7 papers
Barnacle: Adaptive Multi-Leader Scheduling for DAG-Based Consensus
George Danezis, Zeno De Angeli, Alexandru Ianov Vitanov +5
In DAG-based consensus, all validators propose blocks concurrently, and designated leader blocks drive transaction commit. Having multiple leader slots per round cuts queuing laten…
Remora: Scale-out Deterministic Execution for Smart Contracts
Zhengqing Liu, Alberto Sonnino, Igor Zablotchi +2
Modern blockchains rely on a modular architecture that decouples consensus from execution. Recent advances in consensus algorithms have shifted the bottleneck to the execution laye…
Tidehunter: Large-Value Storage With Minimal Data Relocation
Andrey Chursin, Lefteris Kokoris-Kogias, Alex Orlov +2
Log-Structured Merge-Trees (LSM-trees) dominate persistent key-value storage but suffer from high write amplification from 10x to 30x under random workloads due to repeated compact…
Byzantine Consensus in the Random Asynchronous Model
George Danezis, Jovan Komatovic, Lefteris Kokoris-Kogias +2
We propose a novel relaxation of the classic asynchronous network model, called the random asynchronous model, which removes adversarial message scheduling while preserving unbound…
Mahi-Mahi: Low-Latency Asynchronous BFT DAG-Based Consensus
Philipp Jovanovic, Lefteris Kokoris Kogias, Bryan Kumara +3
We present Mahi-Mahi, the first asynchronous BFT consensus protocol that achieves sub-second latency in the WAN while processing over 100,000 transactions per second. We accomplish…
Pilotfish: Distributed Execution for Scalable Blockchains
Quentin Kniep, Lefteris Kokoris-Kogias, Alberto Sonnino +2
Scalability is a crucial requirement for modern large-scale systems, enabling elasticity and ensuring responsiveness under varying load. While cloud systems have achieved scalable…
Cliff-Learning
Tony T. Wang, Igor Zablotchi, Nir Shavit +1
We study the data-scaling of transfer learning from foundation models in the low-downstream-data regime. We observe an intriguing phenomenon which we call cliff-learning. Cliff-lea…