High-performance microprocessors, e.g., multithreaded and multicore processors, are being implemented in embedded real-time systems because of the increasing computational requirements. These complex microprocessors have two major drawbacks when they are used for real-time purposes. First, their complexity difficults the calculation of the WCET (worst case execution time). Second, power consumption requirements are much larger, which is a major concern in these systems. In this paper we propose a novel soft power-aware real-time scheduler for a state-of-the-art multicore multithreaded processor, which implements dynamic voltage scaling techniques. The proposed scheduler reduces the energy consumption while satisfying the constraints of soft real-time applications. Different scheduling alternatives have been evaluated, and experimental results show that using a fair scheduling policy, the proposed algorithm provides, on average, energy savings ranging from 34% to 74%.

Technology projections indicate that static power will become a major concern in future generations of high-performance microprocessors. Caches represent a significant percentage of the overall microprocessor die area. Therefore, recent research has concentrated on the reduction of leakage current dissipated by caches. The variety of techniques to control current leakage can be classified as non-state preserving or state preserving. Non-state preserving techniques power off selected cache lines while state preserving place selected lines into a low-power state. Drowsy caches are a recently proposed state-preserving technique. In order to introduce low performance overhead, drowsy caches must be very selective on which cache lines are moved to a drowsy statePast research on cache organization has focused on how best to exploit the temporal locality present in the data stream. In this paper we propose a novel drowsy cache policy called Reuse Most Recently used On (RMRO), which makes use of reuse information to trade off performance versus energy consumption. Our proposal improves the hit ratio for drowsy lines by about 67%, while reducing the power consumption by about 11.7% (assuming 70nm technology) with respect to previously proposed drowsy cache policies.

The Last Level Cache (LLC) plays a key role in the system performance of current multi-cores by reducing the number of long latency main memory accesses. The inter-application interference at this shared resource, however, can lead the system to undesired situations regarding performance and fairness. Recent approaches have successfully addressed fairness and turnaround time (TT) in commercial processors. Nevertheless, these approaches must face sustaining system performance, which is challenging. This work makes two main contributions. Firstly, LLC behaviors regarding cache performance, data reuse and cache occupancy, that adversely impact on the final performance are identified. Secondly, based on these behaviors, we propose the Critical-Phase Aware Partitioning Approach (CPA), which reduces TT while sustaining (and even improving) IPC by making an effective use of the LLC space. Experimental results show that CPA outperforms CA, Dunn and KPart state-of-the-art approaches, and improves TT (over 40% in some workloads) over Linux default behavior while sustaining or even improving IPC by more than 3% in several mixes.

To improve chip multiprocessor (CMP) performance, recent research has focused on scheduling strategies to mitigate main memory bandwidth contention. Nowadays, commercial CMPs implement multilevel cache hierarchies that are shared by several multithreaded cores. In this microprocessor design, contention points may appear along the whole memory hierarchy. Moreover, this problem is expected to aggravate in future technologies, since the number of cores and hardware threads, and consequently the size of the shared caches increase with each microprocessor generation. This paper characterizes the impact on performance of the different contention points that appear along the memory subsystem. The analysis shows that some benchmarks are more sensitive to contention in higher levels of the memory hierarchy (e.g., shared L2) than to main memory contention. In this paper, we propose two generic scheduling strategies for CMPs. The first strategy takes into account the available bandwidth at each level of the cache hierarchy. The strategy selects the processes to be coscheduled and allocates them to cores to minimize contention effects. The second strategy also considers the performance degradation each process suffers due to contention-aware scheduling. Both proposals have been implemented and evaluated in a commercial single-threaded quad-core processor with a relatively small two-level cache hierarchy. The proposals reach, on average, a performance improvement by 5.38 and 6.64 percent when compared with the Linux scheduler, while this improvement is by 3.61 percent for an state-of-the-art memory contention-aware scheduler under the evaluated mixes.

SRAM and DRAM cells have been the predominant technologies used to implement memory cells in computer systems, each one\ud having its advantages and shortcomings. SRAM cells are faster and require no refresh since reads are not destructive. In contrast,\ud DRAM cells provide higher density and minimal leakage energy since there are no paths within the cell from Vdd to ground. Recently, DRAM cells have been embedded in logic-based technology, thus overcoming the speed limit of typical DRAM cells. In this paper we propose an n-bit macrocell that implements one static cell, and n-1 dynamic cells. This cell is aimed at being used in an n-way set-associative first-level data cache. Our study shows that in a four-way set-associative cache with this macrocell\ud compared to an SRAM based with the same capacity, leakage is reduced by about 75% and area more than half with a minimal impact\ud on performance. Architectural mechanisms have also been devised to avoid refresh logic. Experimental results show that no performance is lost when the retention time is larger than 50K processor cycles. In addition, the proposed delayed writeback policy that avoids refreshing performs\ud a similar amount of writebacks than a conventional cache with the same organization, so no power wasting is incurred.Postprint (published version

Advanced hardware prefetch engines are being integrated in current high-performance processors. Prefetching can boost the performance of most applications, however, the induced bandwidth consumption can lead the system to a high contention for main memory bandwidth, which is a scarce resource in current multicores. In such a case, the system performance can be severely damaged. This work characterizes the applications’ behavior in an IBM POWER8 machine, which presents many prefetch settings,varying the bandwidth contention degree. The study reveals that the best prefetch setting for each application depends on the main memory bandwidth availability, that is, it depends on the co-running applications. Based on this study, we propose Bandwidth-AwarePrefetch Configuration (BAPC) a scalable adaptive prefetching algorithm that improves the performance of multi-program workloads. BAPC increases the performance of the applications in a 8%, 11%, and 12% for workload mixes composed of 6, 8, and 10 applications over the IBM POWER8 default configuration. In addition to performance, BAPC reduces bandwidth consumption in 39%, 42%, and 45%, respectively.