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Tejas Harith

Publications and source records attributed to Tejas Harith.

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LaissezCloud: Continuous Resource Renegotiation for the Public Cloud

Public clouds increasingly expose heterogeneous hardware, but their allocation interface remains built around rigid on-demand and spot service classes. This makes it hard to satisfy time-varying tenant objectives and operator constraints in oversubscribed, heterogeneous clusters without exposing internal application or infrastructure state. We present LaissezCloud, a cloud resource management platform for continuous re-negotiation of running allocations. Unlike spot instances, which use launch-time bids and unilateral preemption, LaissezCloud keeps allocations continuously contestable during execution: tenants and operators update bids online, and a running tenant keeps a resource only as long as its bid exceeds competing demand. Pricing serves both as a narrow waist and as an incentive-alignment mechanism between mutually untrusted participants: tenants express utility through bids, while operators price in power, cooling, or carbon constraints without exposing internal telemetry. Across a diverse set of accelerator workloads, LaissezCloud reduces performance degradation under contention by 8-23% versus on-demand and spot baselines, and scales to clusters of at least 10,000 nodes.

cs.DC

It's the People, Not the Placement: Rethinking Allocations in Post-Moore Clouds

The Cambrian explosion of new accelerators, driven by the slowdown of Moore's Law, has created significant resource management challenges for modern IaaS clouds. Unlike the homogeneous datacenters backing legacy clouds, emerging neoclouds amass a diverse portfolio of heterogeneous hardware -- NVIDIA GPUs, TPUs, Trainium chips, and FPGAs. Neocloud operators and tenants must transition from managing a single large pool of computational resources to navigating a set of highly fragmented and constrained pools. We argue that cloud resource management mechanisms and interfaces require a fundamental rethink to enable efficient and economical neoclouds. Specifically we propose shifting from long-term static resource allocation with fixed-pricing to dynamic allocation with continuous, multilateral cost re-negotatiaton. We demonstrate this approach is not only feasible for modern applications but also significantly improves resource efficiency and reduces costs. Finally, we propose a new architecture for the interaction between operators, tenants, and applications in neoclouds.

cs.DC