Repara 2018 - International Workshop on Reengineering for Parallelism in Heterogeneous Parallel Platforms

In recent years, traditional processors have not been able to directly translate chip fabrication technology advances intro performance gains. To keep satisfying the demand for computing power, there is a shift from homogeneous machines to heterogeneous highly parallel architectures combining different kinds of processors (CPUs, GPUs, DSPs, FPGAs, and other accelerators). While this approach has allowed significant performance and energy efficiency benefits, heterogeneous systems are often highly difficult to program with existing tools. To reduce the cost of system development, reengineering techniques emerge as a solution which may help to balance ease-of-development with better performance, better reliability, and lower maintenance costs.
The RePara 2018 workshop aims to join experts from related disciplines to share recent advances in different areas contributing to better transformation of new and legacy applications to different programming models for diverse computing devices in the context of parallel heterogeneous architectures.
Scope and Interests
Topics of interest include, but are not limited to:
High-level parallel programming models, libraries and languages for heterogeneous platforms
Description languages for Heterogeneous Parallel Platforms
Parallel patterns for Heterogeneous Platforms
Autonomic management of Power/Performance tradeoffs
Automated parallel kernel identification and assessment in existing, sequential code
Software refactoring approaches for parallel programming models
Transformations from source code to reconfigurable hardware
Integration of FPGA accelerators into refactored software
Runtimes for software coordination in heterogeneous parallel platforms
Performance modeling and prediction in heterogeneous parallel platforms
Energy efficiency monitoring and prediction in heterogeneous parallel platforms
Software quality assessment in parallel programming models with special attention to maintainability
Applying partitioning and mapping for parallel heterogeneous computing architectures
Application experiences of refactoring to software in industrial domains