Now showing items 1-5 of 5

    • Improving the Efficiency of Map-Reduce Task Engine 

      Chadha, Mehul (2014-10-03)
      Map-Reduce is a popular distributed programming framework for parallelizing computation on huge datasets over a large number of compute nodes. This year completes a decade since it was invented by Google in 2004. Hadoop, ...
    • Large Scale Online Aggregation Via Distributed Systems 

      Pansare, Niketan (2014-12-04)
      From movie recommendations to fraud detection to personalized health care, there is growing need to analyze huge amounts of data quickly. To deal with huge amounts of data, many analysts use MapReduce, a software framework ...
    • Productive Programming Systems for Heterogeneous Supercomputers 

      Grossman, Max (2017-01-31)
      The majority of today's scientific and data analytics workloads are still run on relatively energy inefficient, heavyweight, general-purpose processing cores, often referred to in the literature as latency-oriented ...
    • Programming Models and Runtimes for Heterogeneous Systems 

      Grossman, Max (2013-09-16)
      With the plateauing of processor frequencies and increase in energy consumption in computing, application developers are seeking new sources of performance acceleration. Heterogeneous platforms with multiple processor ...
    • Understanding and Improving the Efficiency of Failure Resilience for Big Data Frameworks 

      Dinu, Florin (2013-10-30)
      Big data processing frameworks (MapReduce, Hadoop, Dryad) are hugely popular today because they greatly simplify the management and deployment of big data analysis jobs requiring the use of many machines in parallel. A ...