This WG will promote new sustainable programming and execution models in the context of rapidly changing underlying computing architecture. The participants will explore synergies among emerging programming models and run-times from HPC, distributed systems, and big data management communities. The efforts will focus on improving the programmability of future systems that will likely reach substantially higher levels of concurrency and have heterogeneous architectures. This WG will explore programming models and run-times that facilitate the task of scaling and extracting performance on continuous evolving platforms, while providing resilience and fault-tolerant mechanisms to tackle the increasing probability of failures throughout the whole software stack. Further, this WG fill focus on data centric computing, as the increasing data demands of applications from various domains require novel programming paradigms and run- times for efficiency processing data, while keeping the energy consumption within acceptable budgets.
Key objectives: Scale handling (optimal usage of resources, faults), improve programmability, adaptation to rapidly changing underlying computing architecture, data-centric programming models, resilience, energy-efficiency
Topics: programming run-times for adapting to failures and load variability, trade-offs among programmability, performance, scalability and energy-efficiency.
|A Cloudification Methodology for Numerical Simulations.< .||Download|