Technique dovetails very naturally with this style of debug info. The variable exposed so that debug info can be attached to it. Needed for debug info generation: Debug information in Variables that only have one assignment point, good heuristics toĪvoid insertion of unneeded phi nodes, etc. For example, it hasįast-paths for variables that are only used in a single block, That bugs are found fast and fixed early.Įxtremely Fast: mem2reg has a number of special cases that make itįast in common cases as well as fully general. As such, the most common clients of LLVMĪre using this to handle a bulk of their variables. Proven and well tested: clang uses this techniqueįor local mutable variables. Unless there is an extremely good reason not to. ![]() ![]() Strongly recommend that you use this technique for building SSA form, Question you may be asking is: should I bother with this nonsense for myįront-end? Wouldn’t it be better if I just did SSA constructionĭirectly, avoiding use of the mem2reg optimization pass? In short, we Languages, and we’ll illustrate it below with Kaleidoscope. More powerful and can promote structs, “unions”, and arrays in manyĪll of these properties are easy to satisfy for most imperative Scalars and vectors), and only if the array size of the allocation isġ (or missing in the. If the address of the stack object is passed to a function, or if anyįunny pointer arithmetic is involved, the alloca will not be Mem2reg only promotes allocas whose uses are direct loads and stores. Being in the entry block guarantees that the alloca is onlyĮxecuted once, which makes analysis simpler. Mem2reg only looks for alloca instructions in the entry block of theįunction. It does not apply to global variables or heap Mem2reg is alloca-driven: it looks for allocas and if it can handle Pass is the answer to dealing with mutable variables, and we highly That speed up (very common) degenerate cases. The mem2reg pass implements the standard “iterated dominance frontier”Īlgorithm for constructing SSA form and has a number of optimizations $ llvm-as < example.ll | opt -passes =mem2reg | = weak global i32 = weak global i32 0īr i1 %Condition, label %cond_true, label %cond_false If you run thisĮxample through the pass, for example, you’ll get: Into SSA registers, inserting Phi nodes as appropriate. Pass named “mem2reg” that handles this case, promoting allocas like this ![]() While this solution has solved our immediate problem, it introducedĪnother one: we have now apparently introduced a lot of stack trafficįor very simple and common operations, a major performance problem.įortunately for us, the LLVM optimizer has a highly-tuned optimization Taking the address of a variable just uses the stack address Variables without the need to create Phi nodes at all:Įach mutable variable becomes a stack allocation.Įach read of the variable becomes a load from the stack.Įach update of the variable becomes a store to the stack. With this, we have discovered a way to handle arbitrary mutable To understand why mutable variables cause complexities in SSAĬonstruction, consider this extremely simple C = weak global i32 0 type of is i32* = weak global i32 0 type of is i32* define i32 ( i1 %Condition ) ![]() Well tested support for this, though the way it works is a bit The short (and happy) summary of this chapter is that there is no needįor your front-end to build SSA form: LLVM provides highly tuned and Nice property and it is often unclear to newcomers how to generate codeįor an imperative language with mutable variables. Since LLVM requires that the input code be in SSA form, this is a very Particular, a functional language makes it very easy to build LLVM IR That it is functional makes it “too easy” to generate LLVM IR for it. While Kaleidoscope is interesting as a functional language, the fact Journey, we learned some parsing techniques, how to build and representĪn AST, how to build LLVM IR, and how to optimize the resultant code as Very respectable, albeit simple, functional programming Welcome to Chapter 7 of the “ Implementing a language with Kaleidoscope: Extending the Language: Mutable Variables ¶Īdjusting Existing Variables for Mutation
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