With the proliferation of ultrahigh-speed mobile networks and internet-connected devices,
along with the rise of artificial intelligence (AI), the world is generating exponentially …

The monolithic server model where a server is the unit of deployment, operation, and failure
is meeting its limits in the face of several recent hardware and application trends. To improve …

It has long been known that photonic communication can alleviate the data movement
bottlenecks that plague conventional microelectronic processors. More recently, there has …

Computing demand continues to grow exponentially, largely driven by" big data" processing
on hyperscale data stores. At the same time, the slowdown in Moore's law is leading the …

The recent explosive compute growth, mainly fueled by the boost of artificial intelligence (AI)
and deep neural networks (DNNs), is currently instigating the demand for a novel computing …

We evaluate a new processing-in-memory (PIM) architecture from UPMEM that was built
and deployed in an off-the-shelf server. Systems designed to perform computing in or near …

In-network processing, where data is processed by special-purpose devices as it passes
over the network, is showing great promise at improving application performance, in …

Analytic workloads on terabyte data-sets are often run in the cloud, where application and
storage servers are separate and connected via network. In order to saturate the storage …

Database analytic query workloads are heavy consumers of data-center cycles, and there is
constant demand to improve their performance. Associative processors (AP) have re …

The data science revolution and growing popularity of data lakes make efficient processing
of raw data increasingly important. To address this, we propose the ACCelerated Operators …