-0x188(%RBP),%RAX

0x27af89 MOV	%R10,-0xd8(%RBP)

0x27af90 ADD	%R10,%RAX

0x27af93 MOV	%RAX,-0xd0(%RBP)

0x27af9a XOR	%R15D,%R15D

0x27af9d XOR	%EBX,%EBX

0x27af9f MOV	-0xb8(%RBP),%R11

0x27afa6 NOPW	%CS:(%RAX,%RAX,1)

  (1309) 0x27afb0 MOV	-0x1d8(%RBP),%RAX

  (1309) 0x27afb7 MOVSD	(%R9,%RAX,8),%XMM1

  (1309) 0x27afbd ADDSD	%XMM1,%XMM1

  (1309) 0x27afc1 MOV	-0xd8(%RBP),%R10

  (1309) 0x27afc8 DIVSD	(%R12,%R10,8),%XMM1

  (1309) 0x27afce MOVSD	(%RDX,%RAX,8),%XMM0

  (1309) 0x27afd3 MOVHPD	(%R13,%RAX,8),%XMM0

  (1309) 0x27afda MOVSD	(%RCX,%RBX,1),%XMM2

  (1309) 0x27afdf MOV	-0x78(%RBP),%RAX

  (1309) 0x27afe3 MOVHPD	(%RSI,%RAX,8),%XMM2

  (1309) 0x27afe8 ADDPD	%XMM0,%XMM0

  (1309) 0x27afec DIVPD	%XMM2,%XMM0

  (1309) 0x27aff0 MOV	-0xd0(%RBP),%RDI

  (1309) 0x27aff7 MOVSD	(%R8,%RDI,8),%XMM2

  (1309) 0x27affd MULSD	%XMM0,%XMM2

  (1309) 0x27b001 MOV	-0x50(%RBP),%RAX

  (1309) 0x27b005 ADDSD	(%RAX,%R15,1),%XMM2

  (1309) 0x27b00b MOV	-0x38(%RBP),%RCX

  (1309) 0x27b00f MOVSD	(%RCX,%RBX,1),%XMM3

  (1309) 0x27b014 MULSD	%XMM1,%XMM3

  (1309) 0x27b018 ADDSD	%XMM2,%XMM3

  (1309) 0x27b01c MOVAPD	%XMM0,%XMM2

  (1309) 0x27b020 UNPCKHPD	%XMM0,%XMM2

  (1309) 0x27b024 MOVSD	(%R14,%RBX,1),%XMM4

  (1309) 0x27b02a MULSD	%XMM2,%XMM4

  (1309) 0x27b02e ADDSD	%XMM3,%XMM4

  (1309) 0x27b032 ADDSD	%XMM1,%XMM0

  (1309) 0x27b036 ADDSD	%XMM2,%XMM0

  (1309) 0x27b03a MOV	%RSI,%RAX

  (1309) 0x27b03d MOV	%R14,%RSI

  (1309) 0x27b040 MOV	%RCX,%R14

  (1309) 0x27b043 MOV	%R8,%RCX

  (1309) 0x27b046 MOV	%R13,%R8

  (1309) 0x27b049 MOV	%R12,%R13

  (1309) 0x27b04c MOV	%R9,%R12

  (1309) 0x27b04f MOV	%RDX,%R9

  (1309) 0x27b052 MOV	-0x58(%RBP),%RDX

  (1309) 0x27b056 ADDSD	(%RDX,%R15,1),%XMM0

  (1309) 0x27b05c DIVSD	%XMM0,%XMM4

  (1309) 0x27b060 MOV	-0x60(%RBP),%RDX

  (1309) 0x27b064 MOVSD	%XMM4,(%RDX,%R15,1)

  (1309) 0x27b06a MOV	-0x1c8(%RBP),%R10

  (1309) 0x27b071 MOV	%R9,%RDX

  (1309) 0x27b074 MOV	%R12,%R9

  (1309) 0x27b077 MOV	%R13,%R12

  (1309) 0x27b07a MOV	%R8,%R13

  (1309) 0x27b07d MOV	%RCX,%R8

  (1309) 0x27b080 MOV	%R14,%RCX

  (1309) 0x27b083 MOV	%RSI,%R14

  (1309) 0x27b086 MOV	%RAX,%RSI

  (1309) 0x27b089 ADDSD	%XMM4,%XMM4

  (1309) 0x27b08d MOVAPD	%XMM4,%XMM0

  (1309) 0x27b091 SUBSD	(%R8,%RDI,8),%XMM0

  (1309) 0x27b097 MOVSD	%XMM0,(%R8,%RDI,8)

