Ankush Jain, Sheng Jiang, Charles D. Cranor, Qing Zheng, Brian Atkinson, George Amvrosiadis, Gary A. Grider

SC26, November 15-20, 2026, Chicago, Illinois, USA.

The bulk-synchronous parallel (BSP) paradigm powers critical computational workloads from scientific simulations to large-scale machine learning training. Running on tens of thousands of processors, these systems are uniquely sensitive to performance variations that current observability approaches struggle to diagnose—post-hoc analysis of massive traces introduces latency and rigidity that obstructs timely diagnosis. To address these challenges, we present ORCA, a system for always-on, steerable BSP observability. [...more]

Demystifying and Improving Lazy Promotion in Cache Eviction

Qinghan Chen, Muhammad Haekal Muhyidin Al-Araby, Ziyue Qiu, Zhuofan Chen, Rashmi Vinaya, Juncheng Yang

Proceedings of the VLDB Endowment, Vol. 19, No. 4, ISSN 2150-8097, 2026. Presented at 52nd International Conference on Very Large Data Bases. Boston, MA, USA, Aug 31st - Sep 4th, 2026.
BEST PAPER HONORABLE MENTION!

Cache eviction algorithms play a critical role in the performance of modern data systems, yet their scalability is often limited by the high computational overhead associated with object promotions. Lazy Promotion techniques have emerged as relaxations of traditional Least-Recently-Used (LRU) methods, designed to alleviate lock contention and increase throughput. This work uses production traces from real-world systems to benchmark five Lazy Promotion strategies: Probabilistic-LRU, Batch-LRU, Delay-LRU, FIFO-reinsertion, and Random-LRU. We evaluate these techniques. [...more]

Towards Truly Burst-Aware Evaluation of Data Center Congestion Control.

Pragna Mamidipaka, Srikanth Sundaresan, Theophilus A. Benson

10th Asia-Pacific Workshop on Networking (APNet 2026) August 6–7, 2026, Singapore.

The performance of datacenter congestion control algorithms (CCAs) is highly sensitive to bursty traffic patterns, yet a significant fidelity gap exists between evaluation workloads and production traffic. Current evaluations primarily rely on synthetic workloads constructed from flow-size CDFs with incast overlaid on top, an approach that, while intuitive, we show produces traffic that is dissimilar to production in its temporal burst clustering. [...more]