Taiji: A DPU Memory Elasticity Solution for In-production Cloud Environments

TL;DR

Taiji introduces a memory elasticity architecture for DPUs in cloud environments, enabling over 50% memory overcommitment with minimal overhead, supporting hot-switch and hot-upgrade for production systems.

Contribution

It presents a novel resource-elasticity architecture combining hybrid virtualization and parallel memory swapping for DPUs, enabling high memory overcommitment and dynamic resource management.

Findings

Expands DPU memory resources by over 50%.

Maintains virtualization overhead around 5%.

Ensures 90% of swap-ins complete within 10 microseconds.

Abstract

The growth of cloud computing drives data centers toward higher density and efficiency. Data processing units (DPUs) enhance server network and storage performance but face challenges such as long hardware upgrade cycles and limited resources. To address these, we propose Taiji, a resource-elasticity architecture for DPUs. Combining hybrid virtualization with parallel memory swapping, Taiji switches the DPU's operating system (OS) into a guest OS and inserts a lightweight virtualization layer, making nearly all DPU memory swappable. It achieves memory overcommitment for the switched guest OS via high-performance memory elasticity, fully transparent to upper-layer applications, and supports hot-switch and hot-upgrade to meet in-production cloud requirements. Experiments show that Taiji expands DPU memory resources by over 50%, maintains virtualization overhead around 5%, and ensures 90% of swap-ins complete within 10 microseconds. Taiji delivers an efficient, reliable, low-overhead elasticity solution for DPUs and is deployed in large-scale production systems across more than 30,000 servers.