Currently, the data to be explored and exploited by computing systems increases at an
exponential rate. The massive amount of data or so-called “Big Data” put pressure on …

Chip multicore processors (CMPs) have emerged as the dominant architecture choice for
modern computing platforms and will most likely continue to be dominant well into the …

Package-level integration using multi-chip-modules (MCMs) is a promising approach for
building large-scale systems. Compared to a large monolithic die, an MCM combines many …

Emerging scale-out workloads require extensive amounts of computational resources.
However, data centers using modern server hardware face physical constraints in space …

The use of increasingly larger and more complex neural networks (NNs) makes it critical to
scale the capabilities and efficiency of NN accelerators. Tiled architectures provide an …

In scientific cloud workflows, large amounts of application data need to be stored in
distributed data centres. To effectively store these data, a data manager must intelligently …

Recent research advocates using large die-stacked DRAM caches to break the memory
bandwidth wall. Existing DRAM cache designs fall into one of two categories---block-based …

The variety and complexity of microservices in warehouse-scale data centers has grown
precipitously over the last few years to support a growing user base and an evolving product …

Applications extensively use data objects with a regular and fixed layout, which leads to the
recurrence of access patterns over memory regions. Spatial data prefetching techniques …

Chip-multiprocessors (CMPs) must often execute workload mixes with different performance
requirements. On one hand, user-facing, latency-critical applications (eg, web search) need …