As both CPUs and GPUs become employed in a wide range of applications, it has been
acknowledged that both of these Processing Units (PUs) have their unique features and …

Develo** server applications that offload computation and data to a NIC accelerator is
laborious because one has to explore the design space of decisions about data placement …

We created detailed profiles of the energy consumed by common operations done on Java
List, Map, and Set abstractions. The results show that the alternative data types for these …

Reducing the energy usage of software is becoming more important in many environments,
in particular, battery-powered mobile devices, embedded systems and data centers. Recent …

Computers have become increasingly complex with the emergence of heterogeneous
hardware combining multicore CPUs and GPUs. These parallel systems exhibit tremendous …

Memory capacity is a key bottleneck for training large scale neural networks. Intel® Optane#
8482; DC PMM (persistent memory modules) which are available as NVDIMMs are a …

Many processors today integrate a CPU and GPU on the same die, which allows them to
share resources like physical memory and lowers the cost of CPU-GPU communication. As …

Search-based techniques have been demonstrated effective in solving complex optimization
problems that arise in domain-specific compilers for machine learning (ML). Unfortunately …

Linear regression is one of the most important and widely used techniques for data analysis.
However, sometimes people are not satisfied with it because of the following two limitations …

Heterogeneous multiprocessor systems, which are composed of a mix of processing
elements, such as commodity multicore processors, graphics processing units (GPUs), and …