• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.546-553
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• 2015

Recently, flash cache is widely adopted as the performance accelerator of legacy storage systems. Unlike other cache media, flash cache should be carefully managed as it has peculiar characteristics such as long write latency and limited P/E cycles. In particular, we make two prominent observations that can be utilized in managing flash cache. First, a serious worn-out problem happens when the working-set of a system is beyond the capacity of flash cache due to excessively frequent cache replacement. Second, more than 50% of data has no hit in flash cache as it is a second level cache. Based on these observations, we propose a cache admission control policy that does not cache data when it is first accessed, and inserts it into the cache only after its second access occurs within a certain time window. This allows the filtering of data disruptive to flash cache in terms of endurance and performance. With this policy, we prolong the lifetime of flash cache 2.3 times without any performance degradations.

• Journal of Computing Science and Engineering
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• v.11 no.2
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• pp.69-77
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• 2017

Recent GPUs have adopted cache memory to benefit general-purpose GPU (GPGPU) programs. However, unlike CPU programs, GPGPU programs typically have considerably less temporal/spatial locality. Moreover, the L1 data cache is used by many threads that access a data size typically considerably larger than the L1 cache, making it critical to bypass L1 data cache intelligently to enhance GPU cache performance. In this paper, we examine GPU cache access behavior and propose a simple hardware-based GPU cache bypassing method that can be applied to GPU applications without recompiling programs. Moreover, we introduce a hybrid method that integrates static profiling information and hardware-based bypassing to further enhance performance. Our experimental results reveal that hardware-based cache bypassing can boost performance for most benchmarks, and the hybrid method can achieve performance comparable to state-of-the-art compiler-based bypassing with considerably less profiling cost.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.123-133
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• 2017

Cache performance is an important factor in hardware system. We proceed with a cache simulation to analyze the cache performance suitable for sound rendering. In addition, we introduce hardware models based on ray tracing used in geometric method and studies to improve cache performance. Cache simulation is performed on various conditions for cache size, way and block. Various simulations can be found to influence the cache hit rate. We compare cache simulation results with actual hardware performance to analyze cache performance suitable for sound rendering.

• 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.7 no.3
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• pp.129-134
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• 2012

The objective of cache is to reduce I/O access of physical storage device so that user accesses their data faster. Traditionally, the most important metric to measure the performance of cache is hitratio. Thus, when the cache maintains hitratio high, it is regarded as a good cache replacement policy. However, the cache miss latency is different when the storages are heterogeneous. Though the cache hitratio is high, if the cache often misses with low performance disk, then the user experiences low performance. To address this problem we proposed eviction cost estimation based cache management. In our result, the eviction cost estimation based cache management has 10~30% throughput improvement compared with LRU cache management.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.802-810
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• 1997

In this paper, the performance of direce mapping caches, 2_, 4_, 8_, .., 4096_way way set associative caches, and fully assiciative caches are analyized by trace simulation for verivying their effectiveness.In general, it is well known that as n, the number of main memory lines to be stored into one cache line number in direct mapping cache, increases, the performance of the cache memory should get higher linearly.According to our analysis, however, it is not true on all the cache organizations.It is shown that as n increases, miss ratios get lower only when the small cache(less than 256K) using large line size is used.It is also shown that fully associative mapping achieves high performance only when small size cache using large line size ia used.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.1
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• pp.80-90
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• 2016

Thanks to superior leakage energy efficiency compared to SRAM cells, STTRAM cells are considered as a promising alternative for a memory element in on-chip caches. However, the main disadvantage of STTRAM cells is high write energy and latency. In this paper, we propose a low-cost write filter (WF) cache which resides between the load/store queue and STTRAM-based L1 data cache. To maximize efficiency of the WF cache, the line allocation and access policies are optimized for reducing energy consumption of STTRAM-based L1 data cache. By efficiently filtering the write operations in the STTRAM-based L1 data cache, our proposed WF cache reduces energy consumption of the STTRAM-based L1 data cache by up to 43.0% compared to the case without the WF cache. In addition, thanks to the fast hit latency of the WF cache, it slightly improves performance by 0.2%.

• 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 KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.463-476
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• 2006

R-trees have been traditionally optimized for the I/O performance with the disk page as the tree node. Recently, researchers have proposed cache-conscious variations of R-trees optimized for the CPU cache performance in main memory environments, where the node size is several cache lines wide and more entries are packed in a node by compressing MBR keys. However, because there is a big difference between the node sizes of two types of R-trees, disk-optimized R-trees show poor cache performance while cache-optimized R-trees exhibit poor disk performance. In this paper, we propose a cache and disk optimized R-tree, called the PR-tree (Prefetching R-tree). For the cache performance, the node size of the PR-tree is wider than a cache line, and the prefetch instruction is used to reduce the number of cache misses. For the I/O performance, the nodes of the PR-tree are fitted into one disk page. We represent the detailed analysis of cache misses for range queries, and enumerate all the reasonable in-page leaf and nonleaf node sizes, and heights of in-page trees to figure out tree parameters for best cache and I/O performance. The PR-tree that we propose achieves better cache performance than the disk-optimized R-tree: a factor of 3.5-15.1 improvement for one-by-one insertions, 6.5-15.1 improvement for deletions, 1.3-1.9 improvement for range queries, and 2.7-9.7 improvement for k-nearest neighbor queries. All experimental results do not show notable declines of the I/O performance.