• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2078-2094
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• 2015

Now a days, Efficient processing of Broadcast Queries is of critical importance with the ever-increasing deployment and use of mobile technologies. BQs have certain unique characteristics that the traditional spatial query processing in centralized databases does not address. In novel query processing technique, by maintaining high scalability and accuracy, latency is reduced considerably in answering BQs. Novel approach is based on peer-to-peer sharing, which enables us to process queries without delay at a mobile host by using query results cached in its neighboring mobile peers. We design and evaluate cooperative caching techniques to efficiently support data access in ad hoc networks. We first propose two schemes: Cache Data, which caches the data, and Cache Path, which caches the data path. After analyzing the performance of those two schemes, we propose a hybrid approach (Hybrid Cache), which can further improve the performance by taking advantage of Cache Data and Cache Path while avoiding their weaknesses. Cache replacement policies are also studied to further improve the performance. Simulation results show that the proposed schemes can significantly reduce the query delay and message complexity when compared to other caching schemes.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.99-107
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• 2020

In this paper, we analyze the characteristics of mobile cache, which is used to improve the data access speed when executing applications on mobile devices, and verify the importance of mobile cache through a cache data access experiment. The mobile device market has grown at a fast pace over the past decade; however, battery limitations and size, price considerations restrict the usage of fast hardware. Thus, their performance are supplemented by using a memory buffer structure such as the cache memory. The analysis mainly focuses on cache size, hierarchical structure of cache, cache replacement policy, and the effect these features has on mobile performance. For the experimental data, we applied a data set from a microprocessor system study, originally used to test the cache performance. In the experimental results, the average data access speed on a mobile device showed a performance improvement of up to 10 times with the presence of cache memory than without. Accordingly, the cache memory was helpful for the performance improvement of a mobile device when the specifications were identical.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.51-62
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• 2021

On-chip caches of graphics processing units (GPUs) have contributed to improved GPU performance by reducing long memory access latency. However, cache efficiency remains low despite the facts that recent GPUs have considerably mitigated the bottleneck problem of L1 data cache. Although the cache miss rate is a reasonable metric for cache efficiency, it is not necessarily proportional to GPU performance. In this study, we introduce a second key determinant to overcome the problem of predicting the performance gains from L1 data cache based on the assumption that miss rate only is not accurate. The proposed technique estimates the benefits of the cache by measuring the balance between cache efficiency and throughput. The throughput of the cache is predicted based on the warp occupancy information in the warp pool. Then, the warp occupancy is used for a second bypass phase when workloads show an ambiguous miss rate. In our proposed architecture, the L1 data cache is turned off for a long period when the warp occupancy is not high. Our two-level bypassing technique can be applied to recent GPU models and improves the performance by 6% on average compared to the architecture without bypassing. Moreover, it outperforms the conventional bottleneck-based bypassing techniques.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.6
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• pp.353-359
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• 2016

In this paper, we propose a high performance L1 cache structure for the high clock CPU. 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 reduce miss ratio, and a way-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 stored into the two-way set associative buffer. For the high performance and fast access time, we propose an one way among two ways set associative buffer is selectively accessed based on the way-select table (WST). According to simulation results, access time can be reduced by about 7% and 40% comparing with a direct cache and Intel i7-6700 with two times more space respectively.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.104-108
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• 2021

In order to improve performance in IoT, edge computing system, a memory is usually configured in a hierarchical structure. Based on the distance from CPU, the access speed slows down in the order of registers, cache memory, main memory, and storage. Similar to the change in performance, energy consumption also increases as the distance from the CPU increases. Therefore, it is important to develop a technique that places frequently used data to the upper memory as much as possible to improve performance and energy consumption. However, the technique should solve the problem of cache performance degradation caused by lack of spatial locality that occurs when the data access stride is large. This study proposes a technique to selectively place data with large data access stride to a software-controlled cache. By using the proposed technique, data spatial locality can be improved by reducing the data access interval, and consequently, the cache performance can be improved.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.72-79
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• 2010

In this paper, we propose the data cache architecture with a write buffer for a 32bit asynchronous embedded processor. The data cache consists of CAM and data memory. It accelerates data up lood cycle between the processor and the main memory that improves processor performance. The proposed data cache has 8 KB cache memory. The cache uses the 4-way set associative mapping with line size of 4 words (16 bytes) and pseudo LRU replacement algorithm for data replacement in the memory. Dirty register and write buffer is used for write policy of the cache. The designed data cache is synthesized to a gate level design using $0.13-{\mu}m$ process. Its average hit rate is 94%. And the system performance has been improved by 46.53%. The proposed data cache with write buffer is very suitable for a 32-bit asynchronous processor.

• KIISE Transactions on Computing Practices
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• v.23 no.6
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• pp.379-385
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• 2017

In enterprise environments, hybrid storage typically utilizes SSDs over disk-based RAID. Typically, SSDs over RAID are used as the data cache. Recently, the LeavO caching scheme was introduced to reduce the parity update overhead of the underlying RAID. In this paper, we combine the data caching and LeavO caching schemes and derive cost models of the combined cache to determine the optimal data and LeavO cache sizes. We also propose the Adaptive Combined Cache that dynamically adjusts the data cache and LeavO cache sizes for evolving workloads. Experimental results show that the performance of the Adaptive Combined Cache is significantly superior to that of the conventional data caching scheme and is comparable with that of the off-line optimal scheme.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.945-951
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• 2008

In this paper, a new high performance data cache scheme that improves exploitation of both the spatial and temporal locality is proposed. The proposed data cache consists of a hardware prefetch unit and two sub-caches such as a direct-mapped (DM) cache with a large block size and a fully associative buffer with a small block size. Spatial locality is exploited by fetching and storing large blocks into a direct mapped cache, and is enhanced by prefetching a neighboring block when a DM cache hit occurs. Temporal locality is exploited by storing small blocks from the DM cache in the fully associative buffer according to their activity in the DM cache when they are replaced. Experimental results on Spec2000 programs show that the proposed scheme can reduce the average miss ratio by $12.53%\sim23.62%$ and the AMAT by $14.67%\sim18.60%$ compared to the previous schemes such as direct mapped cache, 4-way set associative cache and SMI(selective mode intelligent) cache[8].

• The KIPS Transactions:PartA
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• v.13A no.2 s.99
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• pp.101-110
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• 2006

One of the most effective ways to improve cache performance is to exploit both temporal and spatial locality given by any program executional characteristics. This paper proposes a data cache with small space for low power but high performance on multimedia applications. The basic architecture is a split-cache consisting of a direct-mapped cache with small block sire and a fully-associative buffer with large block size. To overcome the disadvantage of small cache space, two mechanisms are enhanced by considering operational behaviors of multimedia applications: an adaptive multi-block prefetching to initiate various fetch sizes and an efficient block filtering to remove rarely reused data. The simulations on MediaBench show that the proposed 5KB-cache can provide equivalent performance and reduce energy consumption up to 40% as compared with 16KB 4-way set associative cache.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.1-6
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• 2015

The MapReduce Program of Hadoop Distributed File System operates on any unspecified nodes due to distributed-parallel process and block replicate for data stability. Since it is difficult to guarantee the cache locality when a Solid State Drive is used as a cache in hadoop, cache hit-rate is decreased. In this paper, we suggest a method to improve cache hit rate by pre-loading the input data of the MapReduce onto the SSD cache. To perform this method, we estimated the blocks that are used on each node by using capacity scheduler and block metadata. Eventually we could increase the performance of SSD cache by loading the blocks onto SSD cache before the Map Task run.