Castell: a heterogeneous cmp architecture scalable to hundreds of processors

• Autores: Felipe Cabarcas Jaramillo
• Directores de la Tesis: Mateo Valero Cortés (dir. tes.), Alejandro Ramírez Bellido (dir. tes.)
• Lectura: En la Universitat Politècnica de Catalunya (UPC) ( España ) en 2011
• Idioma: inglés
• Tribunal Calificador de la Tesis: Eduard Ayguadé Parra (presid.), Xavier Martorell Bofill (secret.), Georgi Nedeltchev Gaydadjiev (voc.), Miquel Pericàs Gleim (voc.), Osman Unsal García (voc.)
• Materias:
  • Ciencias tecnológicas
    • Tecnología de los ordenadores
      • Arquitectura de ordenadores
• Enlaces
  • Tesis en acceso abierto en: TDX
• Resumen

  • Technology improvements and power constrains have taken multicore architectures to dominate microprocessor designs over uniprocessors. At the same time, accelerator based architectures have shown that heterogeneous multicores are very efficient and can provide high throughput for parallel applications, but with a high-programming effort. We propose Castell a scalable chip multiprocessor architecture that can be programmed as uniprocessors, and provides the high throughput of accelerator-based architectures. Castell relies on task-based programming models that simplify software development. These models use a runtime system that dynamically finds, schedules, and adds hardware-specific features to parallel tasks. One of these features is DMA transfers to overlap computation and data movement, which is known as double buffering. This feature allows applications on Castell to tolerate large memory latencies and lets us design the memory system focusing on memory bandwidth. In addition to provide programmability and the design of the memory system, we have used a hierarchical NoC and added a synchronization module. The NoC design distributes memory traffic efficiently to allow the architecture to scale. The synchronization module is a consequence of the large performance degradation of application for large synchronization latencies. Castell is mainly an architecture framework that enables the definition of domain-specific implementations, fine-tuned to a particular problem or application. So far, Castell has been successfully used to propose heterogeneous multicore architectures for scientific kernels, video decoding (using H.264), and protein sequence alignment (using Smith-Waterman and clustalW). It has also been used to explore a number of architecture optimizations such as enhanced DMA controllers, and architecture support for task-based programming models. iii