  (1309) 0x27b09d MOVAPD	%XMM4,%XMM0

  (1309) 0x27b0a1 SUBSD	(%RCX,%RBX,1),%XMM0

  (1309) 0x27b0a6 MOVSD	%XMM0,(%RCX,%RBX,1)

  (1309) 0x27b0ab MOV	-0x40(%RBP),%RCX

  (1309) 0x27b0af SUBSD	(%R14,%RBX,1),%XMM4

  (1309) 0x27b0b5 MOVSD	%XMM4,(%R14,%RBX,1)

  (1309) 0x27b0bb ADD	-0x1d0(%RBP),%RBX

  (1309) 0x27b0c2 ADD	%R10,%R15

  (1309) 0x27b0c5 DEC	%R11

  (1309) 0x27b0c8 JNE	27afb0

0x27b0ce JMP	27aef0

/home/eoseret/qaas_runs_ZEN5/173-940-2141/intel/Kripke/build/Kripke/tpl/raja/include/RAJA/pattern/kernel/For.hpp: 137 - 137

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

137:     for (decltype(distance_it) i = 0; i < distance_it; ++i) {

/home/eoseret/qaas_runs_ZEN5/173-940-2141/intel/Kripke/build/Kripke/src/Kripke/Kernel/SweepSubdomain.cpp: 88 - 106

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

88:             double xcos_dxi = 2.0 * xcos(d) / dx(i);

89:             double ycos_dyj = 2.0 * ycos(d) / dy(j);

90:             double zcos_dzk = 2.0 * zcos(d) / dz(k);

[...]

96:                 + psi_lf(d, g, j, k) * xcos_dxi

97:                 + psi_fr(d, g, i, k) * ycos_dyj

98:                 + psi_bo(d, g, i, j) * zcos_dzk)

99:                 / (xcos_dxi + ycos_dyj + zcos_dzk + sigt(g, z));

100:

101:             psi(d, g, z) = psi_d_g_z;

102:

103:             /* Apply diamond-difference relationships */

104:             psi_lf(d, g, j, k) = 2.0 * psi_d_g_z - psi_lf(d, g, j, k);

105:             psi_fr(d, g, i, k) = 2.0 * psi_d_g_z - psi_fr(d, g, i, k);

106:             psi_bo(d, g, i, j) = 2.0 * psi_d_g_z - psi_bo(d, g, i, j);

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	1.00
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	8.47
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.34
Bottlenecks
Function	void RAJA::internal::StatementExecutor, RAJA::statement::For<2l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<3l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<4l, RAJA::policy::sequential::seq_exec, RAJA::statement::Lambda<0l> > > > >, RAJA::internal::LoopTypes, camp::list > >::exec, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&>(RAJA::internal::LoopData, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&) [clone .omp_outlined]
Source	For.hpp:137-137
Source loop unroll info	NA
Source loop unroll confidence level	NA
Unroll/vectorization loop type	NA
Unroll factor	NA
CQA cycles	5.63
CQA cycles if no scalar integer	5.63
CQA cycles if FP arith vectorized	5.63
CQA cycles if fully vectorized	0.66
Front-end cycles	4.19
P0 cycles	1.83
P1 cycles	1.83
P2 cycles	1.83
P3 cycles	1.83
P4 cycles	1.83
P5 cycles	1.83
P6 cycles	5.63
P7 cycles	5.63
P8 cycles	5.63
P9 cycles	5.63
P10 cycles	0.00
P11 cycles	0.00
P12 cycles	0.00
P13 cycles	0.00
P14 cycles	0.00
P15 cycles	0.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	1
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	34.00
Nb uops	33.50
Nb loads	17.50
Nb stores	5.00
Nb stack references	18.00
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	32.00
Bytes prefetched	0.00
Bytes loaded	140.00
Bytes stored	40.00
Stride 0	1.00
Stride 1	0.00
Stride n	0.00
Stride unknown	8.00
Stride indirect	7.00
Vectorization ratio all	0.00
Vectorization ratio load	0.00
Vectorization ratio store	0.00
Vectorization ratio mul	NA
Vectorization ratio add_sub	0.00
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	0.00
Vector-efficiency ratio all	12.28
Vector-efficiency ratio load	12.50
Vector-efficiency ratio store	12.50
Vector-efficiency ratio mul	NA
Vector-efficiency ratio add_sub	12.50
Vector-efficiency ratio fma	NA
Vector-efficiency ratio div_sqrt	NA
Vector-efficiency ratio other	11.25

