OV - attention-gcc-skl512 - Loop 26

	Loop Id: 26	Module: attention-gcc-skl512	Source: random.tcc:458-3558 [...]	Coverage: 0.14%

0x1bc8 LEA	0x1(%RDX),%RAX

0x1bcc MOV	-0x2770(%RBP,%RDX,8),%RDX    [1]

0x1bd4 MOV	%RAX,-0x13f0(%RBP)    [1]

0x1bdb MOV	%RDX,%RCX

0x1bde SHR	$0xb,%RCX

0x1be2 MOV	%ECX,%ECX

0x1be4 XOR	%RCX,%RDX

0x1be7 MOV	%RDX,%RCX

0x1bea SAL	$0x7,%RCX

0x1bee AND	$-0x62d3a980,%ECX

0x1bf4 XOR	%RCX,%RDX

0x1bf7 MOV	%RDX,%RCX

0x1bfa SAL	$0xf,%RCX

0x1bfe AND	$-0x103a0000,%ECX

0x1c04 XOR	%RCX,%RDX

0x1c07 MOV	%RDX,%RCX

0x1c0a SHR	$0x12,%RCX

0x1c0e XOR	%RCX,%RDX

0x1c11 VCVTUSI2SS	%EDX,%XMM1,%XMM0

0x1c17 VMULSS	0x23e9(%RIP),%XMM0,%XMM0    [2]

0x1c1f VCOMISS	%XMM0,%XMM3

0x1c23 JA	1c6d

0x1c25 MOV	%RAX,%RDX

0x1c28 CMP	$0x26f,%RAX

0x1c2e JBE	1bc8

0x1c30 VMOVAPS	%XMM1,-0x2800(%RBP)    [1]

0x1c38 LEA	-0x2770(%RBP),%RDI

0x1c3f VZEROUPPER

0x1c42 CALL	36c0 <_ZNSt23mersenne_twister_engineImLm32ELm624ELm397ELm31ELm2567483615ELm11ELm4294967295ELm7ELm2636928640ELm15ELm4022730752ELm18ELm1812433253EE11_M_gen_randEv>

0x1c47 MOV	-0x13f0(%RBP),%RDX    [1]

0x1c4e VMOVAPS	-0x2800(%RBP),%XMM1    [1]

0x1c56 VMOVSS	0x23ae(%RIP),%XMM3    [2]

0x1c5e VMOVDQA64	0x25d8(%RIP),%ZMM7    [2]

0x1c68 JMP	1bc8

/usr/include/c++/16.1.1/bits/random.tcc: 458 - 3558

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

458:       if (_M_p >= state_size)

459: 	_M_gen_rand();

460:

461:       // Calculate o(x(i)).

462:       result_type __z = _M_x[_M_p++];

463:       __z ^= (__z >> __u) & __d;

464:       __z ^= (__z << __s) & __b;

465:       __z ^= (__z << __t) & __c;

466:       __z ^= (__z >> __l);

[...]

3557: 	  const _RealT __ret = _RealT(__sum >> __log2_x) / _RealT(__rd);

3558: 	  if (__ret < _RealT(1.0))

Coverage (%)	Name	Source Location	Module
►100.00+	__libc_init_first		libc.so.6
○	__libc_start_main		libc.so.6
○	_start	new_allocator.h:183	attention-gcc-skl512

