A key lesson was to measure what matters. From the outset, we defined clear success metrics—latency reduction, resource efficiency and cost improvement.
Blind Interference Alignment for MapReduce: Exploiting Side-Information With Reconfigurable Antennas
Abstract: In order to explore how blind interference alignment (BIA) schemes may take advantage of side-information in computation tasks, we study the degrees of freedom (DoF) of a K user wireless ...
Abstract: MapReduce is a software framework for processing data-intensive applications with a parallel manner in cloud computing systems. Some MapReduce jobs have the deadline requirements for their ...
We present Airavat, a Map Reduce-based system which provides strong security and privacy guarantees for distributed computations on sensitive data. Airavat is a novel integration of mandatory access ...
/home/data/programs/jdk/jdk-current/bin/java -classpath /home/data/programs/hadoop/hadoop-current/etc/hadoop: /home/data/programs/hadoop/hadoop-current/etc/hadoop ...
Cloud Posse uses atmos to easily orchestrate multiple environments using Terraform. In Cloud Posse's examples, we avoid pinning modules to specific versions to prevent discrepancies between the ...
The TEEL Lab at Carnegie Mellon University focuses on research in learning methods, technology for learning systems, curriculum development, and workforce training The TEEL Lab has several positions ...
An increasing number of MapReduce applications are written using high-level SQL-like abstractions on top of MapReduce engines. Such programs are translated into MapReduce workflows where the output of ...
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