• Journal of KIISE:Computer Systems and Theory
• /
• v.37 no.1
• /
• pp.43-54
• /
• 2010

The existing timeout based cache leakage management techniques reduce the leakage energy consumption of the cache significantly by switching off the power supply to the inactive cache line. Since these techniques were mainly proposed for single-processor systems, their efficiency is reduced significantly in multiprocessor systems with a shared L2 cache because of the cache interferences among simultaneously executing tasks. In this paper, we propose a novel cache partition strategy which partitions the shared L2 cache considering the inactive cycles of the cache line. Furthermore, we propose the adaptive task-aware timeout management technique which considers the characteristics of each task and adapts the timeout dynamically. Experimental results from the simulation show that the proposed technique reduces the leakage energy consumption of the shared L2 cache by 73% for the 2-way CMP and 56% for the 4-way CMP on average compared to the existing representative leakage management technique, respectively.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.4
• /
• pp.108-116
• /
• 2013

Many algorithms have been introduced to improve performance by using massively parallel systems, which consist of several hundreds of processors. A typical example is a GPU system of many processors which uses shared memory. In the case of image filtering algorithms, which make references to neighboring points, the shared memory helps improve performance by frequently accessing adjacent pixels. However, using shared memory requires rewriting the existing codes and consequently results in complexity of the codes. Recent GPU systems support both L1 and L2 cache along with shared memory. Since the L1 cache memory is located in the same area as the shared memory, the improvement of performance is predictable by using the cache memory. In this paper, the performance of cache and shared memory were compared. In conclusion, the performance of cache-based algorithm is very similar to the one of shared memory. The complexity of the code appearing in a shared memory system, however, is resolved with the cache-based algorithm.

• Journal of Computing Science and Engineering
• /
• v.7 no.4
• /
• pp.285-299
• /
• 2013

To enable hard real-time systems to take advantage of multicore processors, it is crucial to obtain the worst-case execution time (WCET) for programs running on multicore processors. However, this is challenging and complicated due to the inter-thread interferences from the shared resources in a multicore processor. Recent research used the combined cache conflict graph (CCCG) to model and compute the worst-case inter-thread interferences on a shared L2 cache in a multicore processor, which is called the CCCG-based approach in this paper. Although it can compute the WCET safely and accurately, its computational complexity is exponential and prohibitive for a large number of cores. In this paper, we propose three counter-based approaches to significantly reduce the complexity of the multicore WCET analysis, while achieving absolute safety with tightness close to the CCCG-based approach. The basic counter-based approach simply counts the worst-case number of cache line blocks mapped to a cache set of a shared L2 cache from all the concurrent threads, and compares it with the associativity of the cache set to compute the worst-case cache behavior. The enhanced counter-based approach uses techniques to enhance the accuracy of calculating the counters. The hybrid counter-based approach combines the enhanced counter-based approach and the CCCG-based approach to further improve the tightness of analysis without significantly increasing the complexity. Our experiments on a 4-core processor indicate that the enhanced counter-based approach overestimates the WCET by 14% on average compared to the CCCG-based approach, while its averaged running time is less than 1/380 that of the CCCG-based approach. The hybrid approach reduces the overestimation to only 2.65%, while its running time is less than 1/150 that of the CCCG-based approach on average.

• Journal of Computing Science and Engineering
• /
• v.7 no.1
• /
• pp.67-80
• /
• 2013

The worst-case execution time (WCET) of each real-time task in multicore processors with shared caches can be significantly affected by inter-thread cache interferences. The worst-case inter-thread cache interferences are dependent on how tasks are scheduled to run on different cores. Therefore, there is a circular dependence between real-time task scheduling, the worst-case inter-thread cache interferences, and WCET in multicore processors, which is not the case for single-core processors. To address this challenging problem, we present an offline real-time scheduling approach for multicore processors by considering the worst-case inter-thread interferences on shared L2 caches. Our scheduling approach uses a greedy heuristic to generate safe schedules while minimizing the worst-case inter-thread shared L2 cache interferences and WCET. The experimental results demonstrate that the proposed approach can reduce the utilization of the resulting schedule by about 12% on average compared to the cyclic multicore scheduling approaches in our theoretical model. Our evaluation indicates that the enhanced scheduling approach is more likely to generate feasible and safe schedules with stricter timing constraints in multicore real-time systems.

