Simplifier improvements

This MR started as: allow the simplifer to do more in one pass,
arising from places I could see the simplifier taking two iterations
where one would do.  But it turned into a larger project, because
these changes unexpectedly made inlining blow up, especially join
points in deeply-nested cases.

The main changes are below.  There are also many new or rewritten Notes.

Avoiding simplifying repeatedly
~~~~~~~~~~~~~~~
See Note [Avoiding simplifying repeatedly]

* The SimplEnv now has a seInlineDepth field, which says how deep
  in unfoldings we are.  See Note [Inline depth] in Simplify.Env.
  Currently used only for the next point: avoiding repeatedly
  simplifying coercions.

* Avoid repeatedly simplifying coercions.
  see Note [Avoid re-simplifying coercions] in Simplify.Iteration
  As you'll see from the Note, this makes use of the seInlineDepth.

* Allow Simplify.Iteration.simplAuxBind to inline used-once things.
  This is another part of Note [Post-inline for single-use things], and
  is really good for reducing simplifier iterations in situations like
      case K e of { K x -> blah }
  wher x is used once in blah.

* Make GHC.Core.SimpleOpt.exprIsConApp_maybe do some simple case
  elimination.  Note [Case elim in exprIsConApp_maybe]

* Improve the case-merge transformation:
  - Move the main code to `GHC.Core.Utils.mergeCaseAlts`, to join `filterAlts`
    and friends.  See Note [Merge Nested Cases] in GHC.Core.Utils.
  - Add a new case for `tagToEnum#`; see wrinkle (MC3).
  - Add a new case to look through join points: see wrinkle (MC4)

postInlineUnconditionally
~~~~~~~~~~~~~~~~~~~~~~~~~
* Allow Simplify.Utils.postInlineUnconditionally to inline variables
  that are used exactly once. See Note [Post-inline for single-use things].

* Do not postInlineUnconditionally join point, ever.
  Doing so does not reduce allocation, which is the main point,
  and with join points that are used a lot it can bloat code.
  See point (1) of Note [Duplicating join points] in
  GHC.Core.Opt.Simplify.Iteration.

* Do not postInlineUnconditionally a strict (demanded) binding.
  It will not allocate a thunk (it'll turn into a case instead)
  so again the main point of inlining it doesn't hold.  Better
  to check per-call-site.

* Improve occurrence analyis for bottoming function calls, to help
  postInlineUnconditionally.  See Note [Bottoming function calls]
  in GHC.Core.Opt.OccurAnal

Inlining generally
~~~~~~~~~~~~~~~~~~
* In GHC.Core.Opt.Simplify.Utils.interestingCallContext,
  use RhsCtxt NonRecursive (not BoringCtxt) for a plain-seq case.
  See Note [Seq is boring]  Also, wrinkle (SB1), inline in that
  `seq` context only for INLINE functions (UnfWhen guidance).

* In GHC.Core.Opt.Simplify.Utils.interestingArg,
  - return ValueArg for OtherCon [c1,c2, ...], but
  - return NonTrivArg for OtherCon []
  This makes a function a little less likely to inline if all we
  know is that the argument is evaluated, but nothing else.

* isConLikeUnfolding is no longer true for OtherCon {}.
  This propagates to exprIsConLike.  Con-like-ness has /positive/
  information.

Join points
~~~~~~~~~~~
* Be very careful about inlining join points.
  See these two long Notes
    Note [Duplicating join points] in GHC.Core.Opt.Simplify.Iteration
    Note [Inlining join points] in GHC.Core.Opt.Simplify.Inline

* When making join points, don't do so if the join point is so small
  it will immediately be inlined; check uncondInlineJoin.

* In GHC.Core.Opt.Simplify.Inline.tryUnfolding, improve the inlining
  heuristics for join points. In general we /do not/ want to inline
  join points /even if they are small/.  See Note [Duplicating join points]
  GHC.Core.Opt.Simplify.Iteration.

  But sometimes we do: see Note [Inlining join points] in
  GHC.Core.Opt.Simplify.Inline; and the new `isBetterUnfoldingThan` function.

* Do not add an unfolding to a join point at birth.  This is a tricky one
  and has a long Note [Do not add unfoldings to join points at birth]
  It shows up in two places
  - In `mkDupableAlt` do not add an inlining
  - (trickier) In `simplLetUnfolding` don't add an unfolding for a
    fresh join point
  I am not fully satisifed with this, but it works and is well documented.

* In GHC.Core.Unfold.sizeExpr, make jumps small, so that we don't penalise
  having a non-inlined join point.

