Towards a streaming model for nested data parallelism
Frederik M. Madsen, Andrzej Filinski · 2013
The language-integrated cost semantics for nested data parallelism pioneered by NESL provides an intuitive, high-level model for predicting performance and scalability of parallel algorithms with reasonable accuracy. However, this predictability, obtained through a uniform, parallelism-flattening execution strategy, comes at the price of potentially prohibitive space usage in the common case of computations with an excess of available parallelism, such as dense-matrix multiplication.