This book introduces new compilation techniques, using the polyhedron
model for the resource-adaptive parallel execution of loop programs on
massively parallel processor arrays. The authors show how to compute
optimal symbolic assignments and parallel schedules of loop iterations
at compile time, for cases where the number of available cores becomes
known only at runtime. The compile/runtime symbolic parallelization
approach the authors describe reduces significantly the runtime
overhead, compared to dynamic or just‐in-time compilation. The new,
on‐demand fault‐tolerant loop processing approach described in this book
protects loop nests for parallel execution against soft errors.