As processor and system manufacturers increase the amount of both inter- and intra-chip parallelism it becomes crucial to provide the software industry with high-level, clean and efficient tools for parallel programming. Parallel and distributed programming methodologies are currently dominated by low-level techniques such as send/receive message passing, or equivalently unstructured shared memory mechanisms. Higher-level, structured approaches offer many possible advantages and have a key role to play in the scalable exploitation of ubiquitous parallelism. Since 2001 the HLPP series of workshops/symposia has been a forum for researchers developing state-of-the-art concepts, tools and applications for high-level parallel programming. The general emphasis is on software quality, programming productivity and high-level performance models. The 9th Symposium on High-Level Parallel Programming and Applications will be held in Orléans, France.
Topics:
HLPP 2018 invites papers on all topics in high-level parallel programming, its tools and applications including, but not limited to, the following aspects:
-High-level programming, performance models (BSP, CGM, LogP, MPM, etc.) and tools
-Declarative parallel programming methodologies based on functional, logical, data-flow, and other paradigms
-Algorithmic skeletons, patterns, etc. and constructive methods
-High-level parallelism in programming languages and libraries (e.g, Haskell, Scala, etc.): semantics and implementation
-Verification of declarative parallel and distributed programs
-Efficient code generation, auto-tuning and optimization for parallel programming
-Model-driven software engineering for parallel systems
-Domain-specific languages: design, implementation and applications
-High-level programming models for heterogeneous/hierarchical platforms with accelerators, e.g., GPU, Xeon Phi, etc.
-High-level parallel methods for large structured and semi-structured datasets
-Applications of parallel systems using high-level languages and tools
-Teaching experience with high-level tools and methods