For decades, programmers enjoyed a free lunch: their programs would become exponentially faster as new generations of processors were released, all with little-to-no changes. That free lunch is now over. Programmers now shoulder much of the burden in attaining scalable performance on today’s multi-core processors. This burden largely entails introducing parallelism into existing sequential programs, a notoriously difficult task that many programmers are currently unequipped to handle. In this talk I will discuss the challenge of introducing parallelism into sequential programs (parallelization) and describe my work on Kremlin, an automated tool that assists the programmer during this challenging task. Kremlin fills an important gap in the current set of parallelization tools, improving programmer productivity by helping answer the questions: “What parts of this program should I spend time parallelizing?” and “How much speedup can I expect if I parallelize this program?”.