The growing complexity and diversity of neural networks in the fields of autonomous driving
and intelligent robots have facilitated the research of many-core architectures, which can …

Existing tiled manycore architectures propose to convert abundant silicon resources into
general-purpose parallel processors with unmatched computational density and …

Manycore architectures integrate hundreds of cores on a single chip by using simple cores
and simple memory systems usually based on software-managed scratchpad memories …

The lung nodule detection technology plays a vital role in the diagnosis and treatment of
early lung cancer. Deep learning is currently one of the main technologies applied in …

With the development of intelligent applications, simply relying on traditional single type of
computing unit cannot efficiently satisfy diverse cloud requirements. The emergence of …

Large-scale general matrix multiplications (LMMs) are the key bottlenecks in various
computation domains such as Transformer applications. However, it is a challenge to …

Many-core chip multiprocessor offers high parallel processing power for big data analytics;
however, they require efficient multi-level cache and interconnection to achieve high system …

Traditional general-purpose processors emphasize finding parallelism using hardware
control logic, but this logic is energy inefficient and will limit future performance …

Existing tiled manycore architectures propose to convert abundant silicon resources into
general-purpose parallel processors with unmatched computational density and …