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	2.67
CQA speedup if FP arith vectorized	2.33
CQA speedup if fully vectorized	2.39
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.68
Bottlenecks
Function	main
Source	random.tcc:458-466,random.tcc:3557-3558
Source loop unroll info	unrolled by 5
Source loop unroll confidence level	low
Unroll/vectorization loop type	main
Unroll factor	5
CQA cycles	8.00
CQA cycles if no scalar integer	3.00
CQA cycles if FP arith vectorized	3.43
CQA cycles if fully vectorized	3.35
Front-end cycles	8.00
P0 cycles	4.75
P1 cycles	4.75
P2 cycles	2.00
P3 cycles	2.00
P4 cycles	2.00
P5 cycles	4.75
P6 cycles	4.75
P7 cycles	2.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	0
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	29.50
Nb uops	32.00
Nb loads	4.00
Nb stores	1.50
Nb stack references	2.00
FLOP/cycle	0.13
Nb FLOP add-sub	0.00
Nb FLOP mul	1.00
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	8.16
Bytes prefetched	0.00
Bytes loaded	58.00
Bytes stored	16.00
Stride 0	1.50
Stride 1	0.00
Stride n	0.00
Stride unknown	0.50
Stride indirect	0.00
Vectorization ratio all	10.00
Vectorization ratio load	25.00
Vectorization ratio store	25.00
Vectorization ratio mul	0.00
Vectorization ratio add_sub	NA
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	3.57
Vector-efficiency ratio all	13.28
Vector-efficiency ratio load	20.31
Vector-efficiency ratio store	15.63
Vector-efficiency ratio mul	6.25
Vector-efficiency ratio add_sub	NA
Vector-efficiency ratio fma	NA
Vector-efficiency ratio div_sqrt	NA
Vector-efficiency ratio other	10.63

Metric	Value
CQA speedup if no scalar integer	2.44
CQA speedup if FP arith vectorized	2.30
CQA speedup if fully vectorized	1.56
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.86
Bottlenecks	micro-operation queue,
Function	main
Source	random.tcc:458-466,random.tcc:3557-3558
Source loop unroll info	unrolled by 5
Source loop unroll confidence level	low
Unroll/vectorization loop type	main
Unroll factor	5
CQA cycles	9.75
CQA cycles if no scalar integer	4.00
CQA cycles if FP arith vectorized	4.24
CQA cycles if fully vectorized	6.24
Front-end cycles	9.75
P0 cycles	5.25
P1 cycles	5.25
P2 cycles	3.00
P3 cycles	3.00
P4 cycles	3.00
P5 cycles	5.25
P6 cycles	5.25
P7 cycles	3.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	0
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	34.00
Nb uops	39.00
Nb loads	6.00
Nb stores	2.00
Nb stack references	3.00
FLOP/cycle	0.10
Nb FLOP add-sub	0.00
Nb FLOP mul	1.00
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	13.13
Bytes prefetched	0.00
Bytes loaded	104.00
Bytes stored	24.00
Stride 0	2.00
Stride 1	0.00
Stride n	0.00
Stride unknown	0.00
Stride indirect	0.00
Vectorization ratio all	20.00
Vectorization ratio load	50.00
Vectorization ratio store	50.00
Vectorization ratio mul	0.00
Vectorization ratio add_sub	NA
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	7.14
Vector-efficiency ratio all	16.56
Vector-efficiency ratio load	34.38
Vector-efficiency ratio store	18.75
Vector-efficiency ratio mul	6.25
Vector-efficiency ratio add_sub	NA
Vector-efficiency ratio fma	NA
Vector-efficiency ratio div_sqrt	NA
Vector-efficiency ratio other	11.16

Metric	Value
CQA speedup if no scalar integer	3.13
CQA speedup if FP arith vectorized	2.39
CQA speedup if fully vectorized	13.33
CQA speedup if no inter-iteration dependency	NA
CQA speedup if next bottleneck killed	1.47
Bottlenecks	micro-operation queue,
Function	main
Source	random.tcc:458-466,random.tcc:3557-3558
Source loop unroll info	unrolled by 5
Source loop unroll confidence level	low
Unroll/vectorization loop type	main
Unroll factor	5
CQA cycles	6.25
CQA cycles if no scalar integer	2.00
CQA cycles if FP arith vectorized	2.62
CQA cycles if fully vectorized	0.47
Front-end cycles	6.25
P0 cycles	4.25
P1 cycles	4.25
P2 cycles	1.00
P3 cycles	1.00
P4 cycles	1.00
P5 cycles	4.25
P6 cycles	4.25
P7 cycles	1.00
DIV/SQRT cycles	0.00
Inter-iter dependencies cycles	0
FE+BE cycles (UFS)	NA
Stall cycles (UFS)	NA
Nb insns	25.00
Nb uops	25.00
Nb loads	2.00
Nb stores	1.00
Nb stack references	1.00
FLOP/cycle	0.16
Nb FLOP add-sub	0.00
Nb FLOP mul	1.00
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	3.20
Bytes prefetched	0.00
Bytes loaded	12.00
Bytes stored	8.00
Stride 0	1.00
Stride 1	0.00
Stride n	0.00
Stride unknown	1.00
Stride indirect	0.00
Vectorization ratio all	0.00
Vectorization ratio load	0.00
Vectorization ratio store	0.00
Vectorization ratio mul	0.00
Vectorization ratio add_sub	NA
Vectorization ratio fma	NA
Vectorization ratio div_sqrt	NA
Vectorization ratio other	0.00
Vector-efficiency ratio all	10.00
Vector-efficiency ratio load	6.25
Vector-efficiency ratio store	12.50
Vector-efficiency ratio mul	6.25
Vector-efficiency ratio add_sub	NA
Vector-efficiency ratio fma	NA
Vector-efficiency ratio div_sqrt	NA
Vector-efficiency ratio other	10.10

