Various research communities have independently arrived at stream processing as a
programming model for efficient and parallel computing. These communities include digital …

Stream Processing (SP) has evolved as the leading paradigm to process and gain value
from the high volume of streaming data produced, eg, in the domain of the Internet of Things …

Benchmarking has become one of the most important methods for quantitative performance
evaluation of processor and computer system designs. Benchmarking of modern …

Futhark is a purely functional data-parallel array language that offers a machine-neutral
programming model and an optimising compiler that generates OpenCL code for GPUs …

For more than thirty years, the parallel programming community has used the dependence
graph as the main abstraction for reasoning about and exploiting parallelism in" regular" …

This paper presents the design and implementation of PolyMage, a domain-specific
language and compiler for image processing pipelines. An image processing pipeline can …

Code cloning is not only assumed to inflate maintenance costs but also considered defect-
prone as inconsistent changes to code duplicates can lead to unexpected behavior …

This article addresses the profitability problem associated with auto-parallelization of
general-purpose distributed data stream processing applications. Auto-parallelization …

Coarse-grain reconfigurable arrays (CGRAs) can achieve much higher performance and
efficiency than general-purpose cores, approaching the performance of a specialized design …

This paper presents CMP Cooperative Caching, a unified framework to manage a CMP's
aggregate on-chip cache resources. Cooperative caching combines the strengths of private …