By Samuel P. Midkiff
Compiling for parallelism is a longstanding subject of compiler learn. This e-book describes the elemental ideas of compiling "regular" numerical courses for parallelism. we start with a proof of analyses that permit a compiler to appreciate the interplay of knowledge reads and writes in numerous statements and loop iterations in the course of application execution. those analyses contain dependence research, use-def research and pointer research. subsequent, we describe how the result of those analyses are used to permit alterations that make loops extra amenable to parallelization, and talk about adjustments that disclose parallelism to focus on shared reminiscence multicore and vector processors. We then talk about a few difficulties that come up whilst parallelizing courses for execution on dispensed reminiscence machines. eventually, we finish with an outline of fixing Diophantine equations and proposals for extra readings within the issues of this e-book to permit the reader to delve deeper into the sphere.
desk of Contents: advent and evaluate / Dependence research, dependence graphs and alias research / software parallelization / ameliorations to switch and do away with dependences / Transformation of iterative and recursive constructs / Compiling for allotted reminiscence machines / fixing Diophantine equations / A advisor to additional studying
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Additional info for Automatic Parallelization: An Overview of Fundamental Compiler Techniques
1. DATAFLOW ANALYSIS 25 insensitive analysis all call sites share summary IN information. Similar precision/speed trade-offs exist as with the flow sensitive and insensitive analyses. A work queue is typically used to implement a dataflow algorithm. The first node of the function is placed into the queue. Until the queue is empty, the algorithm removes a node from the queue. The IN set is computed from the predecessor node’s OUT sets, and the transfer function is evaluated. If the OUT set of the node being processed changes, its successor nodes are placed into the work queue.
In [181, 182] it is claimed that in all situations where other dependence tests based on Fourier-Motzkin elimination and simpler analyses are accurate, the Omega test is sufficiently fast, especially when a careful implementation is done. Using hybrid analysis, described in , conditions that lead to dependence not being disproved are identified, and tested at run time. Consider the pair of references a[i] and a[i + N]. , no dependence that crosses iterations of a loop. If N > 0 the dependence source is a[i] and its sink is a[i + N].
Tracing the corresponding conflict orientations on the conflict graph yields a cycle. An important result of  is that enforcing all program edges involved in these cycles will prevent the invalid orientations from occurring at run time, and will prevent invalid executions. 6. DEPENDENCE ANALYSIS IN PARALLEL PROGRAMS 45 Thus, the program edges involved in cycles can be thought of as dependences in the explicitly parallel program. X = Y = 0; cobegin X = 1; Y = 1; // z = Y; w = X; // …= z; …= w; end cobegin (a) A program whose conflict graph has minimal and non-minimal mixed cycles.