In recent years, the limits of the multicore approach emerged in the so-called “dark silicon”
issue and diminishing returns of an ever-increasing core count. Hardware manufacturers …

A number of recent efforts have attempted to design accelerators for popular machine
learning algorithms, such as those involving convolutional and deep neural networks (CNNs …

Graphs are one of the key data structures for many real-world computing applications and
the importance of graph analytics is ever-growing. While existing software graph processing …

Reconfigurable architectures have gained popularity in recent years as they allow the
design of energy-efficient accelerators. Fine-grain fabrics (eg FPGAs) have traditionally …

Constructing energy-efficient database systems to reduce economic costs and
environmental impact has been studied for 10 years. With the emergence of the big data …

Pointer chasing is a fundamental operation, used by many important data-intensive
applications (eg, databases, key-value stores, graph processing workloads) to traverse …

With the end of both Dennard's scaling and Moore's law, computer users and researchers
are aggressively exploring alternative forms of computing in order to continue the …

Demand for low-power data processing hardware continues to rise inexorably. Existing
programmable and" general purpose" solutions (eg. SIMD, GPGPUs) are insufficient, as …

Computer architectures are moving towards an era dominated by many-core machines with
dozens or even hundreds of cores on a single chip. This unprecedented level of on-chip …

Complex data queries, because of their need for random accesses, have proven to be slow
unless all the data can be accommodated in DRAM. There are many domains, such as …