Skip to main content

4 Result(s)

within Rajkishore Barik Remove this filter Processor Architectures Remove this filter

and

  1. No Access

    Chapter and Conference Paper

    SWIRL ++ : Evaluating Performance Models to Guide Code Transformation in Convolutional Neural Networks

    Convolutional Neural Networks (CNNs) are ubiquitous in applications ranging from self-driving cars to various branches of health care. CPUs with large core counts and wide SIMD support are used in HPC clusters...

    Tharindu R. Patabandi, Anand Venkat… in Languages and Compilers for Parallel Compu… (2021)

  2. No Access

    Chapter and Conference Paper

    Mozart : Efficient Composition of Library Functions for Heterogeneous Execution

    Current processor trend is to couple a commodity processor with a GPU, a co-processor, or an accelerator. To unleash the full computational power of such heterogeneous systems is a daunting task: programmers o...

    Rajkishore Barik, Tatiana Shpeisman… in Languages and Compilers for Parallel Compu… (2019)

  3. No Access

    Article

    Accelerating Data Analytics on Integrated GPU Platforms via Runtime Specialization

    Integrated GPU systems are a cost-effective and energy-efficient option for accelerating data-intensive applications. While these platforms have reduced overhead of offloading computation to the GPU and potent...

    Naila Farooqui, Indrajit Roy, Yuan Chen… in International Journal of Parallel Programm… (2018)

  4. No Access

    Chapter and Conference Paper

    An Efficient Algorithm to Compute Delay Set in SPMD Programs

    We present compiler analysis for single program multiple data (SPMD) programs that communicate through shared address space. The choice of memory consistency model is sequential consistency as defined by Lampo...

    Manish P. Kurhekar, Rajkishore Barik, Umesh Kumar in High Performance Computing - HiPC 2003 (2003)