[go: up one dir, main page]

Makrani et al., 2018 - Google Patents

Compressive sensing on storage data: An effective solution to alleviate i/0 bottleneck in data-intensive workloads

Makrani et al., 2018

View PDF
Document ID
991367618104614124
Author
Makrani H
Sayadi H
Manoj S
Raftirad S
Homayoun H
Publication year
Publication venue
2018 IEEE 29th International Conference on Application-specific Systems, Architectures and Processors (ASAP)

External Links

Snippet

The gap between computation speed and I/O access on modern computing systems imposes processing limitations in data-intensive applications. Employing high-end memory has proven not to enhance the performance for I/O bound applications, given the low …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/14Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
    • G06F17/141Discrete Fourier transforms
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F12/00Accessing, addressing or allocating within memory systems or architectures
    • G06F12/02Addressing or allocation; Relocation
    • G06F12/08Addressing or allocation; Relocation in hierarchically structured memory systems, e.g. virtual memory systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F7/00Methods or arrangements for processing data by operating upon the order or content of the data handled
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/07Error detection; Error correction; Monitoring responding to the occurence of a fault, e.g. fault tolerance
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F1/00Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
    • HELECTRICITY
    • H03BASIC ELECTRONIC CIRCUITRY
    • H03MCODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M7/00Conversion of a code where information is represented by a given sequence or number of digits to a code where the same information or similar information or a subset of information is represented by a different sequence or number of digits
    • H03M7/30Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction

Similar Documents

Publication Publication Date Title
Sadi et al. Efficient spmv operation for large and highly sparse matrices using scalable multi-way merge parallelization
US8115659B2 (en) Method and apparatus for efficient gathering of information in a multicore system
Makrani et al. Compressive sensing on storage data: An effective solution to alleviate i/0 bottleneck in data-intensive workloads
US20190370645A1 (en) Deep neural network accelerator with fine-grained parallelism discovery
US20200145680A1 (en) Parallel coding of syntax elements for jpeg accelerator
Zou et al. FlexAnalytics: a flexible data analytics framework for big data applications with I/O performance improvement
Bicer et al. Integrating online compression to accelerate large-scale data analytics applications
Zeng et al. An empirical evaluation of columnar storage formats
US8847798B2 (en) Systems and methods for data compression and parallel, pipelined decompression
JPWO2020190808A5 (en)
US20210256357A1 (en) Embedded stochastic-computing accelerator architecture and method for convolutional neural networks
US10848775B2 (en) Memory layout for JPEG accelerator
CN112256623B (en) Heterogeneous system-based processing performance optimization method and device
Salamat et al. NASCENT2: Generic near-storage sort accelerator for data analytics on SmartSSD
Niu et al. Reuse kernels or activations? A flexible dataflow for low-latency spectral CNN acceleration
Sun et al. gLSM: Using GPGPU to Accelerate Compactions in LSM-tree-based Key-value Stores
Karakasis et al. A comparative study of blocking storage methods for sparse matrices on multicore architectures
Finnerty et al. Dr. BFS: Data centric breadth-first search on FPGAs
Parravicini et al. Scaling up hbm efficiency of top-k spmv for approximate embedding similarity on fpgas
Sayadi et al. CUDA memory optimisation strategies for motion estimation
Yuan et al. Parallel implementation of lossy data compression for temporal data sets
Istvan et al. Active pages 20 years later: Active storage for the cloud
US11748255B1 (en) Method for searching free blocks in bitmap data, and related components
Wunderlich et al. Network coding parallelization based on matrix operations for multicore architectures
Li et al. An FPGA‐based JPEG preprocessing accelerator for image classification