Metric	Value
CQA speedup if no scalar integer	1.00
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	8.85
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.33
Bottlenecks	P6, P7, P8, P9,
Function	void RAJA::internal::StatementExecutor, RAJA::statement::For<2l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<3l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<4l, RAJA::policy::sequential::seq_exec, RAJA::statement::Lambda<0l> > > > >, RAJA::internal::LoopTypes, camp::list > >::exec, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&>(RAJA::internal::LoopData, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&) [clone .omp_outlined]
Source	For.hpp:137-137
Source loop unroll info	NA
Source loop unroll confidence level	NA
Unroll/vectorization loop type	NA
Unroll factor	NA
CQA cycles	6.50
CQA cycles if no scalar integer	6.50
CQA cycles if FP arith vectorized	6.50
CQA cycles if fully vectorized	0.73
Front-end cycles	4.88
P0 cycles	2.17
P1 cycles	2.17
P2 cycles	2.17
P3 cycles	2.17
P4 cycles	2.17
P5 cycles	2.17
P6 cycles	6.50
P7 cycles	6.50
P8 cycles	6.50
P9 cycles	6.50
P10 cycles	0.00
P11 cycles	0.00
P12 cycles	0.00
P13 cycles	0.00
P14 cycles	0.00
P15 cycles	0.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	1
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	40.00
Nb uops	39.00
Nb loads	20.00
Nb stores	6.00
Nb stack references	21.00
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	32.00
Bytes prefetched	0.00
Bytes loaded	160.00
Bytes stored	48.00
Stride 0	1.00
Stride 1	0.00
Stride n	0.00
Stride unknown	8.00
Stride indirect	7.00
Vectorization ratio all	0.00
Vectorization ratio load	0.00
Vectorization ratio store	0.00
Vectorization ratio mul	NA
Vectorization ratio add_sub	0.00
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	0.00
Vector-efficiency ratio all	12.05
Vector-efficiency ratio load	12.50
Vector-efficiency ratio store	12.50
Vector-efficiency ratio mul	NA
Vector-efficiency ratio add_sub	12.50
Vector-efficiency ratio fma	NA
Vector-efficiency ratio div_sqrt	NA
Vector-efficiency ratio other	10.00

Metric	Value
CQA speedup if no scalar integer	1.00
CQA speedup if FP arith vectorized	1.00
CQA speedup if fully vectorized	8.00
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.36
Bottlenecks	P6, P7, P8, P9,
Function	void RAJA::internal::StatementExecutor, RAJA::statement::For<2l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<3l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<4l, RAJA::policy::sequential::seq_exec, RAJA::statement::Lambda<0l> > > > >, RAJA::internal::LoopTypes, camp::list > >::exec, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&>(RAJA::internal::LoopData, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&) [clone .omp_outlined]
Source	For.hpp:137-137
Source loop unroll info	NA
Source loop unroll confidence level	NA
Unroll/vectorization loop type	NA
Unroll factor	NA
CQA cycles	4.75
CQA cycles if no scalar integer	4.75
CQA cycles if FP arith vectorized	4.75
CQA cycles if fully vectorized	0.59
Front-end cycles	3.50
P0 cycles	1.50
P1 cycles	1.50
P2 cycles	1.50
P3 cycles	1.50
P4 cycles	1.50
P5 cycles	1.50
P6 cycles	4.75
P7 cycles	4.75
P8 cycles	4.75
P9 cycles	4.75
P10 cycles	0.00
P11 cycles	0.00
P12 cycles	0.00
P13 cycles	0.00
P14 cycles	0.00
P15 cycles	0.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	1
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	28.00
Nb uops	28.00
Nb loads	15.00
Nb stores	4.00
Nb stack references	15.00
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	32.00
Bytes prefetched	0.00
Bytes loaded	120.00
Bytes stored	32.00
Stride 0	NA
Stride 1	NA
Stride n	NA
Stride unknown	NA
Stride indirect	NA
Vectorization ratio all	0.00
Vectorization ratio load	0.00
Vectorization ratio store	0.00
Vectorization ratio mul	NA
Vectorization ratio add_sub	0.00
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	0.00
Vector-efficiency ratio all	12.50
Vector-efficiency ratio load	12.50
Vector-efficiency ratio store	12.50
Vector-efficiency ratio mul	NA
Vector-efficiency ratio add_sub	12.50
Vector-efficiency ratio fma	NA
Vector-efficiency ratio div_sqrt	NA
Vector-efficiency ratio other	12.50