• Journal of Computing Science and Engineering
• /
• v.5 no.2
• /
• pp.131-140
• /
• 2011

Different cores typically share the last-level cache in a multi-core processor. Threads running on different cores may interfere with each other. Therefore, the multi-core worst-case execution time (WCET) analyzer must be able to safely and accurately estimate the worst-case inter-thread cache interference. This is not supported by current WCET analysis techniques that manly focus on single thread analysis. This paper presents a novel approach to analyze the worst-case cache interference and bounding the WCET for threads running on multi-core processors with shared L2 instruction caches. We propose to use an interference matrix to model inter-thread interference, on which basis we can calculate the worst-case inter-thread cache interference. Our experiments indicate that the proposed approach can give a worst-case bound less than 1%, as in benchmark fib-call, and an average 16.4% overestimate for threads running on a dual-core processor with shared-L2 cache. Our approach dramatically improves the accuracy of WCET overestimatation by on average 20.0% compared to work.

• IEIE Transactions on Smart Processing and Computing
• /
• v.4 no.2
• /
• pp.78-82
• /
• 2015

General-purpose graphics processing units (GPGPUs) provide tremendous computational and processing power. Despite the latency hiding mechanism, a GPU architecture requires high memory bandwidth and lower latency between computational units and the memory system. For this reason, the current GPU architecture has private L1 caches in each core and a shared L2 cache to increase performance by reducing memory latency. But in some cases, this CPU-like cache design is not suitable for GPGPUs. In this paper, we analyze detailed cache performance related to GPGPU application characteristics, and suggest technical alternatives for the GPGPU architecture as future work.

• Journal of Computing Science and Engineering
• /
• v.5 no.1
• /
• pp.1-18
• /
• 2011

As the first step toward real-time multi-core computing, this paper presents a novel approach to bounding the worst-case performance for threads running on multi-core processors with shared L2 instruction caches. The idea of our approach is to compute the worst-case instruction access interferences between different threads based on the program control flow information of each thread, which can be statically analyzed. Our experiments indicate that the proposed approach can reasonably estimate the worst-case shared L2 instruction cache misses by considering the inter-thread instruction conflicts. Also, the worst-case execution time (WCET) of applications running on multi-core processors estimated by our approach is much better than the estimation by simply assuming all L2 instruction accesses are misses.

• Journal of Computing Science and Engineering
• /
• v.6 no.1
• /
• pp.12-25
• /
• 2012

For real-time systems it is important to obtain the accurate worst-case execution time (WCET). Furthermore, how to improve the WCET of applications that run on multicore processors is both significant and challenging as the WCET can be largely affected by the possible inter-core interferences in shared resources such as the shared L2 cache. In order to solve this problem, we propose an innovative approach that adopts a code positioning method to reduce the inter-core L2 cache interferences between the different real-time threads that adaptively run in a multi-core processor by using different strategies. The worst-case-oriented strategy is designed to decrease the worst-case WCET among these threads to as low as possible. The other two strategies aim at reducing the WCET of each thread to almost equal percentage or amount. Our experiments indicate that the proposed multicore-aware code positioning approaches, not only improve the worst-case performance of the real-time threads but also make good tradeoffs between efficiency and fairness for threads that run on multicore platforms.

• Journal of Computing Science and Engineering
• /
• v.6 no.4
• /
• pp.267-278
• /
• 2012

The state-of-the-art techniques in multicore timing analysis are limited to analyze multicores with shared instruction caches only. This paper proposes a uniform framework to analyze the worst-case performance for both shared instruction caches and data caches in a multicore platform. Our approach is based on a new concept called address flow graph, which can be used to model both instruction and data accesses for timing analysis. Our experiments, as a proof-of-concept study, indicate that the proposed approach can accurately compute the worst-case performance for real-time threads running on a dual-core processor with a shared L2 cache (either to store instructions or data).

• Journal of Computing Science and Engineering
• /
• v.9 no.2
• /
• pp.51-72
• /
• 2015

Time predictability is crucial in hard real-time and safety-critical systems. Cache memories, while useful for improving the average-case memory performance, are not time predictable, especially when they are shared in multicore processors. To achieve time predictability while minimizing the impact on performance, this paper explores several time-predictable scratch-pad memory (SPM) based architectures for multicore processors. To support these architectures, we propose the dynamic memory objects allocation based partition, the static allocation based partition, and the static allocation based priority L2 SPM strategy to retain the characteristic of time predictability while attempting to maximize the performance and energy efficiency. The SPM based multicore architectural design and the related allocation methods thus form a comprehensive solution to hard real-time multicore based computing. Our experimental results indicate the strengths and weaknesses of each proposed architecture and the allocation method, which offers interesting on-chip memory design options to enable multicore platforms for hard real-time systems.