Edit Distance is a classic family of dynamic programming problems, among which Time Warp Edit Distance refines the problem with the notion of a metric and temporal elasticity. A novel Improved Time Warp Edit Distance algorithm that is both massively parallelizable and requiring only linear storage is presented. This method uses the procession of a three diagonal band to cover the original dynamic program space. Every element of the diagonal update can be computed in parallel. The core method is a feature of the TWED Longest Common Subsequence data dependence and is applicable to dynamic programs that share similar band subproblem structure. The algorithm has been implemented as a CUDA C library with Python bindings. Speedups for challenging problems are phenomenal.

Improved Time Warp Edit Distance -- A Parallel Dynamic Program in Linear Memory