Path /

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

Function	void RAJA::internal::StatementExecutor, RAJA::statement::For<2l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<3l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<4l, RAJA::policy::sequential::seq_exec, RAJA::statement::Lambda<0l> > > > >, RAJA::internal::LoopTypes, camp::list > >::exec, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&>(RAJA::internal::LoopData, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&) [clone .omp_outlined]
Source file and lines	For.hpp:137-137
Module	exec

The loop is defined in:

/home/eoseret/qaas_runs_ZEN5/173-940-2141/intel/Kripke/build/Kripke/tpl/raja/include/RAJA/pattern/kernel/For.hpp:137
/home/eoseret/qaas_runs_ZEN5/173-940-2141/intel/Kripke/build/Kripke/src/Kripke/Kernel/SweepSubdomain.cpp:88-90,96-106

Analyzed code is defined in /home/eoseret/qaas_runs_ZEN5/173-940-2141/intel/Kripke/build/Kripke/tpl/raja/include/RAJA/pattern/kernel/For.hpp:137.

Warnings:
Non-innermost loop: analyzing only self part (ignoring child loops).
The structure of this loop is probably <if then [else] end>.

The presence of multiple execution paths is typically the main/first bottleneck.
Try to simplify control inside loop: ideally, try to remove all conditional expressions, for example by (if applicable):

hoisting them (moving them outside the loop)
turning them into conditional moves, MIN or MAX

Ex: if (x<0) x=0 => x = (x<0 ? 0 : x) (or MAX(0,x) after defining the corresponding macro)

gain
potential
hint
expert

Vectorization

Your loop is not vectorized. Only 12% of vector register length is used (average across all SSE/AVX instructions). By vectorizing your loop, you can lower the cost of an iteration from 5.63 to 0.66 cycles (8.47x speedup).

Details

All SSE/AVX 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:
- recompile with ffast-math (included in Ofast) to extend loop vectorization to FP reductions.
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

Slow data structures access

Detected data structures (typically arrays) that cannot be efficiently read/written

Details

Constant unknown stride: 8 occurrence(s)
Irregular (variable stride) or indirect: 7 occurrence(s)

Non-unit stride (uncontiguous) accesses are not efficiently using data caches

Workaround

Try to reorganize arrays of structures to structures of arrays
Consider to permute loops (see vectorization gain report)
Try to remove indirect accesses. If applicable, precompute elements out of the innermost loop.

Type of elements and instruction set

No instructions are processing arithmetic or math operations on FP elements. This loop is probably writing/copying data or processing integer elements.

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 140 bytes. The binary loop is storing 40 bytes.

General properties

nb instructions	34
nb uops	33.50
loop length	162
used x86 registers	12
used mmx registers	0
used xmm registers	0
used ymm registers	0
used zmm registers	0
nb stack references	18

Front-end

MACRO FUSION NOT POSSIBLE

micro-operation queue	4.19 cycles
front end	4.19 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15
uops	1.83	1.83	1.83	1.83	1.83	1.83	5.63	5.63	5.63	5.63	0.00	0.00	0.00	0.00	0.00	0.00
cycles	1.83	1.83	1.83	1.83	1.83	1.83	5.63	5.63	5.63	5.63	0.00	0.00	0.00	0.00	0.00	0.00

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	4.19
Dispatch	5.63
Data deps.	1.00
Overall L1	5.63

Vectorization ratios

all	0%
load	0%
store	0%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	0%
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	0%

Vector efficiency ratios

all	12%
load	12%
store	12%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	12%
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	11%

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 5.63 cycles. At this rate:

9% of peak load performance is reached (24.94 out of 256.00 bytes loaded per cycle (GB/s @ 1GHz))
5% of peak store performance is reached (7.06 out of 128.00 bytes stored per cycle (GB/s @ 1GHz))

Function	void RAJA::internal::StatementExecutor, RAJA::statement::For<2l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<3l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<4l, RAJA::policy::sequential::seq_exec, RAJA::statement::Lambda<0l> > > > >, RAJA::internal::LoopTypes, camp::list > >::exec, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&>(RAJA::internal::LoopData, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&) [clone .omp_outlined]
Source file and lines	For.hpp:137-137
Module	exec

The loop is defined in:

/home/eoseret/qaas_runs_ZEN5/173-940-2141/intel/Kripke/build/Kripke/tpl/raja/include/RAJA/pattern/kernel/For.hpp:137
/home/eoseret/qaas_runs_ZEN5/173-940-2141/intel/Kripke/build/Kripke/src/Kripke/Kernel/SweepSubdomain.cpp:88-90,96-106

hoisting them (moving them outside the loop)
turning them into conditional moves, MIN or MAX

