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Documents authored by Milionis, Jason

Document
DOI: 10.4230/LIPIcs.AFT.2026.34
EVM Workloads in the Wild: Evidence for Multi-Dimensional Gas Metering, State Growth, Delayed Execution, and Parallelism

Authors: Lioba Heimbach, Kushal Babel, and Jason Milionis

Published in: LIPIcs, Volume 395, 8th Conference on Advances in Financial Technologies (AFT 2026)

Abstract
Gas metering on EVM-compatible blockchains assumes that execution conditions are stable: that the resource mix is constant enough to justify collapsing execution costs into a single scalar with fixed relative prices, and that state drift between submission and execution time does not materially alter a transaction’s outcome. We measure the extent to which this assumption fails. We present a trace-level measurement study of EVM workloads on Ethereum (L1) and Base (L2) throughout 2025, sampling 3{,}000 blocks per day per chain. We decompose each transaction into opcode-level execution gas, intrinsic gas, refunds, and persistent state deltas including storage slots, contract bytecode, and account state. To measure state sensitivity, we re-execute transactions sampled during September 2025 on progressively older blockchain states and record how gas usage, execution outcomes, and storage access patterns change. We find the resource mix to be far from stable: on Base, storage reads and compute account for 29.2% and 24.3% of execution gas, while Ethereum devotes 34.9% to storage writes. The mix is not stable on the same chain either: Ethereum’s gas limit doubling during 2025 shifted its resource profile measurably toward more compute-heavy, Base-like patterns. Base also exhibits a higher fraction of cold storage reads at 49.7%, compared to 39.6% on Ethereum. Persistent state growth, a permanent cost priced as a transient one, reaches 435 GB on Base versus 30 GB on Ethereum, with different composition. We further find that execution outcomes are equally unstable: gas estimates vary across nearby historical states for 46.0% of transactions on Base, compared to 13.9% on Ethereum, with especially high sensitivity for MEV and DeFi activity. Storage access patterns also diverge across execution states, limiting the effectiveness of access lists and complicating parallel execution. Our measurements provide an empirical foundation for multi-dimensional gas metering and explicit pricing of state growth. They show that state-sensitive execution behavior complicates workload estimation and transaction parameterization, directly affecting the predictability of transactions' execution and user experience.
Cite as

Lioba Heimbach, Kushal Babel, and Jason Milionis. EVM Workloads in the Wild: Evidence for Multi-Dimensional Gas Metering, State Growth, Delayed Execution, and Parallelism. In 8th Conference on Advances in Financial Technologies (AFT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 395, pp. 34:1-34:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{heimbach_et_al:LIPIcs.AFT.2026.34,
  author =	{Heimbach, Lioba and Babel, Kushal and Milionis, Jason},
  title =	{{EVM Workloads in the Wild: Evidence for Multi-Dimensional Gas Metering, State Growth, Delayed Execution, and Parallelism}},
  booktitle =	{8th Conference on Advances in Financial Technologies (AFT 2026)},
  pages =	{34:1--34:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-451-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{395},
  editor =	{Kiayias, Aggelos and Kyropoulou, Maria},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AFT.2026.34},
  URN =		{urn:nbn:de:0030-drops-278883},
  doi =		{10.4230/LIPIcs.AFT.2026.34},
  annote =	{Keywords: Ethereum, EVM, gas metering, state growth, workload analysis, Layer-2}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2024.81
A Myersonian Framework for Optimal Liquidity Provision in Automated Market Makers

Authors: Jason Milionis, Ciamac C. Moallemi, and Tim Roughgarden

Published in: LIPIcs, Volume 287, 15th Innovations in Theoretical Computer Science Conference (ITCS 2024)

Abstract
In decentralized finance ("DeFi"), automated market makers (AMMs) enable traders to programmatically exchange one asset for another. Such trades are enabled by the assets deposited by liquidity providers (LPs). The goal of this paper is to characterize and interpret the optimal (i.e., profit-maximizing) strategy of a monopolist liquidity provider, as a function of that LP’s beliefs about asset prices and trader behavior. We introduce a general framework for reasoning about AMMs based on a Bayesian-like belief inference framework, where LPs maintain an asset price estimate, which is updated by incorporating traders' price estimates. In this model, the market maker (i.e., LP) chooses a demand curve that specifies the quantity of a risky asset to be held at each dollar price. Traders arrive sequentially and submit a price bid that can be interpreted as their estimate of the risky asset price; the AMM responds to this submitted bid with an allocation of the risky asset to the trader, a payment that the trader must pay, and a revised internal estimate for the true asset price. We define an incentive-compatible (IC) AMM as one in which a trader’s optimal strategy is to submit its true estimate of the asset price, and characterize the IC AMMs as those with downward-sloping demand curves and payments defined by a formula familiar from Myerson’s optimal auction theory. We generalize Myerson’s virtual values, and characterize the profit-maximizing IC AMM. The optimal demand curve generally has a jump that can be interpreted as a "bid-ask spread," which we show is caused by a combination of adverse selection risk (dominant when the degree of information asymmetry is large) and monopoly pricing (dominant when asymmetry is small). This work opens up new research directions into the study of automated exchange mechanisms from the lens of optimal auction theory and iterative belief inference, using tools of theoretical computer science in a novel way.
Cite as

Jason Milionis, Ciamac C. Moallemi, and Tim Roughgarden. A Myersonian Framework for Optimal Liquidity Provision in Automated Market Makers. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 81:1-81:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{milionis_et_al:LIPIcs.ITCS.2024.81,
  author =	{Milionis, Jason and Moallemi, Ciamac C. and Roughgarden, Tim},
  title =	{{A Myersonian Framework for Optimal Liquidity Provision in Automated Market Makers}},
  booktitle =	{15th Innovations in Theoretical Computer Science Conference (ITCS 2024)},
  pages =	{81:1--81:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-309-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{287},
  editor =	{Guruswami, Venkatesan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2024.81},
  URN =		{urn:nbn:de:0030-drops-196094},
  doi =		{10.4230/LIPIcs.ITCS.2024.81},
  annote =	{Keywords: Posted-Price Mechanisms, Asset Exchange, Market Making, Automated Market Makers (AMMs), Blockchains, Decentralized Finance, Incentive Compatibility, Optimization}
}

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