Bounding Cache Miss Costs of Multithreaded Computations Under General Schedulers

We analyze the caching overhead incurred by a class of multithreaded algorithms when scheduled by an arbitrary scheduler. We obtain bounds that match or improve upon the well-known $O(Q+S \cdot (M/B))$ caching cost for the randomized work stealing (RWS) scheduler, where $S$ is the number of steals, $Q$ is the sequential caching cost, and $M$ and $B$ are the cache size and block (or cache line) size respectively.Comment: Extended abstract in Proceedings of ACM Symp. on Parallel Alg. and Architectures (SPAA) 2017, pp. 339-350. This revision has a few small updates including a missing citation and the replacement of some big Oh terms with precise constant

Heterogeneous multithreaded computing

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.by Howard J. LuM.Eng

Performance driven distributed scheduling of parallel hybrid computations

AbstractExascale computing is fast becoming a mainstream research area. In order to realize exascale performance, it is necessary to have efficient scheduling of large parallel computations with scalable performance on a large number of cores/processors. The scheduler needs to execute in a pure distributed and online fashion, should follow affinity inherent in the computation and must have low time and message complexity. Further, it should also avoid physical deadlocks due to bounded resources including space/memory per core. Simultaneous consideration of these factors makes affinity driven distributed scheduling particularly challenging. We attempt to address this challenge for hybrid parallel computations which contain tasks that have pre-specified affinity to a place and also tasks that can be mapped to any place in the system. Specifically, we address two scheduling problems of the type Pm|Mj,prec|Cmax. This paper presents online distributed scheduling algorithms for hybrid parallel computations assuming both unconstrained and bounded space per place. We also present the time and message complexity for distributed scheduling of hybrid computations. To the best of our knowledge, this is the first time that distributed scheduling algorithms for hybrid parallel computations have been presented and analyzed for time and message bounds under both unconstrained space and bounded space

Efficient and Reasonable Object-Oriented Concurrency

Making threaded programs safe and easy to reason about is one of the chief difficulties in modern programming. This work provides an efficient execution model for SCOOP, a concurrency approach that provides not only data race freedom but also pre/postcondition reasoning guarantees between threads. The extensions we propose influence both the underlying semantics to increase the amount of concurrent execution that is possible, exclude certain classes of deadlocks, and enable greater performance. These extensions are used as the basis an efficient runtime and optimization pass that improve performance 15x over a baseline implementation. This new implementation of SCOOP is also 2x faster than other well-known safe concurrent languages. The measurements are based on both coordination-intensive and data-manipulation-intensive benchmarks designed to offer a mixture of workloads.Comment: Proceedings of the 10th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE '15). ACM, 201

Porting the Sisal functional language to distributed-memory multiprocessors

Parallel computing is becoming increasingly ubiquitous in recent years. The sizes of application problems continuously increase for solving real-world problems. Distributed-memory multiprocessors have been regarded as a viable architecture of scalable and economical design for building large scale parallel machines. While these parallel machines can provide computational capabilities, programming such large-scale machines is often very difficult due to many practical issues including parallelization, data distribution, workload distribution, and remote memory latency. This thesis proposes to solve the programmability and performance issues of distributed-memory machines using the Sisal functional language. The programs written in Sisal will be automatically parallelized, scheduled and run on distributed-memory multiprocessors with no programmer intervention. Specifically, the proposed approach consists of the following steps. Given a program written in Sisal, the front end Sisal compiler generates a directed acyclic graph(DAG) to expose parallelism in the program. The DAG is partitioned and scheduled based on loop parallelism. The scheduled DAG is then translated to C programs with machine specific parallel constructs. The parallel C programs are finally compiled by the target machine specific compilers to generate executables. A distributed-memory parallel machine, the 80-processor ETL EM-X, has been chosen to perform experiments. The entire procedure has been implemented on the EMX multiprocessor. Four problems are selected for experiments: bitonic sorting, search, dot-product and Fast Fourier Transform. Preliminary execution results indicate that automatic parallelization of the Sisal programs based on loop parallelism is effective. The speedup for these four problems is ranging from 17 to 60 on a 64-processor EM-X. Preliminary experimental results further indicate that programming distributed-memory multiprocessors using a functional language indeed frees the programmers from lowl-evel programming details while allowing them to focus on algorithmic performance improvement

Parallel and Distributed Data Series Processing on Modern and Emerging Hardware

This paper summarizes state-of-the-art results on data series processing with the emphasis on parallel and distributed data series indexes that exploit the computational power of modern computing platforms. The paper comprises a summary of the tutorial the author delivered at the 15th International Conference on Management of Digital EcoSystems (MEDES'23).Comment: This paper will appear in the Proceedings of the 15th International Conference on Management of Digital EcoSystems (MEDES'23