On the Complexity of Spill Everywhere under SSA Form

Compilation for embedded processors can be either aggressive (time consuming cross-compilation) or just in time (embedded and usually dynamic). The heuristics used in dynamic compilation are highly constrained by limited resources, time and memory in particular. Recent results on the SSA form open promising directions for the design of new register allocation heuristics for embedded systems and especially for embedded compilation. In particular, heuristics based on tree scan with two separated phases -- one for spilling, then one for coloring/coalescing -- seem good candidates for designing memory-friendly, fast, and competitive register allocators. Still, also because of the side effect on power consumption, the minimization of loads and stores overhead (spilling problem) is an important issue. This paper provides an exhaustive study of the complexity of the ``spill everywhere'' problem in the context of the SSA form. Unfortunately, conversely to our initial hopes, many of the questions we raised lead to NP-completeness results. We identify some polynomial cases but that are impractical in JIT context. Nevertheless, they can give hints to simplify formulations for the design of aggressive allocators.Comment: 10 page

Parallel Copy Motion

International audienceRecent results on the static single assignment (SSA) form open promising directions for the design of new register allocation heuristics for just-in-time (JIT) compilation. In particular, heuris- tics based on tree scans with two decoupled phases, one for spilling, one for splitting/coloring/coalescing, seem good candidates for de- signing memory-friendly, fast, and competitive register allocators. Another class of register allocators, well-suited for JIT compilation, are those based on linear scans. Most of them perform coalesc- ing poorly but also do live-range splitting (mostly on control-flow edges) to avoid spilling. This leads to a large amount of register-to- register copies inside basic blocks but also, implicitly, on critical edges, i.e., edges that flow from a block with several successors to a block with several predecessors. This paper presents a new back-end optimization that we call parallel copy motion. The technique is to move copy instructions in a register-allocated code from a program point, possibly an edge, to another. In contrast with a classical scheduler that must preserve data dependences, our copy motion also permutes register assign- ments so that a copy can "traverse" all instructions of a basic block, except those with conflicting register constraints. Thus, parallel copies can be placed either where the scheduling has some empty slots (for multiple-issues architectures), or where fewer copies are necessary because some variables are dead at this point. Moreover, to the cost of some code compensations (namely, the reverse of the copy), a copy can also be moved out from a critical edge. This pro- vides a simple solution to avoid critical-edge splitting, especially useful when the compiler cannot split it, as it is the case for abnor- mal edges. This compensation technique also enables the schedul- ing/motion of the copy in the successor or predecessor basic block. Experiments with the SPECint benchmarks suite and our own benchmark suite show that we can now apply broadly an SSA-based register allocator: all procedures, even with abnormal edges, can be treated. Simple strategies for moving copies from edges and locally inside basic block show significant average improvements (4% for SPECint and 3% for our suite), with no degradation. It let us believe that the approach is promising, and not only for improving coalescing in fast register allocators

Revisiting Out-of-SSA Translation for Correctness, Code Quality, and Efficiency

Compared to the previous versions, the only change is correcting an awful typo that made Algorithm 1 wrong. Line 18 is not "if b = loc(pred(b))" but simply "if b = loc(b)".Static single assignment (SSA) form is an intermediate program representation in which many code optimizations can be performed with fast and easy-to-implement algorithms. However, some of these optimizations create situations where the SSA variables arising from the same original variable now have overlapping live ranges. This complicates the translation out of SSA code into standard code. There are three issues to consider: correctness, code quality (elimination of copies), and algorithm efficiency (speed and memory footprint). Briggs et al. proposed patches to correct the initial approach of Cytron et al. A cleaner and more general approach was proposed by Sreedhar et al., along with techniques to reduce the number of generated copies. We propose a new approach based on coalescing and a precise view of interferences, in which correctness and optimizations are separated. Our approach is provably correct and simpler to implement, with no patches or particular cases as in previous solutions, while reducing the number of generated copies. Also, experiments with SPEC CINT2000 show that it is 2x faster and 10x less memory-consuming than the Method~III of Sreedhar et al., which makes it suitable for just-in-time compilation

Optimistic chordal coloring: a coalescing heuristic forSSAform programs

The interference graph for a procedure in Static Single Assignment (SSA) Form is chordal. Since the k-colorability problem can be solved in polynomial-time for chordal graphs, this result has generated interest in SSA-based heuristics for spilling and coalescing. Since copies can be folded during SSA construction, instances of the coalescing problem under SSA have fewer affinities than traditional methods. This paper presents Optimistic Chordal Coloring (OCC), a coalescing heuristic for chordal graphs. OCC was evaluated on interference graphs from embedded/multimedia benchmarks: in all cases, OCC found the optimal solution, and ran, on average, 2.30× faster than Iterated Register Coalescin

Survey on Combinatorial Register Allocation and Instruction Scheduling

Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the last three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time. This paper provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization

A formally verified compiler back-end

This article describes the development and formal verification (proof of semantic preservation) of a compiler back-end from Cminor (a simple imperative intermediate language) to PowerPC assembly code, using the Coq proof assistant both for programming the compiler and for proving its correctness. Such a verified compiler is useful in the context of formal methods applied to the certification of critical software: the verification of the compiler guarantees that the safety properties proved on the source code hold for the executable compiled code as well