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Showing 1 to 12 of 12 for “"optimizing compilers"”.
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The formal relationship between direct and continuation-passing style optimizing compilers: A synthesis of two paradigms
Compilers for higher-order programming languages like Scheme, ML, and Lisp can be broadly characterized as either "direct compilers" or "continuation-passing style (CPS) compilers", depending on their main intermediate representation. Our central result is a precise correspondence between the two …
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Automatic Generation and Management of Program Analyses
Designing a program analysis (for use in optimizing compilers) is a time-consuming, complicated process because it involves many parameters. In particular, one must carefully measure the accuracy of the analysis against its cost. To reach an acceptable cost-accuracy balance the designer must …
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Memory disambiguation to facilitate instruction-level parallelism compilation
… the problem of ambiguous memory dependences, optimizing compilers perform memory disambiguation.
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Interactive source-level debugging of globally optimized code with expected behavior
Optimizing compilers and source-level debuggers have become essential for program development. However, their basic premises differ, so it is difficult for them to coexist within a programming environment. The primary purpose of a compiler is to make a program run faster while preserving the …
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Thread Escape Analysis for a Memory Consistency -Aware Compiler
… to prototype different memory models; and optimizing compilers to adapt to different memory models. Among the key analyses required to implement this system are thread escape analysis, i.e. detecting when a referenced object is accessible by more than one thread, synchronization analysis, …
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Collaborative compilation
Modern optimizing compilers use many heuristic solutions that must be tuned empirically. This tuning is usually done "at the factory" using standard benchmarks. However, applications that are not in the benchmark suite will not achieve the best possible performance, because they are not considered …
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Compiler Optimization Techniques for Scheduling and Reducing Overhead
… patterns. Chapter 2 presents an approach of optimizing the address generation of these problems that results in the following: (i) elimination of redundant arithmetic computation by recognizing and exploiting the presence of common sub-expressions across different iterations in stencil codes; …
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Parallel and vector algorithms in nonlinear structural dynamics using the finite element method
… in the finite element method can be exploited. Optimizing compilers are not sufficient for dealing with complications such as data dependencies and are not equipped to recognize opportunities to restructure code to achieve a higher level of concurrency and a consistently efficient vector length. …
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Iterative Schedule Optimization for Parallelization in the Polyhedron Model
… target hardware can deliver to the fullest. Compilers that have the ability to automatically optimize programs for a specific target hardware can be highly useful in this context. Iterative (or search-based) compilation requires little or no prior knowledge and can adapt more easily to …
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Translation validation for compilation verification
Modern optimizing compilers such as LLVM and GCC are huge and complex, and mature releases routinely have uncaught bugs. Beyond harm to software development, the lack of formal correctness guarantees for the compilation process seriously limits the guarantees other software systems can provide, …
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Code Optimization in the Polyhedron Model - Improving the Efficiency of Parallel Loop Nests
A safe basis for automatic loop parallelization is the polyhedron model which represents the iteration domain of a loop nest as a polyhedron in $\mathbb{Z}^n$. However, turning the parallel loop program in the model to efficient code meets with several obstacles, due to which performance may …
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The Challenges of Non-linear Parameters and Variables in Automatic Loop Parallelisation
With the rise of manycore processors, parallelism is becoming a mainstream necessity. Unfortunately, parallel programming is inherently more difficult than sequential programming; therefore, techniques for automatic parallelisation will become indispensable. We aim at extending the well-known …