Efficiently exploiting thread-level parallelism has been challenging for software developers.
As many parallel applications do not scale with the number of cores, the task of rightly …

Efficiently exploiting thread-level parallelism has been challenging. Many parallel
applications are not sufficiently balanced or CPU-bound to take advantage of the increasing …

The growing need for extracting information from large graphs has been pushing the
development of parallel graph algorithms. However, the highly irregular structure of the real …

In the age of the cloud-native, container technology, referred as OS-level virtualization, is
increasingly adopted to deploy cloud applications. Compared with virtual machines …

High-Performance computing systems have been constantly adopting CPU-GPU
architectures as a collaborative environment to accelerate applications by partitioning …

Many parallel applications do not scale as the number of threads increases, which means
that using the maximum number of threads will not always deliver the best outcome in …

The increasing use of cloud and HPC systems put more pressure on the efficient utilization
of hardware resources to keep costs low. Many dynamic concurrency throttling (DCT) …

Warehouses and Cloud Servers have been adopting collaborative CPU-FPGA architectures
as an alternative to enable extra acceleration for data-parallel applications by distributing …

Multi-threading is a common way for programs to benefit from the multi/many-core design.
However, the performance of some parallel programs does not increase/even decrease as …

Many parallel applications do not scale with the number of threads. Several online and
offline strategies have been proposed in order to optimize this number. While the former …