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kmeans-gcc-Ofast-soa - 2025-07-07 11:15:38 - MAQAO 2025.1.1

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Optimizer

Loop IDAnalysisPenalty Score
Loop 4 - kmeans-gcc-Ofast-soaExecution Time: 82 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 5 - kmeans-gcc-Ofast-soa+Execution Time: 11 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.43 %
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+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+6
[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 12 - kmeans-gcc-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.59 %
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 (99.99%)

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 189.08% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 94.55% of time

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (82.85%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (88.35%)

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 (99.75%)

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 (10.41%). 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 (11.64%) lower than cumulative innermost loop coverage (88.35%)

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 4 - kmeans-gcc-Ofast-soaExecution Time: 82 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 5 - kmeans-gcc-Ofast-soa+Execution Time: 11 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.43 %
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+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+6
[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 12 - kmeans-gcc-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.59 %
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 (99.99%)

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 339.68% of observed threads are actually active

[ 3 / 4 ] CPU activity is below 90% (84.93%)

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% (83.08%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (88.63%)

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 (99.34%)

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 (18.84%). 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 (11.36%) lower than cumulative innermost loop coverage (88.63%)

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 4 - kmeans-gcc-Ofast-soaExecution Time: 83 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 5 - kmeans-gcc-Ofast-soa+Execution Time: 11 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.43 %
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+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+6
[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 12 - kmeans-gcc-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.59 %
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 (99.96%)

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 573.75% of observed threads are actually active

[ 3 / 4 ] CPU activity is below 90% (71.74%)

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% (83.16%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (88.67%)

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 (98.75%)

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 (31.69%). 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 (11.29%) lower than cumulative innermost loop coverage (88.67%)

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 4 - kmeans-gcc-Ofast-soaExecution Time: 83 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 5 - kmeans-gcc-Ofast-soa+Execution Time: 11 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.43 %
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+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+6
[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 12 - kmeans-gcc-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.59 %
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 (99.94%)

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 865.01% of observed threads are actually active

[ 2 / 4 ] CPU activity is below 90% (54.08%)

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% (83.07%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (88.60%)

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 (97.95%)

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 (48.00%). 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 (11.33%) lower than cumulative innermost loop coverage (88.60%)

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 4 - kmeans-gcc-Ofast-soaExecution Time: 83 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 5 - kmeans-gcc-Ofast-soa+Execution Time: 11 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.43 %
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+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+6
[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 12 - kmeans-gcc-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.59 %
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 (99.91%)

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 1175.61% of observed threads are actually active

[ 1 / 4 ] CPU activity is below 90% (36.76%)

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% (82.85%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (88.35%)

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 (97.19%)

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 (64.74%). 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 (11.57%) lower than cumulative innermost loop coverage (88.35%)

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 4 - kmeans-gcc-Ofast-soaExecution Time: 82 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 5 - kmeans-gcc-Ofast-soa+Execution Time: 11 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.43 %
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+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+6
[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 12 - kmeans-gcc-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.59 %
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 (99.79%)

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 1325.08% of observed threads are actually active

[ 0 / 4 ] CPU activity is below 90% (27.63%)

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% (83.04%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (88.54%)

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 (96.77%)

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 (73.17%). 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 (11.25%) lower than cumulative innermost loop coverage (88.54%)

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 4 - kmeans-gcc-Ofast-soaExecution Time: 83 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 5 - kmeans-gcc-Ofast-soa+Execution Time: 11 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.43 %
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+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+6
[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 12 - kmeans-gcc-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.59 %
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 (99.77%)

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 1417.22% of observed threads are actually active

[ 0 / 4 ] CPU activity is below 90% (22.17%)

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% (82.97%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (88.47%)

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 (96.47%)

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 (78.33%). 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 (11.29%) lower than cumulative innermost loop coverage (88.47%)

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 4 - kmeans-gcc-Ofast-soaExecution Time: 82 % - Vectorization Ratio: 0.00 % - Vector Length Use: 23.61 %
Loop 5 - kmeans-gcc-Ofast-soa+Execution Time: 11 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.43 %
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+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+6
[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 12 - kmeans-gcc-Ofast-soa+Execution Time: 5 % - Vectorization Ratio: 0.00 % - Vector Length Use: 21.59 %
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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