Path /

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

Function	main
Source file and lines	random.tcc:458-3558
Module	attention-gcc-skl512

The loop is defined in /usr/include/c++/16.1.1/bits/random.tcc:458-466,3557-3558.

It is main loop of related source loop which is unrolled by 5 (including vectorization).
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 13% of vector register length is used (average across all SSE/AVX instructions). By fully vectorizing your loop, you can lower the cost of an iteration from 8.00 to 3.35 cycles (2.39x speedup).

Details

10% of SSE/AVX instructions are used in vector version (process two or more data elements in vector registers):

25% of SSE/AVX loads are used in vector version.
25% of SSE/AVX stores are used in vector version.
0% of SSE/AVX multiply instructions are used in vector version.
3% of SSE/AVX instructions that are not load, store, addition, subtraction nor multiply instructions are used in vector version.

Since your execution units are vector units, only a fully vectorized loop can use their full power.

Workaround

Try another compiler or update/tune your current one
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

CALL instructions

Detected function call instructions.

Details

Calling (and then returning from) a function prevents many compiler optimizations (like vectorization), breaks control flow (which reduces pipeline performance) and executes extra instructions to save/restore the registers used inside it, which is very expensive (dozens of cycles). Consider to inline small functions.

std::mersenne_twister_engine::_M_gen_rand(): 0 occurrences

Complex instructions

Detected COMPLEX INSTRUCTIONS.

Details

These instructions generate more than one micro-operation and only one of them can be decoded during a cycle and the extra micro-operations increase pressure on execution units.

VCVTUSI2SS: 0 occurrences
VZEROUPPER: 0 occurrences

Slow data structures access

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

Details

Constant unknown stride: 0 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)

Conversion instructions

Detected expensive conversion instructions.

Details

VCVTUSI2SS (INT32/64 to FP32, scalar): 0 occurrences

Workaround

Avoid mixing data with different types. In particular, check if the type of constants is the same as array elements.

Type of elements and instruction set

2 SSE or AVX instructions are processing arithmetic or math operations on single precision FP elements in scalar mode (one at a time).

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

The binary loop is composed of 1 FP arithmetical operations:

1: multiply

The binary loop is loading 58 bytes (14 single precision FP elements). The binary loop is storing 16 bytes (4 single precision FP elements).

Arithmetic intensity

Arithmetic intensity is 0.01 FP operations per loaded or stored byte.

General properties

nb instructions	29.50
nb uops	32
loop length	134.50
used x86 registers	4.50
used mmx registers	0
used xmm registers	3
used ymm registers	0
used zmm registers	0.50
nb stack references	2

Front-end

MACRO FUSION NOT POSSIBLE

micro-operation queue	8.00 cycles
front end	8.00 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7
uops	4.75	4.75	2.00	2.00	2.00	4.75	4.75	2.00
cycles	4.75	4.75	2.00	2.00	2.00	4.75	4.75	2.00

Execution ports to units layout:

P0 (256 bits): VPU, BRU, ALU, DIV/SQRT
P1 (256 bits): ALU, VPU
P2 (512 bits): store address, load
P3 (512 bits): store address, load
P4 (512 bits): store data
P5 (512 bits): ALU, VPU
P6: ALU, BRU
P7: store address

Cycles executing div or sqrt instructions	NA
Longest recurrence chain latency (RecMII)	0.00

