Popular SSD-based key-value stores consume a large amount of DRAM in order to provide high-performance database operations. However, DRAM can be expensive for data center providers, especially given recent global supply shortages that have resulted in increasing DRAM costs. In this work, we design a key-value store, MyNVM, which leverages an NVM block device to reduce DRAM usage, and to reduce the total cost of ownership, while providing comparable latency and queries-per-second (QPS) as MyRocks on a server with a much larger amount of DRAM. Replacing DRAM with NVM introduces several challenges. In particular, NVM has limited read bandwidth, and it wears out quickly under a high write bandwidth. We design novel solutions to these challenges, including using small block sizes with a partitioned index, aligning blocks post-compression to reduce read bandwidth, utilizing dictionary compression, implementing an admission control policy for which objects get cached in NVM to control its durability, as well as replacing interrupts with a hybrid polling mechanism. We implemented MyNVM and measured its performance in Facebook's production environment. Our implementation reduces the size of the DRAM cache from 96 GB to 16 GB, and incurs a negligible impact on latency and queries-per-second compared to MyRocks. Finally, to the best of our knowledge, this is the first study on the usage of NVM devices in a commercial data center environment.

Memory disaggregation has received attention in recent years as a promising idea to reduce the total cost of ownership (TCO) of memory in modern datacenters. However, relying on remote memory expands an application's failure domain and makes it susceptible to tail latency variations. In attempts to making disaggregated memory resilient, stateof-the-art solutions face the classic tradeoff between performance and efficiency: some double the memory overhead of disaggregation by replicating to remote memory, while many others limit performance by replicating to the local disk.We present Hydra, a configurable, erasure-coded resilience mechanism for common memory disaggregation solutions. It can transparently handle uncertainties arising from remote failures, evictions, memory corruptions, and stragglers from network imbalance with a significantly better performanceefficiency tradeoff than the state-of-the-art. We design a finetuned data path to achieve single µs read/write latency to remote memory, develop decentralized algorithms for clusterwide memory management, and analyze how to select parameters to mitigate independent and correlated uncertainties. Our integration of Hydra with two major memory disaggregation systems and evaluation on a 50-machine RDMA cluster demonstrates that it achieves the best of both worlds: it improves the latency and throughput of memory-intensive applications by up to 64.78× and 20.61×, respectively, over the state-of-the-art disk backup-based solution. At the same time, it provides performance similar to that of in-memory replication with 1.6× lower memory overhead.

The end of Dennard scaling and the slowing of Moore's Law has put the energy use of datacenters on an unsustainable path. Datacenters are already a significant fraction of worldwide electricity use, with application demand scaling at a rapid rate. We argue that substantial reductions in the carbon intensity of datacenter computing are possible with a software-centric approach: by making energy and carbon visible to application developers on a fine-grained basis, by modifying system APIs to make it possible to make informed trade offs between performance and carbon emissions, and by raising the level of application programming to allow for flexible use of more energy efficient means of compute and storage. We also lay out a research agenda for systems software to reduce the carbon footprint of datacenter computing.

Unlike their cellular counterparts, Wi-Fi networks do not have the luxury of a dedicated control plane that is decoupled from the data plane. Consequently, Wi-Fi struggles to provide many of the capabilities that are taken for granted in cellular networks, including efficient and fair resource allocation, QoS and handoffs. The reason for the lack of a control plane with designated spectrum is that it would impose significant overhead. This is at odds with Wi-Fi's goal of providing a simple, plug-and-play network. In this paper we present Flashback, a novel technique that provides a decoupled low overhead control plane for wireless networks that retains the simplicity of Wi-Fi's distributed asynchronous operation. Flashback allows nodes to reliably send short control messages concurrently with data transmissions, while ensuring that data packets are decoded correctly without harming throughput. We utilize Flashback's novel messaging capability to design, implement and experimentally evaluate a reliable control plane for Wi-Fi with rates from 175Kbps to 400Kbps depending on the environment. Moreover, to demonstrate its broad applicability, we design and implement a novel resource allocation mechanism that utilizes Flashback to provide efficient, QoS-aware and fair medium access, while eliminating control overheads including data plane contention, RTS/CTS and random back offs.

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