• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.1-8
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• 2013

TIn this paper, we propose a high performance L1 cache structure on the high clock CPU of 4GHz. The proposed cache memory consists of three parts, i.e., a direct-mapped cache to support fast access time, a two-way set associative buffer to exploit temporal locality, and a buffer-select table. The most recently accessed data is stored in the direct-mapped cache. If a data has a high probability of a repeated reference, when the data is replaced from the direct-mapped cache, the data is selectively stored into the two-way set associative buffer. For the high performance and low power consumption, we propose an one way among two ways set associative buffer is selectively accessed based on the buffer-select table(BST). According to simulation results, Energy $^*$ Delay product can improve about 45%, 70% and 75% compared with a direct mapped cache, a four-way set associative cache, and a victim cache with two times more space respectively.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.277-278
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• 2010

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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• pp.158-166
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• 2008

These days, mobile embedded systems adopt flash memory capable of XIP feature since they can reduce memory usage, power consumption, and software load time. XIP provides direct access to ROM and flash memory for processors. However, using XIP incurs unnecessary degradation of applications' performance because direct access to ROM and flash memory shows more delay than that to main memory. In this paper, we propose a memory management framework, dynamic XIP, which can resolve the performance degradation of using XIP. Using a constrained RAM cache, dynamic XIP can dynamically change XIP region according to page access pattern to reduce performance degradation in execution time or energy consumption resulting from native XIP problem. The proposed framework consists of a page profiler gathering applications' memory access pattern using PMU and an XIP manager deciding that a page is accessed whether in main memory or in flash memory. The proposed framework is implemented and evaluated in Linux kernel. Our evaluation shows that our framework can reduce execution time at most 25% and energy consumption at most 22% compared with using XIP-only case adopted in general mobile embedded systems. Moreover, the evaluation shows that in execution time and energy consumption, our modified LRU algorithm with code page filters can reduce more than at most 90% and 80% respectively compared with applying just existing LRU algorithm to dynamic XIP.

• KIISE Transactions on Computing Practices
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• v.20 no.9
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• pp.483-491
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• 2014

Contemporary computer systems exploits DVFS (Dynamic Voltage/Frequency Scaling) technology for balancing performance and power consumption. The efficiency of DVFS depends on how much performance we get for larger power consumption due to elevated CPU frequency. Especially for memory-bounded applications, higher CPU frequency often does not result in higher performance. In this paper, we present an upper bound of CPU frequency scaling based on memory accesses. It is observed that the performance gain due to higher CPU frequency is limited by memory accesses (last level cache misses) per instructions by experiments. Using the results, we present the CPU frequency upper bound with little performance gain. Experimental results show that for a memory-bounded application, applying the frequency upper bound enhances the energy efficiency of the application by above 30%.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.1-11
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• 2021

This paper proposes a novel mechanism called Event-driven Uncore Frequency Scaler (eUFS) to improve the energy efficiency of the HPC systems. UFS exploits the hardware events such as LAPI (Last-level Cache Accesses Per Instructions) and CPI (Clock Cycles Per Instruction) to dynamically adjusts the uncore frequency. Hardware events are collected at a reference time period, and the target uncore frequency is determined using the collected event and the previous uncore frequency. Experiments with the NPB benchmarks demonstrate that the eUFS reduces the energy consumption by 6% on average for class C and D NPB benchmarks while it only increases the execution time by 2% on average.

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

• ETRI Journal
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• v.42 no.4
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• pp.468-479
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• 2020

The proposed AI processor architecture has high throughput for accelerating the neural network and reduces the external memory bandwidth required for processing the neural network. For achieving high throughput, the proposed super thread core (STC) includes 128 × 128 nano cores operating at the clock frequency of 1.2 GHz. The function-safe architecture is proposed for a fault-tolerance system such as an electronics system for autonomous cars. The general-purpose processor (GPP) core is integrated with STC for controlling the STC and processing the AI algorithm. It has a self-recovering cache and dynamic lockstep function. The function-safe design has proved the fault performance has ASIL D of ISO26262 standard fault tolerance levels. Therefore, the entire AI processor is fabricated via the 28-nm CMOS process as a prototype chip. Its peak computing performance is 40 TFLOPS at 1.2 GHz with the supply voltage of 1.1 V. The measured energy efficiency is 1.3 TOPS/W. A GPP for control with a function-safe design can have ISO26262 ASIL-D with the single-point fault-tolerance rate of 99.64%.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.367-376
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• 2007

In this paper, we introduce an application-specific and adaptive power management technique for portable systems that support dynamic voltage scaling (DVS). We exploit both the idle time of multitasking systems running soft real-time tasks as well as memory- or CPU-bound code regions. Detailed power and execution time profiles guide an adaptive power manager (APM) that is linked to the operating system. A post-pass optimizer marks candidate regions for DVS by inserting calls to the APM. At runtime, the APM monitors the CPU's performance counters to dynamically determine the affinity of the each marked region. for each region, the APM computes the optimal voltage and frequency setting in terms of energy consumption and switches the CPU to that setting during the execution of the region. Idle time is exploited by monitoring system idle time and switching to the energy-wise most economical setting without prolonging execution. We show that our method is most effective for periodic workloads such as video or audio decoding. We have implemented our method in a multitasking operating system (Microsoft Windows CE) running on an Intel XScale-processor. We achieved up to 9% of total system power savings over the standard power management policy that puts the CPU in a low Power mode during idle periods.