Cycles summary

Front-end	8.00
Dispatch	4.75
Data deps.	0.00
Overall L1	8.00

Vectorization ratios

INT

all	6%
load	100%
store	0%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
other	3%

all	20%
load	16%
store	100%
mul	0%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	0%

INT+FP

all	10%
load	25%
store	25%
mul	0%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	3%

Vector efficiency ratios

INT

all	14%
load	100%
store	12%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
other	10%

all	10%
load	9%
store	25%
mul	6%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	6%

INT+FP

all	13%
load	20%
store	15%
mul	6%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	10%

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 8.00 cycles. At this rate:

4% of peak load performance is reached (6.29 out of 128.00 bytes loaded per cycle (GB/s @ 1GHz))
2% of peak store performance is reached (1.87 out of 64.00 bytes stored per cycle (GB/s @ 1GHz))

Function	main
Source file and lines	random.tcc:458-3558
Module	attention-gcc-skl512

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

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 9.75 to 4.00 cycles (2.44x speedup).

Workaround

Try to reorganize arrays of structures to structures of arrays
Consider to permute loops (see vectorization gain report)

Vectorization

Your loop is poorly vectorized. Only 16% of vector register length is used (average across all SSE/AVX instructions). By fully vectorizing your loop, you can lower the cost of an iteration from 9.75 to 6.24 cycles (1.56x speedup).

Details

20% of SSE/AVX instructions are used in vector version (process two or more data elements in vector registers):

50% of SSE/AVX loads are used in vector version.
50% of SSE/AVX stores are used in vector version.
0% of SSE/AVX multiply instructions are used in vector version.
7% of SSE/AVX instructions that are not load, store, addition, subtraction nor multiply instructions are used in vector version.

Since your execution units are vector units, only a fully vectorized loop can use their full power.

Workaround

Try another compiler or update/tune your current one
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

Found no such bottlenecks but see expert reports for more complex bottlenecks.

No data for this section

CALL instructions

Detected function call instructions.

Details

std::mersenne_twister_engine
::_M_gen_rand(): 1 occurrences►

Complex instructions

Detected COMPLEX INSTRUCTIONS.

Details

These instructions generate more than one micro-operation and only one of them can be decoded during a cycle and the extra micro-operations increase pressure on execution units.

VCVTUSI2SS: 1 occurrences►
- /usr/include/c++/16.1.1/bits/random.tcc:3557
VZEROUPPER: 1 occurrences►
- /usr/include/c++/16.1.1/bits/random.tcc:459

Conversion instructions

Detected expensive conversion instructions.

Details

VCVTUSI2SS (INT32/64 to FP32, scalar): 1 occurrences►
- /usr/include/c++/16.1.1/bits/random.tcc:3557

Workaround

Avoid mixing data with different types. In particular, check if the type of constants is the same as array elements.

Type of elements and instruction set

2 SSE or AVX instructions are processing arithmetic or math operations on single precision FP elements in scalar mode (one at a time).

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

The binary loop is composed of 1 FP arithmetical operations:

1: multiply

The binary loop is loading 104 bytes (26 single precision FP elements). The binary loop is storing 24 bytes (6 single precision FP elements).

Arithmetic intensity

Arithmetic intensity is 0.01 FP operations per loaded or stored byte.

General properties

nb instructions	34
nb uops	39
loop length	165
used x86 registers	5
used mmx registers	0
used xmm registers	3
used ymm registers	0
used zmm registers	1
nb stack references	3

Front-end

MACRO FUSION NOT POSSIBLE FIT IN UOP CACHE

micro-operation queue	9.75 cycles
front end	9.75 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7
uops	5.25	5.25	3.00	3.00	3.00	5.25	5.25	3.00
cycles	5.25	5.25	3.00	3.00	3.00	5.25	5.25	3.00

Execution ports to units layout:

P0 (256 bits): VPU, BRU, ALU, DIV/SQRT
P1 (256 bits): ALU, VPU
P2 (512 bits): store address, load
P3 (512 bits): store address, load
P4 (512 bits): store data
P5 (512 bits): ALU, VPU
P6: ALU, BRU
P7: store address

