As processor and system manufacturers adjust their roadmaps towards increasing levels of both inter and intra-chip parallelism, so the urgency of reorienting the mainstream software industry towards these architectures grows.
At present, popular parallel and distributed programming methodologies are 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.
HLPP symposia provide a forum for discussion and research about such high-level approaches to parallel and distributed programming.
HLPP 2023 invites papers on all topics in high-level parallel programming, its tools and applications including, but not limited to, the following aspects:
- High-level parallel programming and performance models (e.g. BSP, CGM, LogP, MPM, etc.) and tools
- Declarative parallel and distributed programming methodologies based on functional, logical, data-flow, actor, and other paradigms
- Algorithmic skeletons, patterns, etc. and constructive methods
- High-level parallelism in programming languages and libraries (e.g, Haskell, Scala, C++, etc.): semantics and implementation
- Verification of declarative parallel and distributed programs
- Efficient code generation, auto-tuning and optimization for parallel and distributed programs
- Model-driven software engineering for parallel and distributed systems
- Domain-specific languages: design, implementation and applications
- High-level programming models for heterogeneous/hierarchical platforms with accelerators, e.g., GPU, Many-core, DSP, VPU, FPGA, etc.
- High-level parallel methods for large structured and semi-structured datasets
- Applications of parallel and distributed systems using high-level languages and tools
- Teaching experience with high-level tools and methods for parallel and distributed computing