Horcrux: Automatic JavaScript Parallelism for Resource-Efficient Web Computation

Web pages today commonly include large amounts of JavaScript code in order to offer users a dynamic experience. These scripts often make pages slow to load, partly due to a fundamental inefficiency in how browsers process JavaScript content: browsers make it easy for web developers to reason about page state by serially executing all scripts on any frame in a page, but as a result, fail to leverage the multiple CPU cores that are readily available even on low-end phones.

In this paper, we show how to address this inefficiency without requiring pages to be rewritten or browsers to be modified. The key to our solution, Horcrux, is to account for the non-determinism intrinsic to web page loads and the constraints placed by the browser's API for parallelism. Horcrux-compliant web servers perform offline analysis of all the JavaScript code on any frame they serve to conservatively identify, for every JavaScript function, the union of the page state that the function could access across all loads of that page. Horcrux's JavaScript scheduler then uses this information to judiciously parallelize JavaScript execution on the client-side so that the end-state is identical to that of a serial execution, while minimizing coordination and offloading overheads. Across a wide range of pages, phones, and mobile networks covering web workloads in both developed and emerging regions, Horcrux reduces median browser computation delays by 31-44% and page load times by 18-37%.