Cycles executing div or sqrt instructions	NA
Longest recurrence chain latency (RecMII)	0.00

Cycles summary

Front-end	9.75
Dispatch	5.25
Data deps.	0.00
Overall L1	9.75

Vectorization ratios

INT

all	13%
load	100%
store	0%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
other	7%

all	40%
load	33%
store	100%
mul	0%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	0%

INT+FP

all	20%
load	50%
store	50%
mul	0%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	7%

Vector efficiency ratios

INT

all	17%
load	100%
store	12%
mul	NA (no mul vectorizable/vectorized instructions)
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
other	11%

all	13%
load	12%
store	25%
mul	6%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	6%

INT+FP

all	16%
load	34%
store	18%
mul	6%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	11%

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 9.75 cycles. At this rate:

8% of peak load performance is reached (10.67 out of 128.00 bytes loaded per cycle (GB/s @ 1GHz))
3% of peak store performance is reached (2.46 out of 64.00 bytes stored per cycle (GB/s @ 1GHz))

Front-end bottlenecks

Performance is limited by instruction throughput (loading/decoding program instructions to execution core) (front-end is a bottleneck). By removing all these bottlenecks, you can lower the cost of an iteration from 9.75 to 5.25 cycles (1.86x speedup).

ASM code

In the binary file, the address of the loop is: 1c25

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	Latency	Recip. throughput	Vectorization
LEA 0x1(%RDX),%RAX	1	0	0.50	0	0	0	0.50	0	0	1	0.50	N/A
MOV -0x2770(%RBP,%RDX,8),%RDX	1	0	0	0.50	0.50	0	0	0	0	4-5	0.50	N/A
MOV %RAX,-0x13f0(%RBP)	1	0	0	0.33	0.33	1	0	0	0.33	3	1	scal (12.5%)
MOV %RDX,%RCX	1	0	0	0	0	0	0	0	0	0	0.25	scal (12.5%)
SHR $0xb,%RCX	1	0.50	0	0	0	0	0	0.50	0	1	0.50	scal (12.5%)
MOV %ECX,%ECX	1	0	0	0	0	0	0	0	0	0	0.25	scal (6.3%)
XOR %RCX,%RDX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
MOV %RDX,%RCX	1	0	0	0	0	0	0	0	0	0	0.25	scal (12.5%)
SAL $0x7,%RCX	1	0.50	0	0	0	0	0	0.50	0	1	0.50	scal (12.5%)
AND $-0x62d3a980,%ECX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	scal (6.3%)
XOR %RCX,%RDX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
MOV %RDX,%RCX	1	0	0	0	0	0	0	0	0	0	0.25	scal (12.5%)
SAL $0xf,%RCX	1	0.50	0	0	0	0	0	0.50	0	1	0.50	scal (12.5%)
AND $-0x103a0000,%ECX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	scal (6.3%)
XOR %RCX,%RDX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
MOV %RDX,%RCX	1	0	0	0	0	0	0	0	0	0	0.25	scal (12.5%)
SHR $0x12,%RCX	1	0.50	0	0	0	0	0	0.50	0	1	0.50	scal (12.5%)
XOR %RCX,%RDX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
VCVTUSI2SS %EDX,%XMM1,%XMM0	2	0.50	0.50	0	0	0	1	0	0	6	1	scal (6.3%)
VMULSS 0x23e9(%RIP),%XMM0,%XMM0	1	0.50	0.50	0.50	0.50	0	0	0	0	4	0.50	scal (6.3%)
VCOMISS %XMM0,%XMM3	1	1	0	0	0	0	0	0	0	3	1	scal (6.3%)
JA 1c6d <main+0x92d>	1	0.50	0	0	0	0	0	0.50	0	0	0.50-1	N/A
MOV %RAX,%RDX	1	0	0	0	0	0	0	0	0	0	0.25	N/A
CMP $0x26f,%RAX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
JBE 1bc8 <main+0x888>	1	0.50	0	0	0	0	0	0.50	0	0	0.50-1	N/A
VMOVAPS %XMM1,-0x2800(%RBP)	1	0	0	0.33	0.33	1	0	0	0.33	3	1	vect (25.0%)
LEA -0x2770(%RBP),%RDI	1	0	0.50	0	0	0	0.50	0	0	1	0.50	N/A
VZEROUPPER	4	0	0	0	0	0	0	0	0	0	1	vect (25.0%)
CALL 36c0 <_ZNSt23mersenne_twister_engineImLm32ELm624ELm397ELm31ELm2567483615ELm11ELm4294967295ELm7ELm2636928640ELm15ELm4022730752ELm18ELm1812433253EE11_M_gen_randEv>	2	0	0	0.33	0.33	1	0	1	0.33	0	1	N/A
MOV -0x13f0(%RBP),%RDX	1	0	0	0.50	0.50	0	0	0	0	4-5	0.50	N/A
VMOVAPS -0x2800(%RBP),%XMM1	1	0	0	0.50	0.50	0	0	0	0	4-5	0.50	vect (25.0%)
VMOVSS 0x23ae(%RIP),%XMM3	1	0	0	0.50	0.50	0	0	0	0	4-5	0.50	scal (6.3%)
VMOVDQA64 0x25d8(%RIP),%ZMM7	1	0	0	0.50	0.50	0	0	0	0	5	0.50	vect (100.0%)
JMP 1bc8 <main+0x888>	1	0	0	0	0	0	0	1	0	0	1-2	N/A

