Now showing items 8-17 of 17

    • A Generic Programming System for Sparse Matrix Computations 

      Mateev, Nikolay; Kotlyar, Vladimir; Pingali, Keshav; Stodghill, Paul (Cornell University, 1999-07)
      Sparse matrices are stored in compressed formats in which zeros are not stored explicitly. Writing high-performance sparse matrix libraries is a difficult and tedious job because there are many compressed formats in use ...
    • A Generic Programming System for Sparse Matrix Computations (REVISED) 

      Nikolay Mateev, Vladimir Kotlyar, Keshav Pingali; Stodghill, Paul (Cornell University, 1999-08)
      Sparse matrices are stored in compressed formats in which zeros are not stored explicitly. Writing high-performance sparse matrix libraries is a difficult and tedious job because there are many compressed formats in use ...
    • Man vs. Machine : Comparing Handwritten and Compiler-generated Application-Level Checkpointing 

      Ezick, James; Marques, Daniel; Pingali, Keshav; Stodghill, Paul (Cornell University, 2004-10-12)
      The contributions of this paper are the following. We describe the implementation of the $C^3$ system for semi-automatic application-level checkpointing of C programs. The system has (i) a pre-compiler that instruments C ...
    • Performance Analysis of the Pipe Problem, a Multi-Physics Simulation Based on Web Services 

      Stodghill, Paul; Cronin, Rob; Pingali, Keshav; Heber, Gerd (Cornell University, 2004-02-16)
      The ongoing convergence of grid computing and web services has inspired a number of studies on the use of SOAP-based web services for scientific computing. These studies have exposed several performance problems in ...
    • A Relational Approach to the Automatic Generation of Sequential SparseMatrix Codes 

      Stodghill, Paul (Cornell University, 1997-07)
      This thesis presents techniques for automatically generating sparse codes from dense matrix algorithms through a process called \emph{sparse compilation}. We will start by recognizing that sparse computations are ubiquitous ...
    • A Relational Approach to the Compilation of Sparse Matrix Programs 

      Kotlyar, Vladimir; Pingali, Keshav; Stodghill, Paul (Cornell University, 1997-03)
      We present a relational algebra based framework for compiling efficient sparse matrix code from dense DO-ANY loops and a specification of the representation of the sparse matrix. We present experimental data that demonstrates ...
    • Solving Alignment using Elementary Linear Algebra 

      Bau, David; Kodukula, Induprakas; Kotlyar, Vladimir; Pingali, Keshav; Stodghill, Paul (Cornell University, 1995-01)
      Data and computation alignment is an important part of compiling sequential programs to architectures with non-uniform memory access times. In this paper, we show that elementary matrix methods can be used to determine ...
    • Think Globally, Search Locally 

      Yotov, Kamen; Pingali, Keshav; Stodghill, Paul (Cornell University, 2004-11-04)
      A key step in program optimization is the determination of optimal values for code optimization parameters such as cache tile sizes and loop unrolling factors. One approach, which is implemented in most compilers, is to ...
    • Unified framework for sparse and dense SPMD code generation(preliminary report) 

      Kotlyar, Vladimir; Pingali, Keshav; Stodghill, Paul (Cornell University, 1997-03)
      We describe a novel approach to sparse {\em and} dense SPMD code generation: we view arrays (sparse and dense) as distributed relations and parallel loop execution as distributed relational query evaluation. This approach ...
    • X-Ray : Automatic Measurement of Hardware Parameters 

      Yotov, Kamen; Pingali, Keshav; Stodghill, Paul (Cornell University, 2004-10-06)
      There is growing interest in autonomic, self-tuning software that can optimize itself on new platforms, without manual intervention. Optimization requires detailed knowledge of the target platform such as the latency and ...