Stefan K. Muller

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An important feature of functional programs is that they are parallel by default. Implementing an efficient parallel functional language, however, is a major challenge, in part because the high rate of allocation and freeing associated with functional programs requires an efficient and scalable memory manager. In this paper, we present a technique for(More)
With the rise of multicore computers, parallel applications no longer consist solely of computational, batch workloads, but also include applications that may, for example, take input from a user, access secondary storage or the network, or perform remote procedure calls. Such operations can incur substantial latency, requiring the program to wait for a(More)
We articulate the need for managing (data) locality automatically rather than leaving it to the programmer, especially in parallel programming systems. To this end, we propose techniques for coupling tightly the computation (including the thread scheduler) and the memory manager so that data and computation can be positioned closely in hardware. Such tight(More)
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