Function	main
Source file and lines	random.tcc:458-3558
Module	attention-gcc-skl512

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

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 6.25 to 2.00 cycles (3.12x speedup).

Workaround

Try to reorganize arrays of structures to structures of arrays
Consider to permute loops (see vectorization gain report)

Vectorization

Your loop is not vectorized. Only 10% 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 6.25 to 0.47 cycles (13.33x 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
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

Found no such bottlenecks but see expert reports for more complex bottlenecks.

No data for this section

Complex instructions

Detected COMPLEX INSTRUCTIONS.

Details

These instructions generate more than one micro-operation and only one of them can be decoded during a cycle and the extra micro-operations increase pressure on execution units.

VCVTUSI2SS: 1 occurrences►
- /usr/include/c++/16.1.1/bits/random.tcc:3557

Slow data structures access

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

Details

Constant unknown stride: 1 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)

Conversion instructions

Detected expensive conversion instructions.

Details

VCVTUSI2SS (INT32/64 to FP32, scalar): 1 occurrences►
- /usr/include/c++/16.1.1/bits/random.tcc:3557

Workaround

Avoid mixing data with different types. In particular, check if the type of constants is the same as array elements.

Type of elements and instruction set

2 SSE or AVX instructions are processing arithmetic or math operations on single precision FP elements in scalar mode (one at a time).

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

The binary loop is composed of 1 FP arithmetical operations:

1: multiply

The binary loop is loading 12 bytes (3 single precision FP elements). The binary loop is storing 8 bytes (2 single precision FP elements).

Arithmetic intensity

Arithmetic intensity is 0.05 FP operations per loaded or stored byte.

General properties

nb instructions	25
nb uops	25
loop length	104
used x86 registers	4
used mmx registers	0
used xmm registers	3
used ymm registers	0
used zmm registers	0
nb stack references	1

Front-end

ASSUMED MACRO FUSION FIT IN UOP CACHE

micro-operation queue	6.25 cycles
front end	6.25 cycles

Back-end

	P0	P1	P2	P3	P4	P5	P6	P7
uops	4.25	4.25	1.00	1.00	1.00	4.25	4.25	1.00
cycles	4.25	4.25	1.00	1.00	1.00	4.25	4.25	1.00

Execution ports to units layout:

P0 (256 bits): VPU, BRU, ALU, DIV/SQRT
P1 (256 bits): ALU, VPU
P2 (512 bits): store address, load
P3 (512 bits): store address, load
P4 (512 bits): store data
P5 (512 bits): ALU, VPU
P6: ALU, BRU
P7: store address

Cycles executing div or sqrt instructions	NA
Longest recurrence chain latency (RecMII)	0.00

Cycles summary

Front-end	6.25
Dispatch	4.25
Data deps.	0.00
Overall L1	6.25

Vectorization ratios

INT

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

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

INT+FP

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

Vector efficiency ratios

INT

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

all	6%
load	6%
store	NA (no store vectorizable/vectorized instructions)
mul	6%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	6%

