Search

As part of an effort to design and implement a Fortran compiler on the ILLIAC IV, an extended Fortran, called IVTRAN, has been developed. This language provides a means of expressing data and control structures suitable for exploiting ILLIAC IV parallelism. This paper reviews the hardware characteristics of the nine and singles out unconventiona features which could be expected to influence langluage (and compiler) design. The implications of these features for data layout and algorithm structure are discussed, and the conclusion is drawn that data allocation rather than code structuring is the crucial ILLIAC optimization problem. A satisfactory method of data allocation is then presented. Language structures to utilize this storage method and express parallel algorithms are described. [ABSTRACT FROM AUTHOR]

Ideally, a program written as a composition of concise, self-contained components should perform as well as the equivalent hand-written version where the functionality of what was many components has been manually combined into a monolithic implementation. That is, programmers should not have to sacrifice code clarity or good software engineering practices to obtain performance--we want compositionality without a performance penalty. This work shows how to attain this goal for high-level Haskell in the domain of sequence-processing functions, which includes applications such as array processing. Prior work on stream fusion3 shows how to automatically transform some high-level sequence-processing functions into efficient implementations. It has been used to great effect in Haskell libraries for manipulating byte arrays, Unicode text, and unboxed vectors. However some operations, like vector append, do not perform well within the stream fusion framework. Others, like SIMD computation using the SSE and AVX instructions available on modern x86 chips, do not seem to fit in the stream fusion framework at all. We describe generalized stream fusion, which solves these issues through a careful choice of stream representation. Benchmarks show that high-level Haskell code written using our compiler and libraries can produce code that is faster than both compiler- and hand-vectorized C. [ABSTRACT FROM AUTHOR]

Matrix representations and operations are examined for the purpose of minimizing the page faulting occurring in a paged memory system. It is shown that carefully designed matrix algorithms can lead to enormous savings in the number of page faults occurring when only a small part of the total matrix can be in main memory at one time. Examination of addition, multiplication, and inversion algorithms shows that a partitioned matrix representation (i.e. one submatrix or partition per page) in most cases induced fewer page faults than a row-by-row representation. The number of page-pulls required by these matrix manipulation algorithms is also studied as a function of the number of pages of main memory available to the algorithm. [ABSTRACT FROM AUTHOR]