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JavaScript is the most popular language on the web and is a crucial component of HTML5 applications and services that run on consumer platforms ranging from desktops to phones. However, despite ample amount of hardware parallelism available to web applications on such platforms, JavaScript web applications remain predominantly sequential. Common parallel programming solutions accepted by other programming languages failed to transfer themselves to JavaScript due to differences in programming models, the additional requirements of the web and different developer expectations. In this paper we present River Trail - a parallel programming model and API for JavaScript that provides safe, portable, programmer-friendly, deterministic parallelism to JavaScript applications. River Trail allows web applications to effectively utilize multiple cores, vector instructions, and GPUs on client platforms while allowing the web developer to remain within the environment of JavaScript. We describe the implementation of the River Trail compiler and runtime and present experimental results that show the impact of River Trail on performance and scalability for a variety of realistic HTML5 applications. Our experiments show that River Trail has a dramatic positive impact on overall performance and responsiveness of computationally intense JavaScript based applications achieving up to 33.6 times speedup for kernels and up to 11.8 times speedup for realistic web applications compared to sequential JavaScript. Moreover, River Trail enables new interactive web usages that are simply not even possible with standard sequential JavaScript.