INT+FP

all	10%
load	6%
store	12%
mul	6%
add-sub	NA (no add-sub vectorizable/vectorized instructions)
fma	NA (no fma vectorizable/vectorized instructions)
div/sqrt	NA (no div/sqrt vectorizable/vectorized instructions)
other	10%

Cycles and memory resources usage

Assuming all data fit into the L1 cache, each iteration of the binary loop takes 6.25 cycles. At this rate:

1% of peak load performance is reached (1.92 out of 128.00 bytes loaded per cycle (GB/s @ 1GHz))
2% of peak store performance is reached (1.28 out of 64.00 bytes stored per cycle (GB/s @ 1GHz))

Front-end bottlenecks

ASM code

In the binary file, the address of the loop is: 1c25

Instruction	Nb FU	P0	P1	P2	P3	P4	P5	P6	P7	Latency	Recip. throughput	Vectorization
LEA 0x1(%RDX),%RAX	1	0	0.50	0	0	0	0.50	0	0	1	0.50	N/A
MOV -0x2770(%RBP,%RDX,8),%RDX	1	0	0	0.50	0.50	0	0	0	0	4-5	0.50	N/A
MOV %RAX,-0x13f0(%RBP)	1	0	0	0.33	0.33	1	0	0	0.33	3	1	scal (12.5%)
MOV %RDX,%RCX	1	0	0	0	0	0	0	0	0	0	0.25	scal (12.5%)
SHR $0xb,%RCX	1	0.50	0	0	0	0	0	0.50	0	1	0.50	scal (12.5%)
MOV %ECX,%ECX	1	0	0	0	0	0	0	0	0	0	0.25	scal (6.3%)
XOR %RCX,%RDX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
MOV %RDX,%RCX	1	0	0	0	0	0	0	0	0	0	0.25	scal (12.5%)
SAL $0x7,%RCX	1	0.50	0	0	0	0	0	0.50	0	1	0.50	scal (12.5%)
AND $-0x62d3a980,%ECX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	scal (6.3%)
XOR %RCX,%RDX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
MOV %RDX,%RCX	1	0	0	0	0	0	0	0	0	0	0.25	scal (12.5%)
SAL $0xf,%RCX	1	0.50	0	0	0	0	0	0.50	0	1	0.50	scal (12.5%)
AND $-0x103a0000,%ECX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	scal (6.3%)
XOR %RCX,%RDX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
MOV %RDX,%RCX	1	0	0	0	0	0	0	0	0	0	0.25	scal (12.5%)
SHR $0x12,%RCX	1	0.50	0	0	0	0	0	0.50	0	1	0.50	scal (12.5%)
XOR %RCX,%RDX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
VCVTUSI2SS %EDX,%XMM1,%XMM0	2	0.50	0.50	0	0	0	1	0	0	6	1	scal (6.3%)
VMULSS 0x23e9(%RIP),%XMM0,%XMM0	1	0.50	0.50	0.50	0.50	0	0	0	0	4	0.50	scal (6.3%)
VCOMISS %XMM0,%XMM3	1	1	0	0	0	0	0	0	0	3	1	scal (6.3%)
JA 1c6d <main+0x92d>	1	0.50	0	0	0	0	0	0.50	0	0	0.50-1	N/A
MOV %RAX,%RDX	1	0	0	0	0	0	0	0	0	0	0.25	N/A
CMP $0x26f,%RAX	1	0.25	0.25	0	0	0	0.25	0.25	0	1	0.25	N/A
JBE 1bc8 <main+0x888>	1	0.50	0	0	0	0	0	0.50	0	0	0.50-1	N/A

Report Configuration

Vectorization

Details

Workaround

CALL instructions

Details

Complex instructions

Details

Slow data structures access

Details

Workaround

Conversion 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

Code clean check

Workaround

Vectorization

Details

Workaround

Execution units bottlenecks

CALL instructions

Details

Complex instructions

Details

Conversion 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

Workaround

Execution units bottlenecks

Complex instructions

Details

Slow data structures access

Details

Workaround

Conversion 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