Ex: if (x<0) x=0 => x = (x<0 ? 0 : x) (or MAX(0,x) after defining the corresponding macro)

gain
potential
hint
expert

Vectorization

Details

All SSE/AVX 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:
- recompile with ffast-math (included in Ofast) to extend loop vectorization to FP reductions.
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)

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 6.50 to 4.88 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

No data for this section

Slow data structures access

Detected data structures (typically arrays) that cannot be efficiently read/written

Details

Constant unknown stride: 8 occurrence(s)
Irregular (variable stride) or indirect: 7 occurrence(s)

Non-unit stride (uncontiguous) accesses are not efficiently using data caches

Workaround

Try to reorganize arrays of structures to structures of arrays
Consider to permute loops (see vectorization gain report)
Try to remove indirect accesses. If applicable, precompute elements out of the innermost loop.

Type of elements and instruction set

No instructions are processing arithmetic or math operations on FP elements. This loop is probably writing/copying data or processing integer elements.

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 160 bytes. The binary loop is storing 48 bytes.

General properties

nb instructions	40
nb uops	39
loop length	197
used x86 registers	14
used mmx registers	0
used xmm registers	0
used ymm registers	0
used zmm registers	0
nb stack references	21

Front-end

MACRO FUSION NOT POSSIBLE FIT IN UOP CACHE

micro-operation queue	4.88 cycles
front end	4.88 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12	P13	P14	P15
uops	2.17	2.17	2.17	2.17	2.17	2.17	6.50	6.50	6.50	6.50	0.00	0.00	0.00	0.00	0.00	0.00
cycles	2.17	2.17	2.17	2.17	2.17	2.17	6.50	6.50	6.50	6.50	0.00	0.00	0.00	0.00	0.00	0.00

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	4.88
Dispatch	6.50
Data deps.	1.00
Overall L1	6.50

Vectorization ratios

all	0%
load	0%
store	0%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	0%
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	0%

Vector efficiency ratios

all	12%
load	12%
store	12%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	12%
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	10%

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 6.50 cycles. At this rate:

9% of peak load performance is reached (24.62 out of 256.00 bytes loaded per cycle (GB/s @ 1GHz))
5% of peak store performance is reached (7.38 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: 27af2e

