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kmeans-acfl-Ofast-soa - 2025-07-07 11:47:09 - MAQAO 2025.1.1

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Optimizer

Loop IDAnalysisPenalty Score
Loop 9 - kmeans-acfl-Ofast-soaExecution Time: 75 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 8 - kmeans-acfl-Ofast-soa+Execution Time: 18 % - Vectorization Ratio: 0.00 % - Vector Length Use: 16.07 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+4
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Data Access Issues+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Vectorization Roadblocks+8
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 6 - kmeans-acfl-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.75 %
Loop Computation Issues+6
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Data Access Issues+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12
Vectorization Roadblocks+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12

Strategizer  

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (97.72%)

If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.

[ 4 / 4 ] Threads activity is good

On average, more than 193.10% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 96.55% of time

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (72.99%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (78.55%)

If the time spent in analyzed innermost loops is less than 15%, standard innermost loop optimizations such as vectorisation will have a limited impact on application performances.

[ 4 / 4 ] Affinity is good (99.85%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 0 / 3 ] Too many functions do not use all threads

Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (15.14%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (19.17%) lower than cumulative innermost loop coverage (78.55%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations

BLAS2 calls usually could make a poor cache usage and could benefit from inlining.

[ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions)

Optimizer

Loop IDAnalysisPenalty Score
Loop 9 - kmeans-acfl-Ofast-soaExecution Time: 72 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 8 - kmeans-acfl-Ofast-soa+Execution Time: 19 % - Vectorization Ratio: 0.00 % - Vector Length Use: 16.07 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+4
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Data Access Issues+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Vectorization Roadblocks+8
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 6 - kmeans-acfl-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.75 %
Loop Computation Issues+6
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Data Access Issues+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12
Vectorization Roadblocks+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12

Strategizer  

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (93.42%)

If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.

[ 4 / 4 ] Threads activity is good

On average, more than 364.51% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 91.14% of time

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (70.65%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (75.96%)

If the time spent in analyzed innermost loops is less than 15%, standard innermost loop optimizations such as vectorisation will have a limited impact on application performances.

[ 4 / 4 ] Affinity is good (99.64%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 0 / 3 ] Too many functions do not use all threads

Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (27.68%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (17.46%) lower than cumulative innermost loop coverage (75.96%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations

BLAS2 calls usually could make a poor cache usage and could benefit from inlining.

[ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions)

Optimizer

Loop IDAnalysisPenalty Score
Loop 9 - kmeans-acfl-Ofast-soaExecution Time: 70 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 8 - kmeans-acfl-Ofast-soa+Execution Time: 17 % - Vectorization Ratio: 0.00 % - Vector Length Use: 16.07 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+4
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Data Access Issues+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Vectorization Roadblocks+8
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 6 - kmeans-acfl-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.75 %
Loop Computation Issues+6
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Data Access Issues+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12
Vectorization Roadblocks+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12

Strategizer  

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (85.82%)

If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.

[ 4 / 4 ] Threads activity is good

On average, more than 664.73% of observed threads are actually active

[ 3 / 4 ] CPU activity is below 90% (83.12%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (64.80%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (69.67%)

If the time spent in analyzed innermost loops is less than 15%, standard innermost loop optimizations such as vectorisation will have a limited impact on application performances.

[ 4 / 4 ] Affinity is good (99.33%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 0 / 3 ] Too many functions do not use all threads

Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (34.68%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (16.15%) lower than cumulative innermost loop coverage (69.67%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations

BLAS2 calls usually could make a poor cache usage and could benefit from inlining.

[ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions)

Optimizer

Loop IDAnalysisPenalty Score
Loop 9 - kmeans-acfl-Ofast-soaExecution Time: 64 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 8 - kmeans-acfl-Ofast-soa+Execution Time: 16 % - Vectorization Ratio: 0.00 % - Vector Length Use: 16.07 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+4
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Data Access Issues+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Vectorization Roadblocks+8
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 6 - kmeans-acfl-Ofast-soa+Execution Time: 4 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.75 %
Loop Computation Issues+6
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Data Access Issues+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12
Vectorization Roadblocks+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12

Strategizer  

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (74.22%)

If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.

[ 4 / 4 ] Threads activity is good

On average, more than 1162.30% of observed threads are actually active

[ 3 / 4 ] CPU activity is below 90% (72.68%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (56.13%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (60.32%)

If the time spent in analyzed innermost loops is less than 15%, standard innermost loop optimizations such as vectorisation will have a limited impact on application performances.

