30,182 research outputs found
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
The Parma Polyhedra Library: Toward a Complete Set of Numerical Abstractions for the Analysis and Verification of Hardware and Software Systems
Since its inception as a student project in 2001, initially just for the
handling (as the name implies) of convex polyhedra, the Parma Polyhedra Library
has been continuously improved and extended by joining scrupulous research on
the theoretical foundations of (possibly non-convex) numerical abstractions to
a total adherence to the best available practices in software development. Even
though it is still not fully mature and functionally complete, the Parma
Polyhedra Library already offers a combination of functionality, reliability,
usability and performance that is not matched by similar, freely available
libraries. In this paper, we present the main features of the current version
of the library, emphasizing those that distinguish it from other similar
libraries and those that are important for applications in the field of
analysis and verification of hardware and software systems.Comment: 38 pages, 2 figures, 3 listings, 3 table
Automatically Leveraging MapReduce Frameworks for Data-Intensive Applications
MapReduce is a popular programming paradigm for developing large-scale,
data-intensive computation. Many frameworks that implement this paradigm have
recently been developed. To leverage these frameworks, however, developers must
become familiar with their APIs and rewrite existing code. Casper is a new tool
that automatically translates sequential Java programs into the MapReduce
paradigm. Casper identifies potential code fragments to rewrite and translates
them in two steps: (1) Casper uses program synthesis to search for a program
summary (i.e., a functional specification) of each code fragment. The summary
is expressed using a high-level intermediate language resembling the MapReduce
paradigm and verified to be semantically equivalent to the original using a
theorem prover. (2) Casper generates executable code from the summary, using
either the Hadoop, Spark, or Flink API. We evaluated Casper by automatically
converting real-world, sequential Java benchmarks to MapReduce. The resulting
benchmarks perform up to 48.2x faster compared to the original.Comment: 12 pages, additional 4 pages of references and appendi
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