Dope vector

Abstract: Systems and methods are provided for writing code to access data arrays. One aspect provides a method of accessing a memory array. Data is provided within a one-dimensional array of allocated memory. A dimensional dynamic overlay is declared from within a block of statements, and the declaration initializes various attributes within an array attribute storage object. The data is accessed from within the block of statements as a dimensional indexed array using the array attribute storage object. Another aspect provides a method of creating and accessing a dimensional dynamic array. A dimensional dynamic array is declared from within a block of statements, and memory storage for the array is dynamically allocated. A dynamic overlay storage object is also provided and its attributes are initialized from the dynamic array declaration. The data is accessed as a dimensional indexed array from within the block of statements using the array attribute storage object.

Abstract: —An overview of the ILLIAC IV system is given and its software plans are discussed.

Abstract: The design of specialized processing array architectures, capable of executing any given arbitrary algorithm, is proposed. An approach is adopted in which the algorithm is first represented in the form of a dataflow graph and then mapped onto the specialized processor array. The processors in this array execute the operations included in the corresponding nodes (or subsets of nodes) of the dataflow graph, while regular interconnections of these elements serve as edges of the graph. To speed up the execution, the proposed array allows the generation of computation fronts and their cancellation at a later time, depending on the arriving data operands; thus it is called a data-driven array. The structure of the basic cell and its programming are examined. Some design details are presented for two selected blocks, the instruction memory and the flag array. A scheme for mapping a dataflow graph (program) onto a hexagonally connected array is described and analyzed. Two distinct performance measures-mapping efficiency and array utilization-and some performance results are discussed. >

Abstract: A number of existing compiler techniques hinge on the analysis of array accesses in a program. The most important task in array access analysis is to collect the information about array accesses of interest and summarize it in some standard form. Traditional forms used in array access analysis are sensitive to the complexity of array subscripts; that is, they are usually quite accurate and efficient for simple array subscripting expressions, but lose accuracy or require potentially expensive algorithms for complex subscripts. Our study has revealed that in many programs, particularly numerical applications, many access patterns are simple in nature even when the subscripting expressions are complex. Based on this analysis, we have developed a new, general array region representational form, called the linear memory access descriptor (LMAD). The key idea of the LMAD is to relate all memory accesses to the linear machine memory rather than to the shape of the logical data structures of a programming language. This form helps us expose the simplicity of the actual patterns of array accesses in memory, which may be hidden by complex array subscript expressions. Our recent experimental studies show that our new representation simplifies array access analysis and, thus, enables efficient and accurate compiler analysis.