Improve JIT loop optimizations (.NET 6)

[BruceForstall]

RyuJIT has several loop optimization phases that have various issues (both correctness and performance) and can be significantly improved. RyuJIT also lacks some loop optimizations that have been shown to benefit various use cases. For .NET 6 the
proposed work is fixing and improving the existing phases and collecting information and developing a plan for adding
the missing phases.

Existing Optimizations

Below is a list of the existing loop-related RyuJIT phases and a short description of the improvement opportunities.

Loop Recognition

RyuJIT currently has lexical-based loop recognition and only recognizes natural loops. We should consider replacing it with a standard Tarjan SCC algorithm that classifies all loops. Then we can extend some loop optimizations to also work on non-natural loops.

Even if we continue to use the current algorithm, we should verify that it catches the maximal set of natural loops; it is believed that it misses some natural loops.

• Certain loops do not get recorded in optLoopTable #43713 Describes two cases where loops are missed due to various issues.

Loop Inversion

"While" loops are transformed to "do-while" loops to save one branch in the loop. Some issues have been identified with
heuristics for this optimization.

• JIT: heuristics in optInvertWhileLoop may be overly conservative #6569 JIT: heuristics in fgOptWhileLoop may be overly conservative
• Iterating with ForEach over ImmutableArray is slower than over Array #780 The issue contains a link to a prototype tweaking the heuristics and some code size numbers and analysis
• Improve loop inversion #52347 Improve cases where the loop condition block (the entry block) has multiple non-loop predecessors.

Loop Cloning

This optimization creates two copies of a loop: one with bounds checks and one without bounds checks and executes one of them at runtime based on some condition. Several issues have been identified with this optimizations. One recurring theme is unnecessary loop cloning where we first clone a loop and then eliminate range checks from both copies.

• RyuJIT's loop cloning optimization has questionable CQ #4929 RyuJIT's loop cloning optimization has questionable CQ
• JIT: examples where loop cloning is not useful #8558 JIT: examples where loop cloning is not useful
• Poor loop optimization in BilinearInterpol benchmark #31831 Poor loop optimization in BilinearInterpol benchmark
• LoopCloneContext::EvaluateConditions need to evaluate for const init, limit condition.  #10314 LoopCloneContext::EvaluateConditions need to evaluate for const init, limit condition.
• [Mostly done] loop cloning and pgo #48850 loop cloning and pgo. Remaining: use PGO data to influence cost/benefit analysis of deciding to clone a loop.
• If compReturnBB is unreachable we should remove it #48740 (comment) Poor tracking of return blocks impacts loop cloning
• [Stretch goal] Support loop cloning with struct arrays #48897 Support loop cloning with struct arrays
• Consider hoisting of class init checks for loop cloning and inversion #49102 Consider hoisting of class init checks for loop cloning and inversion

Loop Unrolling

The existing phase only does full unrolls, and only for SIMD loops: current heuristic is that the loop bounds test must be a SIMD element count. The impact of the optimization is currently very limited but in general it's a high-impact optimization with the right heuristics.

• Loop unrolling support in RyuJIT #4248 Loop unrolling support in RyuJIT
• JIT optimization: loop unrolling #8107 JIT optimization: loop unrolling
• Loop Unrolling is not Enabled in Release Build #41063 Loop Unrolling is not Enabled in Release Build

Loop Invariant Code Hoisting

This phase attempts to hoist code that will produce the same value on each iteration of the loop to the pre-header. There is
at least one (and likely more) correctness issue:

• JIT: Loop hoisting re-ordering exceptions #6639 JIT: Loop hoisting re-ordering exceptions

And multiple issues about limitations of the algorithm:

• JIT: limitations in hoisting (loop invariant code motion) #35735 JIT: limitations in hoisting (loop invariant code motion)
• JIT: Loop hoisting inhibited by phase-ordering issue #6554 JIT: Loop hoisting inhibited by phase-ordering issue
• RyuJIT: Loop hoist invariant struct field accesses #7265 RyuJIT: Loop hoist invariant struct field accesses
• RyuJIT: missed opportunity for LICM #6666 RyuJIT: missed opportunity for LICM

Loop optimization hygiene

Loop optimizations need to work well with the rest of the compiler phases and IR invariants, such as with PGO.

• [Mostly done] Loop opts should not be recomputing pred lists from scratch #49030 Loop opts should not be recomputing pred lists from scratch. Remaining phases to fix: optFindNaturalLoops, optUnrollLoops, fgInsertGCPolls.

