Run-time parallelization and scheduling of loops

Run time methods are studied to automatically parallelize and schedule iterations of a do loop in certain cases, where compile-time information is inadequate. The methods presented involve execution time preprocessing of the loop. At compile-time, these methods set up the framework for performing a loop dependency analysis. At run time, wave fronts of concurrently executable loop iterations are identified. Using this wavefront information, loop iterations are reordered for increased parallelism. Symbolic transformation rules are used to produce: inspector procedures that perform execution time preprocessing and executors or transformed versions of source code loop structures. These transformed loop structures carry out the calculations planned in the inspector procedures. Performance results are presented from experiments conducted on the Encore Multimax. These results illustrate that run time reordering of loop indices can have a significant impact on performance. Furthermore, the overheads associated with this type of reordering are amortized when the loop is executed several times with the same dependency structure

A Theoretical Approach Involving Recurrence Resolution, Dependence Cycle Statement Ordering and Subroutine Transformation for the Exploitation of Parallelism in Sequential Code.

To exploit parallelism in Fortran code, this dissertation consists of a study of the following three issues: (1) recurrence resolution in Do-loops for vector processing, (2) dependence cycle statement ordering in Do-loops for parallel processing, and (3) sub-routine parallelization. For recurrence resolution, the major findings include: (1) the node splitting algorithm cannot be used directly to break an essential antidependence link, of which the source variable that results in antidependence is itself the sink variable of another true dependence so a correction method is proposed, (2) a sink variable renaming technique is capable of breaking an antidependence and/or output-dependence link, (3) for recurrences formed by only true dependences, a dynamic dependence concept and the derived technique are powerful, and (4) by integrating related techniques, an algorithm for resolving a general multistatement recurrence is developed. The performance of a parallel loop is determined by the level of parallelism and the time delay due to interprocessor communication and synchronization. For a dependence cycle of a single parallel loop executed in a general synchronization mode, the parallelism exposed varies with the alignment of statements. Statements are reordered on the basis of execution-time of the loop as estimated at compile-time. An improved timing formula and a derived statement ordering algorithm are proposed. Further extension of this algorithm to multiple perfectly nested Do-loops with simple global dependence cycle is also presented. The subroutine is a potential source for parallel processing. Several problems must be solved for subroutine parallelization: (1) the precedence of parallel executions of subroutines, (2) identification of the optimum execution mode for each subroutine and (3) the restructuring of a serial program. A five-step approach to parallelize called subroutines for a calling subroutine is proposed: (1) computation of control dependence, (2) approximation of the global effects of subroutines, (3) analysis of data dependence, (4) identification of execution mode, and (5) restructuring of calling and called subroutines. Application of these five steps in a recursive manner to different levels of calling subroutines in a program addresses the parallelization of subroutines

Run-time parallelization and scheduling of loops

The class of problems that can be effectively compiled by parallelizing compilers is discussed. This is accomplished with the doconsider construct which would allow these compilers to parallelize many problems in which substantial loop-level parallelism is available but cannot be detected by standard compile-time analysis. We describe and experimentally analyze mechanisms used to parallelize the work required for these types of loops. In each of these methods, a new loop structure is produced by modifying the loop to be parallelized. We also present the rules by which these loop transformations may be automated in order that they be included in language compilers. The main application area of the research involves problems in scientific computations and engineering. The workload used in our experiment includes a mixture of real problems as well as synthetically generated inputs. From our extensive tests on the Encore Multimax/320, we have reached the conclusion that for the types of workloads we have investigated, self-execution almost always performs better than pre-scheduling. Further, the improvement in performance that accrues as a result of global topological sorting of indices as opposed to the less expensive local sorting, is not very significant in the case of self-execution

An Initial Evaluation of the Tera Multithreaded Architecture and Programming System Using the C3I Parallel Benchmark Suite

The Tera Multithreaded Architecture (MTA) is a radical new architecture intended to revolutionize high-performance computing in both the scientific and commercial marketplaces. Each processor supports 128 threads in hardware. Extremely fast thread switching is used to mask latency in a uniform-access memory system without caching. It is claimed that these hardware characteristics allow compilers to easily transform sequential programs into efficient multithreaded programs for the Tera MTA. In this paper, we attempt to provide an objective initial evaluation of the performance of the Tera multithreaded architecture and programming system for general-purpose applications. The basis of our investigation is two programs from the C3I Parallel Benchmark Suite (C3IPBS). Both these programs have previously been shown to have the potential for large-scale parallelization. We compare the performance of these programs on (i) a fast uniprocessor, (ii) two conventional shared-memory multiprocessors, and (iii) the first installed Tera MTA (at the San Diego Supercomputer Center). On these platforms, we compare the effectiveness of both automatic and manual parallelization

Automatic Parallelization of Database Queries

Although automatic parallelization of conventional language programs is now widely accepted, relatively little emphasis has been placed on automatic parallelization of database query programs (sometimes referred to as “multiple queries” ). In this paper, we discuss the unique problems associated with automatic parallelization of database programs. From this discussion, we derive a complete approach to automatic parallelization of database programs. Beside integrating a number of existing techniques, our approach relies heavily on several new concepts, including the concepts of “algorithm-level” analysis and hybrid static/dynamic scheduling

Gigaflop performance on a CRAY-2: Multitasking a computational fluid dynamics application

The methodology is described for converting a large, long-running applications code that executed on a single processor of a CRAY-2 supercomputer to a version that executed efficiently on multiple processors. Although the conversion of every application is different, a discussion of the types of modification used to achieve gigaflop performance is included to assist others in the parallelization of applications for CRAY computers, especially those that were developed for other computers. An existing application, from the discipline of computational fluid dynamics, that had utilized over 2000 hrs of CPU time on CRAY-2 during the previous year was chosen as a test case to study the effectiveness of multitasking on a CRAY-2. The nature of dominant calculations within the application indicated that a sustained computational rate of 1 billion floating-point operations per second, or 1 gigaflop, might be achieved. The code was first analyzed and modified for optimal performance on a single processor in a batch environment. After optimal performance on a single CPU was achieved, the code was modified to use multiple processors in a dedicated environment. The results of these two efforts were merged into a single code that had a sustained computational rate of over 1 gigaflop on a CRAY-2. Timings and analysis of performance are given for both single- and multiple-processor runs

A Survey on Thread-Level Speculation Techniques

Producción CientíficaThread-Level Speculation (TLS) is a promising technique that allows the parallel execution of sequential code without relying on a prior, compile-time-dependence analysis. In this work, we introduce the technique, present a taxonomy of TLS solutions, and summarize and put into perspective the most relevant advances in this field.MICINN (Spain) and ERDF program of the European Union: HomProg-HetSys project (TIN2014-58876-P), CAPAP-H5 network (TIN2014-53522-REDT), and COST Program Action IC1305: Network for Sustainable Ultrascale Computing (NESUS)