EVMTracer: Dynamic Analysis of the Parallelization and Redundancy Potential in the Ethereum Virtual Machine

Ethereum is one of the first blockchains executing smart contracts, i.e., financial applications directly executed on the ledger using a virtual machine. High transaction volumes caused by financial applications, including decentralized finance and non-fungible tokens, slow down the Ethereum Virtual Machine. Hence, there is a need to detail the execution characteristics of the Ethereum Virtual Machine before its performance can be improved. This work introduces an off-line Ethereum virtual machine tracer called EVMTracer that produces runtime data dependence graphs from executed transactions as an alternative program representation. From the runtime dependence graphs, we can deduce valuable metrics about program execution characteristics, including the degree of parallelization and computational redundancies in smart contracts. Our experiments encompass all blocks up to
$\mathrm {12~ \text {M} }$
on the Ethereum mainnet. We found a geometric mean of
$1.90\times $
theoretical maximum speedup when executing the smart contracts in parallel and identified
$\mathrm {34.97~\%}$
of SLOAD instructions as redundant.