Parallel programming paradigms are commonly characterized by the core metrics of scalability, memory use, ease of use, hardware requirements and resiliency. Increasingly the support of heterogeneous environments, for example a mix of CPUs and accelerators, are of interest. Analysis of the semantics of different classes of parallel programming paradigms and their cost leads to DYCE (Distributed Yet Common Environment), a shared memory, rich but hardware friendly, race and deadlock free parallel programming paradigm that allows for resiliency without the need for explicit check-pointing code. Pointer based structures that span the memory of multiple heterogeneous compute devices are possible. Importantly, data exchange is independent of the specific data structures and does not require serialization and deserialization code, even for data structures such as a dynamic linked radix tree of strings. The analysis shows that DYCE does not require coherence from the system and thus can be executed with near minimal overhead and hardware requirements, including the page table cost for large unified address spaces that span many devices. We demonstrate efficacy with a prototype.