Abstract. In the last few years, the traditional ways to keep the increase of hardware performance to the rate predicted by the Moore's Law have vanished. When uni-cores were the norm, hardware design was decoupled from the software stack thanks to a well defined Instruction Set Architecture (ISA). This simple interface allowed developing applications without worrying too much about the underlying hardware, while hardware designers were able to aggressively exploit instructionlevel parallelism (ILP) in superscalar processors. Current multi-cores are designed as simple symmetric multiprocessors (SMP) on a chip. However, we believe that this is not enough to overcome all the problems that multi-cores face. The runtime of the parallel application has to drive the design of future multi-cores to overcome the restrictions in terms of power, memory, programmability and resilience that multi-cores have. In the paper, we introduce a first approach towards a Runtime-Aware Architecture (RAA), a massively parallel architecture designed from the runtime's perspective.

Abstract-Managing criticality in task-based programming models opens a wide range of performance and power optimization opportunities in future manycore systems. Criticality aware task schedulers can benefit from these opportunities by scheduling tasks to the most appropriate cores. However, these schedulers may suffer from priority inversion and static binding problems that limit their expected improvements.Based on the observation that task criticality information can be exploited to drive hardware reconfigurations, we propose a Criticality Aware Task Acceleration (CATA) mechanism that dynamically adapts the computational power of a task depending on its criticality. As a result, CATA achieves significant improvements over a baseline static scheduler, reaching average improvements up to 18.4% in execution time and 30.1% in Energy-Delay Product (EDP) on a simulated 32-core system.The cost of reconfiguring hardware by means of a softwareonly solution rises with the number of cores due to lock contention and reconfiguration overhead. Therefore, novel architectural support is proposed to eliminate these overheads on future manycore systems. This architectural support minimally extends hardware structures already present in current processors, which allows further improvements in performance with negligible overhead. As a consequence, average improvements of up to 20.4% in execution time and 34.0% in EDP are obtained, outperforming state-of-the-art acceleration proposals not aware of task criticality.

Abstract-Cache coherence protocols limit the scalability of multicore and manycore architectures and are responsible for an important amount of the power consumed in the chip. A good way to alleviate these problems is to introduce a local memory alongside the cache hierarchy, forming a hybrid memory system. Local memories are more power-efficient than caches and do not generate coherence traffic, but they suffer from poor programmability. When non-predictable memory access patterns are found compilers do not succeed in generating code because of the incoherence between the two storages. This paper proposes a coherence protocol for hybrid memory systems that allows the compiler to generate code even in the presence of memory aliasing problems. Coherence is ensured by a software/hardware co-design where the compiler identifies potentially incoherent memory accesses and the hardware diverts them to the correct copy of the data. The coherence protocol introduces overheads of 0.26% in execution time and of 2.03% in energy consumption to enable the usage of the hybrid memory system, which outperforms cache-based systems by an speedup of 38% and an energy reduction of 27%.