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	Latency	Recip. throughput	Vectorization
MOV -0x30(%RBP),%RDX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
INC %RDX	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	1	0.17	scal (12.5%)
ADD -0x68(%RBP),%R14	1	0.17	0.17	0.17	0.17	0.17	0.17	0.25	0.25	0.25	0.25	1	0.25	scal (12.5%)
MOV -0x70(%RBP),%RAX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	N/A
MOV -0x60(%RBP),%RSI	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
ADD %RAX,%RSI	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	1	0.17	scal (12.5%)
MOV -0x58(%RBP),%R9	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
ADD %RAX,%R9	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	1	0.17	scal (12.5%)
MOV -0x50(%RBP),%RCX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
ADD %RAX,%RCX	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	1	0.17	scal (12.5%)
MOV %RDX,%RAX	1	0	0	0	0	0	0	0	0	0	0	0	0.17	N/A
MOV %RDX,-0x30(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
CMP -0x1c0(%RBP),%RDX	1	0.17	0.17	0.17	0.17	0.17	0.17	0.25	0.25	0.25	0.25	1	0.25	scal (12.5%)
MOV %R9,%RAX	1	0	0	0	0	0	0	0	0	0	0	0	0.17	N/A
MOV %RSI,%RDX	1	0	0	0	0	0	0	0	0	0	0	0	0.17	scal (12.5%)
JE 27abc0 <_ZN4RAJA8internal17StatementExecutorINS_9statement8CollapseINS_26omp_parallel_collapse_execEN4camp7int_seqIlJLl0ELl1EEEEJNS2_3ForILl2ENS_6policy10sequential8seq_execEJNS8_ILl3ESB_JNS8_ILl4ESB_JNS2_6LambdaILl0EJEEEEEEEEEEEEEEENS0_9LoopTypesINS5_4listIJvvvvvEEESK_EEE4execIRNS0_8LoopDataINS5_5tupleIJNS_4SpanINS_9Iterators16numeric_iteratorIN6Kripke9DirectionElPSU_EElEENSQ_INSS_INST_5GroupElPSY_EElEENSQ_INSR_24strided_numeric_iteratorINST_5ZoneKElPS13_EElEENSQ_INS12_INST_5ZoneJElPS17_EElEENSQ_INS12_INST_5ZoneIElPS1B_EElEEEEENSP_IJEEENS5_9resources2v14HostEJZNK9SweepSdomclINST_11ArchLayoutTINST_12ArchT_OpenMPENST_11LayoutT_DGZEEEEEvT_RNST_4Core9DataStoreENST_6SdomIdEEUlSU_SY_S13_S17_S1B_E_EEEEEvOS1Q_.omp_outlined+0x650>	1	0	0	0	0.33	0.33	0.33	0	0	0	0	1	0.50-1	N/A
MOV %RCX,-0x50(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
MOV %RAX,-0x58(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
MOV %RDX,-0x60(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
CMPQ $0,-0x48(%RBP)	1	0.17	0.17	0.17	0.17	0.17	0.17	0.25	0.25	0.25	0.25	1	0.25	scal (12.5%)
MOV -0x1b8(%RBP),%RDX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x1b0(%RBP),%R9	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x1a8(%RBP),%R12	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x1a0(%RBP),%R13	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x198(%RBP),%RSI	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x190(%RBP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x40(%RBP),%RCX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
JLE 27aef0 <_ZN4RAJA8internal17StatementExecutorINS_9statement8CollapseINS_26omp_parallel_collapse_execEN4camp7int_seqIlJLl0ELl1EEEEJNS2_3ForILl2ENS_6policy10sequential8seq_execEJNS8_ILl3ESB_JNS8_ILl4ESB_JNS2_6LambdaILl0EJEEEEEEEEEEEEEEENS0_9LoopTypesINS5_4listIJvvvvvEEESK_EEE4execIRNS0_8LoopDataINS5_5tupleIJNS_4SpanINS_9Iterators16numeric_iteratorIN6Kripke9DirectionElPSU_EElEENSQ_INSS_INST_5GroupElPSY_EElEENSQ_INSR_24strided_numeric_iteratorINST_5ZoneKElPS13_EElEENSQ_INS12_INST_5ZoneJElPS17_EElEENSQ_INS12_INST_5ZoneIElPS1B_EElEEEEENSP_IJEEENS5_9resources2v14HostEJZNK9SweepSdomclINST_11ArchLayoutTINST_12ArchT_OpenMPENST_11LayoutT_DGZEEEEEvT_RNST_4Core9DataStoreENST_6SdomIdEEUlSU_SY_S13_S17_S1B_E_EEEEEvOS1Q_.omp_outlined+0x980>	1	0	0	0	0.33	0.33	0.33	0	0	0	0	1	0.50-1	N/A
MOV -0x30(%RBP),%R10	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	N/A
IMUL -0xc0(%RBP),%R10	1	0.33	0.33	0.33	0	0	0	0.25	0.25	0.25	0.25	3	0.33	N/A
ADD -0xc8(%RBP),%R10	1	0.17	0.17	0.17	0.17	0.17	0.17	0.25	0.25	0.25	0.25	1	0.25	N/A
MOV -0x188(%RBP),%RAX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	N/A
MOV %R10,-0xd8(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
ADD %R10,%RAX	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	1	0.17	N/A
MOV %RAX,-0xd0(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
XOR %R15D,%R15D	1	0	0	0	0	0	0	0	0	0	0	0	0.25	scal (6.3%)
XOR %EBX,%EBX	1	0	0	0	0	0	0	0	0	0	0	0	0.25	scal (6.3%)
MOV -0xb8(%RBP),%R11	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
NOPW %CS:(%RAX,%RAX,1)	0	0	0	0	0	0	0	0	0	0	0	0	0.09	N/A
JMP 27aef0 <_ZN4RAJA8internal17StatementExecutorINS_9statement8CollapseINS_26omp_parallel_collapse_execEN4camp7int_seqIlJLl0ELl1EEEEJNS2_3ForILl2ENS_6policy10sequential8seq_execEJNS8_ILl3ESB_JNS8_ILl4ESB_JNS2_6LambdaILl0EJEEEEEEEEEEEEEEENS0_9LoopTypesINS5_4listIJvvvvvEEESK_EEE4execIRNS0_8LoopDataINS5_5tupleIJNS_4SpanINS_9Iterators16numeric_iteratorIN6Kripke9DirectionElPSU_EElEENSQ_INSS_INST_5GroupElPSY_EElEENSQ_INSR_24strided_numeric_iteratorINST_5ZoneKElPS13_EElEENSQ_INS12_INST_5ZoneJElPS17_EElEENSQ_INS12_INST_5ZoneIElPS1B_EElEEEEENSP_IJEEENS5_9resources2v14HostEJZNK9SweepSdomclINST_11ArchLayoutTINST_12ArchT_OpenMPENST_11LayoutT_DGZEEEEEvT_RNST_4Core9DataStoreENST_6SdomIdEEUlSU_SY_S13_S17_S1B_E_EEEEEvOS1Q_.omp_outlined+0x980>	1	0	0	0	0.33	0.33	0.33	0	0	0	0	0	1	N/A