Performance changes
~~~~~~~~~~~~~~~~~~~
* Binary sizes fall by around 2.6%, according to nofib.

* Compile times improve slightly. Here are the figures over 1%.

  I investiate the biggest differnce in T18304. It's a very small module, just
  a few hundred nodes. The large percentage difffence is due to a single
  function that didn't quite inline before, and does now, making code size a
  bit bigger.  I decided gains outweighed the losses.

    Metrics: compile_time/bytes allocated (changes over +/- 1%)
    ------------------------------------------------
           CoOpt_Singletons(normal)   -9.2% GOOD
                LargeRecord(normal)  -23.5% GOOD
MultiComponentModulesRecomp(normal)   +1.2%
MultiLayerModulesTH_OneShot(normal)   +4.1%  BAD
                  PmSeriesS(normal)   -3.8%
                  PmSeriesV(normal)   -1.5%
                     T11195(normal)   -1.3%
                     T12227(normal)  -20.4% GOOD
                     T12545(normal)   -3.2%
                     T12707(normal)   -2.1% GOOD
                     T13253(normal)   -1.2%
                 T13253-spj(normal)   +8.1%  BAD
                     T13386(normal)   -3.1% GOOD
                     T14766(normal)   -2.6% GOOD
                     T15164(normal)   -1.4%
                     T15304(normal)   +1.2%
                     T15630(normal)   -8.2%
                    T15630a(normal)          NEW
                     T15703(normal)  -14.7% GOOD
                     T16577(normal)   -2.3% GOOD
                     T17516(normal)  -39.7% GOOD
                     T18140(normal)   +1.2%
                     T18223(normal)  -17.1% GOOD
                     T18282(normal)   -5.0% GOOD
                     T18304(normal)  +10.8%  BAD
                     T18923(normal)   -2.9% GOOD
                      T1969(normal)   +1.0%
                     T19695(normal)   -1.5%
                     T20049(normal)  -12.7% GOOD
                    T21839c(normal)   -4.1% GOOD
                      T3064(normal)   -1.5%
                      T3294(normal)   +1.2%  BAD
                      T4801(normal)   +1.2%
                      T5030(normal)  -15.2% GOOD
                   T5321Fun(normal)   -2.2% GOOD
                      T6048(optasm)  -16.8% GOOD
                       T783(normal)   -1.2%
                      T8095(normal)   -6.0% GOOD
                      T9630(normal)   -4.7% GOOD
                      T9961(normal)   +1.9%  BAD
                      WWRec(normal)   -1.4%
        info_table_map_perf(normal)   -1.3%
                 parsing001(normal)   +1.5%

                          geo. mean   -2.0%
                          minimum    -39.7%
                          maximum    +10.8%

* Runtimes generally improve. In the testsuite perf/should_run gives:
   Metrics: runtime/bytes allocated
   ------------------------------------------
             Conversions(normal)   -0.3%
                 T13536a(optasm)  -41.7% GOOD
                   T4830(normal)   -0.1%
           haddock.Cabal(normal)   -0.1%
            haddock.base(normal)   -0.1%
        haddock.compiler(normal)   -0.1%

                       geo. mean   -0.8%
                       minimum    -41.7%
                       maximum     +0.0%

* For runtime, nofib is a better test.  The news is mostly good.
  Here are the number more than +/- 0.1%:

    # bytes allocated
    ==========================++==========
       imaginary/digits-of-e1 ||  -14.40%
       imaginary/digits-of-e2 ||   -4.41%
          imaginary/paraffins ||   -0.17%
               imaginary/rfib ||   -0.15%
       imaginary/wheel-sieve2 ||   -0.10%
                real/compress ||   -0.47%
                   real/fluid ||   -0.10%
                  real/fulsom ||   +0.14%
                  real/gamteb ||   -1.47%
                      real/gg ||   -0.20%
                   real/infer ||   +0.24%
                     real/pic ||   -0.23%
                  real/prolog ||   -0.36%
                     real/scs ||   -0.46%
                 real/smallpt ||   +4.03%
        shootout/k-nucleotide ||  -20.23%
              shootout/n-body ||   -0.42%
       shootout/spectral-norm ||   -0.13%
              spectral/boyer2 ||   -3.80%
         spectral/constraints ||   -0.27%
          spectral/hartel/ida ||   -0.82%
                spectral/mate ||  -20.34%
                spectral/para ||   +0.46%
             spectral/rewrite ||   +1.30%
              spectral/sphere ||   -0.14%
    ==========================++==========
                    geom mean ||   -0.59%

    real/smallpt has a huge nest of local definitions, and I
    could not pin down a reason for a regression.  But there are
    three big wins!

Metric Decrease:
    CoOpt_Singletons
    LargeRecord
    T12227
    T12707
    T13386
    T13536a
    T14766
    T15703
    T16577
    T17516
    T18223
    T18282
    T18923
    T21839c
    T20049
    T5321Fun
    T5030
    T6048
    T8095
    T9630
    T783
Metric Increase:
    MultiLayerModulesTH_OneShot
    T13253-spj
    T18304
    T18698a
    T9961
    T3294