Compiler-Driven Data Layout Transformation for Heterogeneous Platforms

Modern heterogeneous systems comprise of CPU cores, GPU cores, and in some cases, accelerator cores. Each of these computational cores have very different memory hierarchies, making it challenging to efficiently map the data structures of an application to these memory hierarchies automatically. In this paper, we present a compiler-driven data layout transformation framework for heterogeneous platforms. We integrate our data layout framework with the data parallel construct, forasync, of Habanero-C and enable the same source code to be compiled with different data layouts for various architectures. The programmer or an auto-tuner specifies a schema of the data layout. Our compiler infrastructure generates efficient code for different architectures based on the meta information provided in the schema. Our experimental results show significant benefits from the compiler-driven data layout transformation, and demonstrate that the best data layout for a program varies with different heterogenous platforms.