CSR: Small: Collaborative Research: Exploring Portable Data Placement on Massively Parallel Platforms with Heterogeneous Memory Architectures

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Heterogeneous computing is becoming crucial for many computational fields, including simulations of the galaxy, analysis of social networks, modeling of stock transactions, and so on. Programming heterogeneous memory systems is a grand challenge, and creates a major obstacle between heterogeneous hardware and applications because of the programming complexity and fast hardware evolution. This project aims to address this obstacle, and is expected to significantly relieve programmers from handling the underlying memory system heterogeneity. The outcome from this research will also enable continuous enhancement of the computing efficiency of a number of applications on future heterogeneous systems, which is a critical condition for sustained advancement of science, health, security and other aspects of humanity.To address the programming challenges on heterogeneous memory systems, the project investigates a software framework, consisting of a hardware specification language, a set of novel compiler and runtime techniques, and advanced memory performance modeling. The goal is to develop a systematic solution to automatically place data given a complex heterogeneous memory system, especially on massively parallel platforms. With the proposed framework, programmers are relieved from tailoring their programs to different memory systems, and at the same time, the sophisticated memory systems can get fully translated into high computing efficiency. The framework transforms the programs such that they are customized - in terms of where data are placed in memory, when and how to migrate, etc. - to the underlying heterogeneous memory system at runtime and attain a near optimal memory usage.