In recent years, significant advances have been made in the design and evaluation of
balanced (hyper) graph partitioning algorithms. We survey trends of the past decade in …

We investigate the problem of partitioning the vertices of a directed acyclic graph into a
given number of parts. The objective function is to minimize the number or the total weight of …

Hardware simulation is a critical tool for design, but its slow speed often bottlenecks the
entire design process. Although most signals in a digital design rarely change, most leading …

Task scheduling on fog environments surges new challenges compared to scheduling on
conventional cloud computing. Various levels of heterogeneity and dynamism cause task …

Coarse-grained reconfigurable architectures (CGRAs) provide high energy efficiency with
word-level programmability rather than bit-level ones such as FPGAs. The coarser …

Directed graphs are widely used to model data flow and execution dependencies in
streaming applications. This enables the utilization of graph partitioning algorithms for the …

As deep learning models become increasingly complex, the deep learning compilers are
critical for enhancing the system efficiency and unlocking hidden optimization opportunities …

Memory-aware network scheduling is becoming increasingly important for deep neural
network (DNN) inference on resource-constrained devices. However, due to the complex …

Many state-of-the-art Deep Neural Networks (DNNs) have substantial memory requirements.
Limited device memory becomes a bottleneck when training those models. We propose …

The sensitive information of vehicles which is closely related to the safety of transportation
makes the privacy problems in the vehicular networks a popular concern. The development …