Extracting portable performance in an application requires structuring that program into a data-flow graph of coarse-grained tasks (CGTs). Structuring applications that interconnect multiple external libraries and custom code (i.e., “Code From The Wild” (CFTW)) is challenging. When experts manually restructure a program, they trivialize the extraction of structure; however, this expertise is not broadly available. Automatic structuring approaches focus on the intersection of hot code and static loops, ignoring the data dependencies between tasks and significantly reducing the scope of analyzeable programs. This work addresses the problem of extracting the data-flow graph of CGTs from CFTW. To that end, we present Cyclebite. Our approach extracts CGTs from unstructured compute-programs by detecting CGT candidates in the simplified Markov Control Graph (MCG), and localizing CGTs in an epoch profile. Additionally, the epoch profile extracts the data dependence between CGTs required to build the data-flow graph of CGTs. Cyclebite demonstrates a robust selectivity for critical CGTs relative to the state-of-the-art (SoA), leading to a potential speedup of 12x on average and thread-scaling of 24x on average compared to modern compiler optimizers. We validate the results of Cyclebite and compare them to two SoA techniques using an input corpus of 25 open-source C/C++ libraries with 2,019 unique execution profiles.

RF system development is traditionally constrained by a restrictive trade-off between power efficiency and programmatic flexibility. We outline a path towards achieving both, thereby enabling a range of new system concepts that better utilize limited resources. As an example, for many future applications, we consider RF convergence – reusing the same spectrum and waveforms to achieve multiple distributed system functions and goals, simultaneously. To enable this next step in processing, we develop a novel framework that includes both software and the system-on-chip (SoC) design.