Congestion detection is the cornerstone of end-to-end congestion control. Through in-depth
observations and understandings, we reveal that existing congestion detection mechanisms …

The allreduce operation is an essential building block for many distributed applications,
ranging from the training of deep learning models to scientific computing. In an allreduce …

Benchmarking is commonly used in research fields, such as computer architecture design
and machine learning, as a powerful paradigm for rigorously assessing, comparing, and …

Congestion detection is the cornerstone of end-to-end congestion control. Through in-depth
observations and understandings, we reveal that existing congestion detection mechanisms …

Large-scale high-performance computing systems frequently experience a wide range of
failure modes, such as reliability failures (eg, hang or crash), and resource overload-related …

Node downtime and failed jobs in a computing cluster translate into wasted resources and
user dissatisfaction. Therefore understanding why nodes and jobs fail in HPC clusters is …

Recent advances in fast optical switching technology show promise in meeting the high
goodput and low latency requirements of datacenter networks (DCN). We present …

Hardware memory disaggregation is an emerging trend in datacenters that provides access
to remote memory as part of a shared pool or unused memory on machines across the …

Network congestion in high-speed interconnects is a major source of application runtime
performance variation. Recent years have witnessed a surge of interest from both academia …

Modern high-performance computing (HPC) systems concurrently execute multiple
distributed applications that contend for the high-speed network leading to congestion …