Missing Optimizations

Several major optimizations are missing even though we have evidence of their effectiveness (at least on microbenchmarks).

Induction Variable Widening

Induction variable widening eliminates unnecessary widening converts from int32 sized induction variables to int64 size address mode register uses. On AMD64, this eliminates unnecessary movsxd instructions prior to array dereferencing.

• RyuJIT: Index Variable Widening optimization for array accesses #7312 RyuJIT: Index Variable Widening optimization for array accesses

Strength Reduction

Strength reduction replaces expensive operations with equivalent but less expensive operations.

• Strength reduction for add operations performed power of 2 times #34938 Strength reduction for add operations performed power of 2 times
• ARM64: loop array indexing inefficiencies #34810 ARM64: loop array indexing inefficiencies

Loop Unswitching

Loop unswitching moves a conditional from inside a loop to outside of it by duplicating the loop's body, and placing a version of the loop inside each of the if and else clauses of the conditional. It has elements of both Loop Cloning and Loop Invariant Code Motion.

Loop Interchange

Loop interchange swaps an inner and outer loop to provide follow-on optimization opportunities.

• JIT: loop interchange optimization #4358 JIT: loop interchange optimization

Benefits

It's easy to show the benefit of improved loop optimizations on microbenchmarks. For example, the team has done analysis of JIT microbenchmarks (benchstones, SciMark, etc.) several years ago. The analysis contains estimates of perf improvement from several of these optimizations (each is low single digit %). Real code is also likely to have hot loops that will benefit from improved loop optimizations.

The benchmarks and other metrics we will measure to show the benefits is TBD.

Proposed work

• Do analysis of hot loops in important workloads (ASP.NET, etc.)
• Use the findings along with the existing microbenchmark analysis to prioritize loop optimizations work
• Fix the known issues in the existing loop optimizations starting with the more impactful ones as determined by the previous two items.
  • Determine if current loop recognition and loop structure representation needs to be revamped to be more general and allow for more powerful optimizations.
  • Recommend starting with Loop Cloning and Loop Invariant Code Hoisting as there are well-understood weaknesses and improvement opportunities in those phases.
• Evaluate the use of SSA in loop optimizations. Perhaps a better representation of heap locations in SSA will make it more useful for loop optimizations.
• Create a plan for adding missing optimizations

category:planning
theme:loop-opt
skill-level:expert
cost:large

[BruceForstall]

fyi @dotnet/jit-contrib

[EgorBo]

Some candidates for "Missing optimizations" section:

1. Elimination of loops with empty bodys (probably covered by Induction Variable)
2. Loop vectorization (relies on Loop Unrolling)
3. Loop Idiom Recognition - some loops can be folded into memset/memcpy/popcount (gc pauses?)
   e.g. currently in Mono-LLVM the following C# code:

    static void Foo3(byte* array, int len, byte val)
    {
        for (int i = 0; i < len; i++)
            array[i] = val;
    }

is folded into:

    call void @llvm.memset.p0i8.i64(i8* %array, i8 %val, i64 %len, i32 1, i1 false)

4. Reverse loops, see godbolt: https://godbolt.org/z/3xPqxc

Also, really enjoyed this one:

Here GVN has figured out that loading a[i] is unnecessary because a[i + 1] from one loop iteration can be forwarded to the next iteration as a[i].

for:

bool is_sorted(int *a, int n) {
  for (int i = 0; i < n - 1; i++)
    if (a[i] > a[i + 1])
      return false;
  return true;
}

(c) https://blog.regehr.org/archives/1603

[am11]

An induction analysis case from this thread https://news.ycombinator.com/item?id=13182726:

int X (int num) {
    int a = 0;
    for (int x = 0; x < num; x += 2) {
        if (x % 2 != 0) {
            a += x;
        }
    }
    return a;
}

where gcc and clang with -O2 produce:

X(int): # @X(int)
xor eax, eax
ret

The key analysis going on here is called scalar evolution (SCEV) in the LLVM community. It is basically just a stronger symbolic induction variable analysis than what is normally needed for traditional loop optimizations. In this case SCEV identifies that "x" starts at 0, increments to num by 2, and is even. It also knows that "a" is a reduction of x. The calculus to simplify this is actually straightforward based on that symbolic information.

[EgorBo]

An induction analysis case from this thread https://news.ycombinator.com/item?id=13182726:

Reminds me an issue we had in dotnet/performance repo where LLVM managed to fold the whole benchmark into xor eax, eax :D https://godbolt.org/z/qffPv8 and here is the fix for that benchmark: https://github.com/dotnet/performance/pull/960/files