[ 4 / 4 ] Affinity is good (98.93%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 0 / 3 ] Too many functions do not use all threads

Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (71.31%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (13.90%) lower than cumulative innermost loop coverage (60.32%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations

BLAS2 calls usually could make a poor cache usage and could benefit from inlining.

[ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions)

Optimizer

Loop IDAnalysisPenalty Score
Loop 9 - kmeans-acfl-Ofast-soaExecution Time: 56 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 8 - kmeans-acfl-Ofast-soa+Execution Time: 13 % - Vectorization Ratio: 0.00 % - Vector Length Use: 16.07 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+4
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Data Access Issues+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Vectorization Roadblocks+8
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 6 - kmeans-acfl-Ofast-soa+Execution Time: 4 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.75 %
Loop Computation Issues+6
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Data Access Issues+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12
Vectorization Roadblocks+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12

Strategizer  

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (58.42%)

If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.

[ 4 / 4 ] Threads activity is good

On average, more than 1984.83% of observed threads are actually active

[ 2 / 4 ] CPU activity is below 90% (62.09%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (44.13%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (47.41%)

If the time spent in analyzed innermost loops is less than 15%, standard innermost loop optimizations such as vectorisation will have a limited impact on application performances.

[ 4 / 4 ] Affinity is good (98.50%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 0 / 3 ] Too many functions do not use all threads

Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (94.52%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (11.00%) lower than cumulative innermost loop coverage (47.41%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations

BLAS2 calls usually could make a poor cache usage and could benefit from inlining.

[ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions)

Optimizer

Loop IDAnalysisPenalty Score
Loop 9 - kmeans-acfl-Ofast-soaExecution Time: 44 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 8 - kmeans-acfl-Ofast-soa+Execution Time: 11 % - Vectorization Ratio: 0.00 % - Vector Length Use: 16.07 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+4
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Data Access Issues+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Vectorization Roadblocks+8
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 6 - kmeans-acfl-Ofast-soa+Execution Time: 3 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.75 %
Loop Computation Issues+6
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Data Access Issues+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12
Vectorization Roadblocks+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12

Strategizer  

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (48.27%)

If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.

[ 4 / 4 ] Threads activity is good

On average, more than 2713.22% of observed threads are actually active

[ 2 / 4 ] CPU activity is below 90% (56.60%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (36.36%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (39.07%)

If the time spent in analyzed innermost loops is less than 15%, standard innermost loop optimizations such as vectorisation will have a limited impact on application performances.

[ 4 / 4 ] Affinity is good (98.28%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 0 / 3 ] Too many functions do not use all threads

Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (79.15%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (9.20%) lower than cumulative innermost loop coverage (39.07%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations

BLAS2 calls usually could make a poor cache usage and could benefit from inlining.

[ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions)

Optimizer

Loop IDAnalysisPenalty Score
Loop 9 - kmeans-acfl-Ofast-soaExecution Time: 36 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 8 - kmeans-acfl-Ofast-soa+Execution Time: 9 % - Vectorization Ratio: 0.00 % - Vector Length Use: 16.07 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+4
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Data Access Issues+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Vectorization Roadblocks+8
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 6 - kmeans-acfl-Ofast-soa+Execution Time: 2 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.75 %
Loop Computation Issues+6
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Data Access Issues+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12
Vectorization Roadblocks+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12

Strategizer  

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (40.85%)

If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.

[ 4 / 4 ] Threads activity is good

On average, more than 3409.79% of observed threads are actually active

[ 2 / 4 ] CPU activity is below 90% (53.36%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (30.87%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (33.17%)

If the time spent in analyzed innermost loops is less than 15%, standard innermost loop optimizations such as vectorisation will have a limited impact on application performances.

[ 4 / 4 ] Affinity is good (98.12%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 0 / 3 ] Too many functions do not use all threads

Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (84.69%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (7.68%) lower than cumulative innermost loop coverage (33.17%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations

BLAS2 calls usually could make a poor cache usage and could benefit from inlining.

[ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions)

Optimizer

Loop IDAnalysisPenalty Score
Loop 9 - kmeans-acfl-Ofast-soaExecution Time: 30 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 8 - kmeans-acfl-Ofast-soa+Execution Time: 7 % - Vectorization Ratio: 0.00 % - Vector Length Use: 16.07 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+4
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Data Access Issues+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Vectorization Roadblocks+8
[SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each.2
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 6 - kmeans-acfl-Ofast-soa+Execution Time: 2 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.75 %
Loop Computation Issues+6
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Data Access Issues+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12
Vectorization Roadblocks+12
[SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each.12
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