Function	void RAJA::internal::StatementExecutor, RAJA::statement::For<2l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<3l, RAJA::policy::sequential::seq_exec, RAJA::statement::For<4l, RAJA::policy::sequential::seq_exec, RAJA::statement::Lambda<0l> > > > >, RAJA::internal::LoopTypes, camp::list > >::exec, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&>(RAJA::internal::LoopData, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long>, RAJA::Span, long> >, camp::tuple<>, camp::resources::v1::Host, SweepSdom::operator() >(Kripke::ArchLayoutT, Kripke::Core::DataStore&, Kripke::SdomId) const::{lambda(Kripke::Direction, Kripke::Group, Kripke::ZoneK, Kripke::ZoneJ, Kripke::ZoneI)#1}>&) [clone .omp_outlined]
Source file and lines	For.hpp:137-137
Module	exec

The loop is defined in:

/home/eoseret/qaas_runs_ZEN5/173-940-2141/intel/Kripke/build/Kripke/tpl/raja/include/RAJA/pattern/kernel/For.hpp:137
/home/eoseret/qaas_runs_ZEN5/173-940-2141/intel/Kripke/build/Kripke/src/Kripke/Kernel/SweepSubdomain.cpp:88-90,96-106

hoisting them (moving them outside the loop)
turning them into conditional moves, MIN or MAX

Ex: if (x<0) x=0 => x = (x<0 ? 0 : x) (or MAX(0,x) after defining the corresponding macro)

gain
potential
hint
expert

Vectorization

Your loop is not vectorized. 8 data elements could be processed at once in vector registers. By vectorizing your loop, you can lower the cost of an iteration from 4.75 to 0.59 cycles (8.00x speedup).

Details

All SSE/AVX 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:
- recompile with ffast-math (included in Ofast) to extend loop vectorization to FP reductions.
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)

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 4.75 to 3.50 cycles (1.36x speedup).

Workaround

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

No data for this section

Type of elements and instruction set

No instructions are processing arithmetic or math operations on FP elements. This loop is probably writing/copying data or processing integer elements.

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 120 bytes. The binary loop is storing 32 bytes.

General properties

nb instructions	28
nb uops	28
loop length	127
used x86 registers	10
used mmx registers	0
used xmm registers	0
used ymm registers	0
used zmm registers	0
nb stack references	15

Front-end

MACRO FUSION NOT POSSIBLE 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	1.50	1.50	1.50	1.50	1.50	1.50	4.75	4.75	4.75	4.75	0.00	0.00	0.00	0.00	0.00	0.00
cycles	1.50	1.50	1.50	1.50	1.50	1.50	4.75	4.75	4.75	4.75	0.00	0.00	0.00	0.00	0.00	0.00

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	3.50
Dispatch	4.75
Data deps.	1.00
Overall L1	4.75

Vectorization ratios

all	0%
load	0%
store	0%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	0%
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	0%

Vector efficiency ratios

all	12%
load	12%
store	12%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	12%
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	12%

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 4.75 cycles. At this rate:

9% of peak load performance is reached (25.26 out of 256.00 bytes loaded per cycle (GB/s @ 1GHz))
5% of peak store performance is reached (6.74 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: 27af2e

