Reading Group
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Reading Group. Virtual Consensus in Delos
We are continuing through the OSDI 2020 paper list in our reading group. This time we have discussed “Virtual Consensus in Delos,” a consensus paper (Delos is yet another greek island to continue the consensus naming tradition). Delos relies on the log abstraction to keep track of all commands/operations and their order. Traditionally, some consensus…
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Reading Group. hXDP: Efficient Software Packet Processing on FPGA NICs
Last reading group meeting we have discussed “hXDP: Efficient Software Packet Processing on FPGA NICs.” This paper talks about using FPGA NICs to offload some CPU cycles doing certain routine packet processing tasks. In particular, the paper implements XDP purely in FPGA and achieves a performance similar to that of a single x86 CPU core.…
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Reading Group. Toward a Generic Fault Tolerance Technique for Partial Network Partitioning
Short Summary We have resumed the distributed systems reading group after a short holiday break. Yesterday we discussed the “Toward a Generic Fault Tolerance Technique for Partial Network Partitioning” paper from OSDI 2020. The paper studies a particular type of network partitioning – partial network partitioning. Normally, we expect that every node can reach every…
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Reading Group. Near-Optimal Latency Versus Cost Tradeoffs in Geo-Distributed Storage
Short Summary Yesterday we discussed Pando, a geo-replication system achieving near-optimal latency-cost tradeoff in storage systems. Pando uses large Flexible Paxos deployments and erasure coding to do its magic. Pando relies on having many storage sites to locate sites closer to users. It then uses Flexible Paxos to optimize read and write quorums to have…
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Reading Group. Autoscaling Tiered Cloud Storage in Anna.
This week we looked at “Autoscaling Tiered Cloud Storage in Anna.” This is the second Anna paper. The first one introduces Anna Key-Value store, and the second paper talks about various “cloud-native” improvements. The presentation by Michael Whittaker is available here: Short Summary Anna is an eventual-consistent key-value data store, where each value is a…
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Reading Group Paper List. Papers ##37-50
This week we are on the 35th paper in our reading group. We will be discussing “Autoscaling Tiered Cloud Storage in Anna” from VLDB 2019. It is exciting that the reading group has managed to go through this many papers since we have started in April! Today I and Murat have sat down and picked…
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Reading Group. Compositional Programming and Testing of Dynamic Distributed Systems
We have resumed the reading group after one week of Thanksgiving break. On Wednesday, we have discussed “Compositional Programming and Testing of DynamicDistributed Systems.” This paper is on the edge between programming languages, distributed systems, and some formal methods/verification. The premise of the paper is to decompose large monolithic distributed programs into smaller pieces and…
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Reading Group. Aria: A Fast and Practical Deterministic OLTP Database.
In our 33rd reading group meeting, we discussed “Aria: A Fast and Practical Deterministic OLTP Database.” by Yi Lu, Xiangyao Yu, Lei Cao, Samuel Madden. We had a very nice presentation by Alex Miller: Quick Summary Aria is a transaction protocol, heavily influenced by Calvin, and it largely adopts Calvin’s transaction model, with one big…
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Reading Group. High availability in cheap distributed key value storage
Our recent paper was “High availability in cheap distributed key value storage”. And what a paper that was! It was definitely a mind-tingling read the lead to a very interesting and long discussion session with the group. Short Summary The paper addresses the problem of fast recovery from the leader (primary) crashes in key-value stores…
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Reading Group. RMWPaxos: Fault-Tolerant In-Place Consensus Sequences
Quick Summary In the last reading group discussion, we talked about RMWPaxos. The paper argues that under some circumstances, log-based replication schemes and replicated state machines (RSMs), like Multi-Paxos, are a waste of resources. For example, when the state is small, it may be more efficient to just manage the state directly instead of managing…
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