drm/sched: Add some scheduling quality unit tests

To make evaluating different scheduling policies easier (no need for
external benchmarks) and perfectly repeatable, lets add some synthetic
workloads built upon mock scheduler unit test infrastructure.

Focus is on two parallel clients (two threads) submitting different job
patterns and logging their progress and some overall metrics. This is
repeated for both scheduler credit limit 1 and 2.

Example test output:

  Normal and low:
                    pct1 cps1 qd1;  pct2 cps2 qd2
        +     0ms:   0     0    0;   0     0    0
        +   104ms: 100  1240  112; 100  1240  125
        +   209ms: 100     0   99; 100     0  125
        +   313ms: 100     0   86; 100     0  125
        +   419ms: 100     0   73; 100     0  125
        +   524ms: 100     0   60; 100     0  125
        +   628ms: 100     0   47; 100     0  125
        +   731ms: 100     0   34; 100     0  125
        +   836ms: 100     0   21; 100     0  125
        +   939ms: 100     0    8; 100     0  125
        +  1043ms:               ; 100     0  120
        +  1147ms:               ; 100     0  107
        +  1252ms:               ; 100     0   94
        +  1355ms:               ; 100     0   81
        +  1459ms:               ; 100     0   68
        +  1563ms:               ; 100     0   55
        +  1667ms:               ; 100     0   42
        +  1771ms:               ; 100     0   29
        +  1875ms:               ; 100     0   16
        +  1979ms:               ; 100     0    3
    0: prio=normal sync=0 elapsed_ms=1015ms (ideal_ms=1000ms) cycle_time(min,avg,max)=134,222,978 us latency_time(min,avg,max)=134,222,978
us
    1: prio=low sync=0 elapsed_ms=2009ms (ideal_ms=1000ms) cycle_time(min,avg,max)=134,215,806 us latency_time(min,avg,max)=134,215,806 us

There we have two clients represented in the two respective columns, with
their progress logged roughly every 100 milliseconds. The metrics are:

 - pct - Percentage progress of the job submit part
 - cps - Cycles per second
 - qd  - Queue depth - number of submitted unfinished jobs

The cycles per second metric is inherent to the fact that workload
patterns are a data driven cycling sequence of:

 - Submit 1..N jobs
 - Wait for Nth job to finish (optional)
 - Sleep (optional)
 - Repeat from start

In this particular example we have a normal priority and a low priority
client both spamming the scheduler with 8ms jobs with no sync and no
sleeping. Hence they build very deep queues and we can see how the low
priority client is completely starved until the normal finishes.

Note that the PCT and CPS metrics are irrelevant for "unsync" clients
since they manage to complete all of their cycles instantaneously.

A different example would be:

  Heavy and interactive:
                    pct1 cps1 qd1;  pct2 cps2 qd2
        +     0ms:   0     0    0;   0     0    0
        +   106ms:   5    40    3;   5    40    0
        +   209ms:   9    40    0;   9    40    0
        +   314ms:  14    50    3;  14    50    0
        +   417ms:  18    40    0;  18    40    0
        +   522ms:  23    50    3;  23    50    0
        +   625ms:  27    40    0;  27    40    1
        +   729ms:  32    50    0;  32    50    0
        +   833ms:  36    40    1;  36    40    0
        +   937ms:  40    40    0;  40    40    0
        +  1041ms:  45    50    0;  45    50    0
        +  1146ms:  49    40    1;  49    40    1
        +  1249ms:  54    50    0;  54    50    0
        +  1353ms:  58    40    1;  58    40    0
        +  1457ms:  62    40    0;  62    40    1
        +  1561ms:  67    50    0;  67    50    0
        +  1665ms:  71    40    1;  71    40    0
        +  1772ms:  76    50    0;  76    50    0
        +  1877ms:  80    40    1;  80    40    0
        +  1981ms:  84    40    0;  84    40    0
        +  2085ms:  89    50    0;  89    50    0
        +  2189ms:  93    40    1;  93    40    0
        +  2293ms:  97    40    0;  97    40    1

In this case client one is submitting 3x 2.5ms jobs, waiting for the 3rd
and then sleeping for 2.5ms (in effect causing 75% GPU load, minus the
overheads). Second client is submitting 1ms jobs, waiting for each to
finish and sleeping for 9ms (effective 10% GPU load). Here we can see
the PCT and CPS reflecting real progress.

Signed-off-by: Tvrtko Ursulin <tvrtko.ursulin@igalia.com>
Cc: Christian König <christian.koenig@amd.com>
Cc: Danilo Krummrich <dakr@kernel.org>
Cc: Matthew Brost <matthew.brost@intel.com>
Cc: Philipp Stanner <phasta@kernel.org>
Cc: Pierre-Eric Pelloux-Prayer <pierre-eric.pelloux-prayer@amd.com>
Acked-by: Christian König <christian.koenig@amd.com>
Acked-by: Danilo Krummrich <dakr@kernel.org>
Tested-by: Vitaly Prosyak <vitaly.prosyak@amd.com>
Signed-off-by: Philipp Stanner <phasta@kernel.org>
Link: https://patch.msgid.link/20260417103744.76020-5-tvrtko.ursulin@igalia.com

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