Nothing Special   »   [go: up one dir, main page]

Kandemir et al., 2002 - Google Patents

An i/o-conscious tiling strategy for disk-resident data sets

Kandemir et al., 2002

View PDF
Document ID
3588216642941172095
Author
Kandemir M
Choudhary A
Ramanujam J
Publication year
Publication venue
The Journal of Supercomputing

External Links

Snippet

This paper describes a tiling technique that can be used by application programmers and optimizing compilers to obtain I/O-efficient versions of regular scientific loop nests. Due to the particular characteristics of I/O operations, a straightforward extension of the traditional …
Continue reading at users.eecs.northwestern.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/40—Transformations of program code
    • G06F8/41—Compilation
    • G06F8/44—Encoding
    • G06F8/443—Optimisation
    • G06F8/4441—Reducing the execution time required by the program code
    • G06F8/4442—Reducing the number of cache misses; Data prefetching
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/40—Transformations of program code
    • G06F8/41—Compilation
    • G06F8/45—Exploiting coarse grain parallelism in compilation, i.e. parallelism between groups of instructions
    • G06F8/456—Parallelism detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/40—Transformations of program code
    • G06F8/41—Compilation
    • G06F8/45—Exploiting coarse grain parallelism in compilation, i.e. parallelism between groups of instructions
    • G06F8/451—Code distribution
    • G06F8/452—Loops
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/30—Arrangements for executing machine-instructions, e.g. instruction decode
    • G06F9/34—Addressing or accessing the instruction operand or the result; Formation of operand address; Addressing modes
    • G06F9/345—Addressing or accessing the instruction operand or the result; Formation of operand address; Addressing modes of multiple operands or results
    • G06F9/3455—Addressing or accessing the instruction operand or the result; Formation of operand address; Addressing modes of multiple operands or results using stride
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/30—Arrangements for executing machine-instructions, e.g. instruction decode
    • G06F9/38—Concurrent instruction execution, e.g. pipeline, look ahead
    • G06F9/3824—Operand accessing
    • G06F9/383—Operand prefetching
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/30—Arrangements for executing machine-instructions, e.g. instruction decode
    • G06F9/30003—Arrangements for executing specific machine instructions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
    • G06F17/141—Discrete Fourier transforms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F12/00—Accessing, addressing or allocating within memory systems or architectures
    • G06F12/02—Addressing or allocation; Relocation
    • G06F12/08—Addressing or allocation; Relocation in hierarchically structured memory systems, e.g. virtual memory systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46—Multiprogramming arrangements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/44—Arrangements for executing specific programmes
    • G06F9/4421—Execution paradigms
    • G06F9/4436—Data-driven
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F12/00—Accessing, addressing or allocating within memory systems or architectures
    • G06F12/02—Addressing or allocation; Relocation
    • G06F12/0223—User address space allocation, e.g. contiguous or non contiguous base addressing
    • G06F12/023—Free address space management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a programme unit and a register, e.g. for a simultaneous processing of several programmes
    • G06F15/163—Interprocessor communication

Similar Documents

Publication Publication Date Title
Yang et al. A GPGPU compiler for memory optimization and parallelism management
Ding et al. Improving effective bandwidth through compiler enhancement of global cache reuse
Baskaran et al. Optimizing sparse matrix-vector multiplication on GPUs
Ramanujam et al. Compile-time techniques for data distribution in distributed memory machines
Kandemir et al. Improving locality using loop and data transformations in an integrated framework
Brown et al. Compiler-based I/O prefetching for out-of-core applications
Gu et al. An empirically tuned 2D and 3D FFT library on CUDA GPU
Lucas et al. Multifrontal computations on GPUs and their multi-core hosts
Kandemir et al. A matrix-based approach to the global locality optimization problem
Datta et al. Titanium performance and potential: an NPB experimental study
Gatlin et al. Architecture-cognizant divide and conquer algorithms
Su et al. Automatic support for irregular computations in a high-level language
Kandemir et al. A unified framework for optimizing locality, parallelism, and communication in out-of-core computations
Hiranandani et al. Performance of hashed cache data migration schemes on multicomputers
Kandemir et al. An i/o-conscious tiling strategy for disk-resident data sets
Liu et al. Improving the performance of OpenMP by array privatization
Franke et al. A complete compiler approach to auto-parallelizing C programs for multi-DSP systems
Abdel-Hafeez et al. A comparison-free sorting algorithm on CPUs and GPUs
Li et al. Synthesizing efficient out-of-core programs for block recursive algorithms using block-cyclic data distributions
Voevodin et al. The V-Ray technology of optimizing programs to parallel computers
Kayraklioglu et al. A machine learning approach for productive data locality exploitation in parallel computing systems
Kandemir et al. A matrix-based approach to global locality optimization
Kodukula et al. Data-centric transformations for locality enhancement
Zhou et al. A parallel, out-of-core algorithm for RNA secondary structure prediction
Kandemir et al. Data relation vectors: A new abstraction for data optimizations