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Browsing by Author "Pingali, Keshav"
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A Generic Programming System for Sparse Matrix Computations
Mateev, Nikolay; Kotlyar, Vladimir; Pingali, Keshav; Stodghill, Paul (Cornell University, 199907)Sparse matrices are stored in compressed formats in which zeros are not stored explicitly. Writing highperformance sparse matrix libraries is a difficult and tedious job because there are many compressed formats in use ... 
IStructures: Data Structures for Parallel Computing
Arvind; Nikhil, Rishiyur; Pingali, Keshav (Cornell University, 198702)It is difficult simulteneously to achieve elegance, efficiency and parallelism in functional programs that manipulate large data structures. We demonstrate this through careful analysis of program examples using three ... 
The Lambda Loop Transformation Toolkit (User's Reference Manual)
Li, Wei; Pingali, Keshav (Cornell University, 199408)Loop transformations are becoming critical to exploiting parallelism and data locality in parallelizing and optimizing compilers. This document describes the Lambda loop transformation toolkit, an implementation of the ... 
The Lambda Loop Transformation Toolkit (User's Reference Manual)
Li, Wei; Pingali, Keshav (Cornell University, 199406)Loop transformations are becoming critical to exploiting parallelism and data locality in parallelizing and optimizing compilers. This document describes the Lambda loop transformation toolkit, an implementation of the ... 
Lazy Evaluation and the Logic Variable
Pingali, Keshav (Cornell University, 198711)Functional languages can be enriched with logic variables to provide new computational features such as incremental construction of data structures. In this paper, we present a novel application for logic variables that ... 
Leftlooking to Rightlooking and vice versa: An Application of FractalSymbolic Analysis to Linear Algebra Code Restructuring
Mateev, Nikolay; Menon, Vijay; Pingali, Keshav (Cornell University, 20000801)We have recently developed a new program analysis strategy called fractal symbolic analysis that addresses some of limitations of techniques such as dependence analysis. In this paper, we show how fractal symbolic analysis ... 
Man vs. Machine : Comparing Handwritten and Compilergenerated ApplicationLevel Checkpointing
Ezick, James; Marques, Daniel; Pingali, Keshav; Stodghill, Paul (Cornell University, 20041012)The contributions of this paper are the following. We describe the implementation of the $C^3$ system for semiautomatic applicationlevel checkpointing of C programs. The system has (i) a precompiler that instruments C ... 
Optimal Control Dependence Computation and the Roman Chariots Problem
Pingali, Keshav; Bilardi, Gianfranco (Cornell University, 199609)The control dependence relation plays a fundamental role in program restructuring and optimization. The usual representation of this relation is the control dependence graph (CDG), but the size of the CDG can grow ... 
Performance Analysis of the Pipe Problem, a MultiPhysics Simulation Based on Web Services
Stodghill, Paul; Cronin, Rob; Pingali, Keshav; Heber, Gerd (Cornell University, 20040216)The ongoing convergence of grid computing and web services has inspired a number of studies on the use of SOAPbased web services for scientific computing. These studies have exposed several performance problems in ... 
Process Decomposition Through Locality of Reference
Rogers, Anne M.; Pingali, Keshav (Cornell University, 198808)In the context of sequential computers, it is common practice to exploit temporal locality of reference through devices such as caches and virtual memory. In the context of multiprocessors, we believe that it is equally ... 
Register Renaming and Dynamic Speculation: an Alternative Approach
Moudgill, Mayan; Pingali, Keshav; Vassiliadis, Stamatis (Cornell University, 199308)In this paper, we present a novel mechanism that implements register renaming, dynamic speculation and precise interrupts. Renaming of registers is performed during the instruction fetch stage instead of the decode stage, ... 
A Relational Approach to the Compilation of Sparse Matrix Programs
Kotlyar, Vladimir; Pingali, Keshav; Stodghill, Paul (Cornell University, 199703)We present a relational algebra based framework for compiling efficient sparse matrix code from dense DOANY loops and a specification of the representation of the sparse matrix. We present experimental data that demonstrates ... 
A Singular Loop Transformation Framework Based on Nonsingular Matrices
Li, Wei; Pingali, Keshav (Cornell University, 199207)In this paper, we discuss a loop transformation framework that is based on integer nonsingular matrices. The transformations included in this framework are called Atransformations and include permutation, skewing ... 
A Singular Loop Transformation Framework Based on NonSingular Matrices
Li, Wei; Pingali, Keshav (Cornell University, 199207)In this paper, we discuss a loop transformation framework that is based on integer nonsingular matrices. The transformations included in this framework are called $\Lambda$transformations and include permutation, skewing ... 
Solving Alignment using Elementary Linear Algebra
Bau, David; Kodukula, Induprakas; Kotlyar, Vladimir; Pingali, Keshav; Stodghill, Paul (Cornell University, 199501)Data and computation alignment is an important part of compiling sequential programs to architectures with nonuniform memory access times. In this paper, we show that elementary matrix methods can be used to determine ... 
Static Scheduling for Dynamic Dataflow Machines
Beck, Micah; Pingali, Keshav; Nicolau, Alexandru (Cornell University, 198901)Dataflow machines can "unravel" loops automatically so that many iterations of a loop can execute in parallel. Unbounded loop unraveling can strain the resources available on the machine and, in extreme cases, deadlock ... 
Think Globally, Search Locally
Yotov, Kamen; Pingali, Keshav; Stodghill, Paul (Cornell University, 20041104)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 ... 
Tiling Imperfectlynested Loop Nests (REVISED)
Ahmed, Nawaaz; Mateev, Nikolay; Pingali, Keshav (Cornell University, 20000131)Tiling is one of the more important transformations for enhancing locality of reference in programs. Tiling of perfectlynested loop nests (which are loop nests in which all assignment statements are contained in the ... 
Tiling Imperfectlynested Loops
Ahmed, Nawaaz; Mateev, Nikolay; Pingali, Keshav (Cornell University, 199909)Tiling is one of the more important transformations for enhancing locality of reference in programs. Intuitively, tiling a set of loops achieves the effect of interleaving iterations of these loops. Tiling has been applied ... 
Unified framework for sparse and dense SPMD code generation(preliminary report)
Kotlyar, Vladimir; Pingali, Keshav; Stodghill, Paul (Cornell University, 199703)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 ...