Showing papers by "Rezaul Chowdhury published in 2017"

Provably Efficient Scheduling of Cache-oblivious Wavefront Algorithms

Abstract: Iterative wavefront algorithms for evaluating dynamic programming recurrences exploit optimal parallelism but show poor cache performance. Tiled-iterative wavefront algorithms achieve optimal cache complexity and high parallelism but are cache-aware and hence are not portable and not cache-adaptive. On the other hand, standard cache-oblivious recursive divide-and-conquer algorithms have optimal serial cache complexity but often have low parallelism due to artificial dependencies among subtasks. Recently, we introduced cache-oblivious recursive wavefront (COW) algorithms, which do not have any artificial dependencies, but they are too complicated to develop, analyze, implement, and generalize. Though COW algorithms are based on fork-join primitives, they extensively use atomic operations for ensuring correctness, and as a result, performance guarantees (i.e., parallel running time and parallel cache complexity) provided by state-of-the-art schedulers (e.g., the randomized work-stealing scheduler) for programs with fork-join primitives do not apply. Also, extensive use of atomic locks may result in high overhead in implementation. In this paper, we show how to systematically transform standard cache-oblivious recursive divide-and-conquer algorithms into recursive wavefront algorithms to achieve optimal parallel cache complexity and high parallelism under state-of-the-art schedulers for fork-join programs. Unlike COW algorithms these new algorithms do not use atomic operations. Instead, they use closed-form formulas to compute the time when each divide-and-conquer function must be launched in order to achieve high parallelism without losing cache performance. The resulting implementations are arguably much simpler than implementations of known COW algorithms. We present theoretical analyses and experimental performance and scalability results showing a superiority of these new algorithms over existing algorithms.

Autogen: Automatic Discovery of Efficient Recursive Divide-8-Conquer Algorithms for Solving Dynamic Programming Problems

Abstract: We present Autogen—an algorithm that for a wide class of dynamic programming (DP) problems automatically discovers highly efficient cache-oblivious parallel recursive divide-and-conquer algorithms from inefficient iterative descriptions of DP recurrences. Autogen analyzes the set of DP table locations accessed by the iterative algorithm when run on a DP table of small size and automatically identifies a recursive access pattern and a corresponding provably correct recursive algorithm for solving the DP recurrence. We use Autogen to autodiscover efficient algorithms for several well-known problems. Our experimental results show that several autodiscovered algorithms significantly outperform parallel looping and tiled loop-based algorithms. Also, these algorithms are less sensitive to fluctuations of memory and bandwidth compared with their looping counterparts, and their running times and energy profiles remain relatively more stable. To the best of our knowledge, Autogen is the first algorithm that can automatically discover new nontrivial divide-and-conquer algorithms.

POSTER: Provably Efficient Scheduling of Cache-Oblivious Wavefront Algorithms

Abstract: Standard cache-oblivious recursive divide-and-conquer algorithms for evaluating dynamic programming recurrences have optimal serial cache complexity but often have lower parallelism compared with iterative wavefront algorithms due to artificial dependencies among subtasks. Very recently cache-oblivious recursive wavefront (COW) algorithms have been introduced which do not have any artificial dependencies. Though COW algorithms are based on fork-join primitives, they extensively use atomic operations, and as a result, performance guarantees provided by state-of-the-art schedulers for programs with fork-join primitives do not apply. In this work, we show how to systematically transform standard cache-oblivious recursive divide-and-conquer algorithms into recursive wavefront algorithms to achieve optimal parallel cache complexity and high parallelism under state-of-the-art schedulers for fork-join programs. Unlike COW algorithms these new algorithms do not use atomic operations. Instead, they use closed-form formulas to compute at what time each recursive function must be launched in order to achieve high parallelism without losing cache performance. The resulting implementations are arguably much simpler than implementations of known COW algorithms.