When a computational task tolerates a relaxation of its specification or when an algorithm
tolerates the effects of noise in its execution, hardware, system software, and programming …

The rapid growth of demanding applications in domains applying multimedia processing
and machine learning has marked a new era for edge and cloud computing. These …

Ethereum is an emerging distributed computing platform that supports a decentralized
replicated virtual machine at a large scale. Transactions in Ethereum are specified in smart …

A system's memory size is often dictated by worst-case workloads with highest memory
requirements; this causes memory to be underutilized in the common case when the system …

As we approach the limits of Moore's law, researchers are exploring new paradigms for
future high-performance computing (HPC) systems. Approximate computing has gained …

The challenging deployment of compute-intensive applications from domains such Artificial
Intelligence (AI) and Digital Signal Processing (DSP), forces the community of computing …

Computational workflows are important methods for automating complex data-generation
and analysis pipelines. Workflows are composed of sub-graphs that perform specific tasks …

The end of Dennard scaling and the slowdown of Moore's law led to a shift in technology
trends towards parallel architectures, particularly in HPC systems. To continue providing …

As computer system technology approaches the end of Moore's law, new computing
paradigms that improve performance become a necessity. One such paradigm is …

Due to the ever-increasing complexity of computing tasks, emerging computing paradigms
that increase efficiency, such as approximate computing, are gaining momentum. However …