LIBRARIES

A memory abstraction is an abstraction layer between the program execution and the memory that provides a different "view " of a memory location depending on the execution context in which the memory access is made. Properly designed memory abstractions help ease the task of parallel programming by mitigating the complexity of synchronization or admitting more efficient use of resources. This dissertation describes five memory abstractions for parallel programming: (i) cactus stacks that interoperate with linear stacks, (ii) efficient reducers, (iii) reducer arrays, (iv) ownership-aware transactions, and (v) location-based memory fences. To demonstrate the utility of memory abstractions, my collaborators and I developed Cilk-M, a dynamically multithreaded concurrency platform which embodies the first three memory abstractions. Many dynamic multithreaded concurrency platforms incorporate cactus stacks to support mul-tiple stack views for all the active children simultaneously. The use of cactus stacks, albeit essential, forces concurrency platforms to trade off between performance, memory consumption, and inter-operability with serial code due to its incompatibility with linear stacks. This dissertation proposes a new strategy to build a cactus stack using thread-local memory mapping (or TLMM), whic