This paper proposes optical network interconnects as a key enabler for building high-
bandwidth ML training clusters with strong scaling properties. Our design, called SiP-ML …

This paper provides an overview of software-defined “hardware” infrastructures (SDHI).
SDHI builds upon the concept of hardware (HW) resource disaggregation. HW resource …

With the widespread use of distributed machine learning (DML), many IT companies have
established networks dedicated to DML. Different communication architectures of DML have …

High-performance, byte-addressable non-volatile main memories (NVMMs) force system
designers to rethink trade-offs throughout the system stack, often leading to dramatic …

Datacenter workloads have evolved from the data intensive, loosely-coupled workloads of
the past decade to more tightly coupled ones, wherein ultra-low latency communication is …

With cloud providers constantly seeking the best infrastructure trade-off between
performance delivered to customers and overall energy/utilization efficiency of their data …

Disaggregated racks comprise a dense cluster of separate pools of compute, memory and
storage blades, all inter-connected through an internal network within a single rack …

Circuit-switched technologies have long been proposed for handling high-throughput traffic
in datacenter networks, but recent developments in nanosecond-scale reconfiguration have …

Reconfigurable data center networks (RDCNs) are arising as a promising data center
network (DCN) design in the post-Moore's law era. However, the constantly reconfigured …

This paper promotes convertible data center network architectures, which can dynamically
change the network topology to combine the benefits of multiple architectures. We propose …