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#Distributed Systems

8 entries

Oct 2024Distributed Systems Classics

Reading Notes: Lamport Clocks and Happens-Before

Notes on Lamport's 1978 paper introducing logical clocks and the happens-before relation, with observations on how the idea maps onto modern distributed databases.

distributed systemsclocksLamportreading notes

Sep 2024Parth Sinha, Elena Voronova, James WhitfieldACM Symposium on Operating Systems Principles (SOSP)

Adaptive Consensus Protocols Under Partial Synchrony

We present AdaptRaft, a variant of the Raft consensus algorithm that dynamically adjusts its timing parameters using a lightweight online learning model, reducing tail latency by up to 34% in geo-distributed deployments.

distributed systemsconsensusmachine learningRaft

Aug 2024

AdaptRaft

A modified Raft implementation with an online bandit learner that adapts election and heartbeat timeouts to observed network conditions. Companion codebase for the SOSP 2024 paper.

distributed systemsRaftGomachine learning

Jul 2024Distributed Systems Classics

Working Notes: What Raft Actually Guarantees

Informal notes clarifying which safety and liveness properties Raft provides under which assumptions, written while preparing a talk on adaptive consensus.

distributed systemsRaftconsensusworking notes

Jan 2024

Distributed Systems — Hilary Term 2024

Graduate teaching assistant for the Distributed Systems course. Eight tutorials covering consensus, replication, fault tolerance, and consistency models.

teachingdistributed systemsgraduate

Nov 2023

DistBench

A configurable benchmarking harness for distributed consensus protocols. Supports pluggable protocol implementations, synthetic and replay workloads, and structured JSON output for reproducible experiments.

distributed systemsbenchmarkingPythonresearch tools

Jun 2023Parth SinhaWorkshop on ML for Systems (MLSys)

Learned Indices for Distributed Key-Value Stores

We explore the applicability of learned index structures to distributed key-value stores, demonstrating that model-based indices can reduce lookup latency by 22% with a modest increase in memory footprint on skewed workloads.

machine learningdistributed systemsindexingkey-value stores