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New research uses Bayesian optimization to tune Hyperledger Fabric performance

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new method called Caliper-in-the-Loop to automate the performance tuning of Hyperledger Fabric. This approach treats the complex configuration of Hyperledger Fabric as a black-box optimization problem, utilizing Bayesian optimization with dimensionality reduction. The system successfully improved transaction throughput by up to 12% in a cloud testbed, demonstrating a practical solution for optimizing high-dimensional systems. AI

IMPACT Offers a novel automated tuning method for complex distributed systems, potentially improving efficiency in blockchain applications.

RANK_REASON Academic paper detailing a new optimization method for Hyperledger Fabric.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New research uses Bayesian optimization to tune Hyperledger Fabric performance

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Yash Madhwal, Arseny Bolotnikov, Mark Prikhno, Irina Lebedeva, Ivan Laishevskiy, Vladimir Gorgadze, Artem Barger, Yury Yanovich ·

    Caliper-in-the-Loop: Black-Box Optimization for Hyperledger Fabric Performance Tuning

    arXiv:2605.02690v1 Announce Type: cross Abstract: Hyperledger Fabric performance depends on many interacting configuration parameters, making manual tuning difficult. We study automated throughput tuning by treating benchmarking as a noisy black-box optimization problem and apply…

  2. arXiv cs.AI TIER_1 English(EN) · Yury Yanovich ·

    Caliper-in-the-Loop: Black-Box Optimization for Hyperledger Fabric Performance Tuning

    Hyperledger Fabric performance depends on many interacting configuration parameters, making manual tuning difficult. We study automated throughput tuning by treating benchmarking as a noisy black-box optimization problem and applying Bayesian optimization (BO) with dimensionality…

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