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	P8	P9	Latency	Recip. throughput	Vectorization
MOV -0x30(%RBP),%RDX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
INC %RDX	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	1	0.17	scal (12.5%)
ADD -0x68(%RBP),%R14	1	0.17	0.17	0.17	0.17	0.17	0.17	0.25	0.25	0.25	0.25	1	0.25	scal (12.5%)
MOV -0x70(%RBP),%RAX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x60(%RBP),%RSI	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
ADD %RAX,%RSI	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	1	0.17	scal (12.5%)
MOV -0x58(%RBP),%R9	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
ADD %RAX,%R9	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	1	0.17	scal (12.5%)
MOV -0x50(%RBP),%RCX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
ADD %RAX,%RCX	1	0.17	0.17	0.17	0.17	0.17	0.17	0	0	0	0	1	0.17	scal (12.5%)
MOV %RDX,%RAX	1	0	0	0	0	0	0	0	0	0	0	0	0.17	scal (12.5%)
MOV %RDX,-0x30(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
CMP -0x1c0(%RBP),%RDX	1	0.17	0.17	0.17	0.17	0.17	0.17	0.25	0.25	0.25	0.25	1	0.25	scal (12.5%)
MOV %R9,%RAX	1	0	0	0	0	0	0	0	0	0	0	0	0.17	scal (12.5%)
MOV %RSI,%RDX	1	0	0	0	0	0	0	0	0	0	0	0	0.17	scal (12.5%)
JE 27abc0 <_ZN4RAJA8internal17StatementExecutorINS_9statement8CollapseINS_26omp_parallel_collapse_execEN4camp7int_seqIlJLl0ELl1EEEEJNS2_3ForILl2ENS_6policy10sequential8seq_execEJNS8_ILl3ESB_JNS8_ILl4ESB_JNS2_6LambdaILl0EJEEEEEEEEEEEEEEENS0_9LoopTypesINS5_4listIJvvvvvEEESK_EEE4execIRNS0_8LoopDataINS5_5tupleIJNS_4SpanINS_9Iterators16numeric_iteratorIN6Kripke9DirectionElPSU_EElEENSQ_INSS_INST_5GroupElPSY_EElEENSQ_INSR_24strided_numeric_iteratorINST_5ZoneKElPS13_EElEENSQ_INS12_INST_5ZoneJElPS17_EElEENSQ_INS12_INST_5ZoneIElPS1B_EElEEEEENSP_IJEEENS5_9resources2v14HostEJZNK9SweepSdomclINST_11ArchLayoutTINST_12ArchT_OpenMPENST_11LayoutT_DGZEEEEEvT_RNST_4Core9DataStoreENST_6SdomIdEEUlSU_SY_S13_S17_S1B_E_EEEEEvOS1Q_.omp_outlined+0x650>	1	0	0	0	0.33	0.33	0.33	0	0	0	0	1	0.50-1	N/A
MOV %RCX,-0x50(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
MOV %RAX,-0x58(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
MOV %RDX,-0x60(%RBP)	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	4	0.50	scal (12.5%)
CMPQ $0,-0x48(%RBP)	1	0.17	0.17	0.17	0.17	0.17	0.17	0.25	0.25	0.25	0.25	1	0.25	N/A
MOV -0x1b8(%RBP),%RDX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x1b0(%RBP),%R9	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x1a8(%RBP),%R12	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x1a0(%RBP),%R13	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x198(%RBP),%RSI	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x190(%RBP),%R8	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
MOV -0x40(%RBP),%RCX	1	0	0	0	0	0	0	0.25	0.25	0.25	0.25	3	0.25	scal (12.5%)
JLE 27aef0 <_ZN4RAJA8internal17StatementExecutorINS_9statement8CollapseINS_26omp_parallel_collapse_execEN4camp7int_seqIlJLl0ELl1EEEEJNS2_3ForILl2ENS_6policy10sequential8seq_execEJNS8_ILl3ESB_JNS8_ILl4ESB_JNS2_6LambdaILl0EJEEEEEEEEEEEEEEENS0_9LoopTypesINS5_4listIJvvvvvEEESK_EEE4execIRNS0_8LoopDataINS5_5tupleIJNS_4SpanINS_9Iterators16numeric_iteratorIN6Kripke9DirectionElPSU_EElEENSQ_INSS_INST_5GroupElPSY_EElEENSQ_INSR_24strided_numeric_iteratorINST_5ZoneKElPS13_EElEENSQ_INS12_INST_5ZoneJElPS17_EElEENSQ_INS12_INST_5ZoneIElPS1B_EElEEEEENSP_IJEEENS5_9resources2v14HostEJZNK9SweepSdomclINST_11ArchLayoutTINST_12ArchT_OpenMPENST_11LayoutT_DGZEEEEEvT_RNST_4Core9DataStoreENST_6SdomIdEEUlSU_SY_S13_S17_S1B_E_EEEEEvOS1Q_.omp_outlined+0x980>	1	0	0	0	0.33	0.33	0.33	0	0	0	0	1	0.50-1	N/A

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Slow data structures access

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Type of elements and instruction set

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

General properties

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Cycles summary

Vectorization ratios

Vector efficiency ratios

Cycles and memory resources usage

Vectorization

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Execution units bottlenecks

Workaround

Slow data structures access

Details

Workaround

Type of elements and instruction set

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

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

Type of elements and instruction set

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

General properties

Front-end

Back-end

Cycles summary

Vectorization ratios

Vector efficiency ratios

Cycles and memory resources usage

Front-end bottlenecks

ASM code