From its modest beginnings as a tool to validate forms, JavaScript is now an industrial-strength language used to power online applications such as spreadsheets, IDEs, image editors and even 3D games. Since all modern web browsers support JavaScript, it provides a medium that is both easy to distribute for developers and easy to access for users. This paper provides empirical data to answer the question: Is JavaScript fast enough for numerical computations? By measuring and comparing the runtime performance of benchmarks representative of a wide variety of scientific applications, we show that sequential JavaScript is within a factor of 2 of native code. Parallel code using WebCL shows speed improvements of up to 2.28 over JavaScript for the majority of the benchmarks.

From its modest beginnings as a tool to validate forms, JavaScript is now an industrial-strength language used to power online applications such as spreadsheets, IDEs, image editors and even 3D games. Since all modern web browsers support JavaScript, it provides a medium that is both easy to distribute for developers and easy to access for users. This paper provides empirical data to answer the question: Is JavaScript fast enough for numerical computations? By measuring and comparing the runtime performance of benchmarks representative of a wide variety of scientific applications, we show that sequential JavaScript is within a factor of 2 of native code. Parallel code using WebCL shows speed improvements of up to 2.28 over JavaScript for the majority of the benchmarks.

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