Abstract: Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.
Abstract: An approach and its implementation in 0.18 m CMOS process of the multichannel ASIC for capacitive (up to 30 pF) sensors are described in the paper. The main design aim was to study an analog data-driven architecture. The design was done for an analog derandomizing function of the 128 to 16 structure. That means that the ASIC structure should provide a parallel front-end readout of 128 input analog sensor signals and after the corresponding fast commutation with appropriate arbitration logic their processing by means of 16 output chains, including analog-to-digital conversion. The principal feature of the ASIC is a low power consumption within 2 mW/channel (including a 9-bit 20Ms/s ADC) at a maximum average channel hit rate not less than 150 kHz.
Abstract: Block replacement algorithms to increase hit ratio
have been extensively used in cache memory management. Among
basic replacement schemes, LRU and FIFO have been shown to be
effective replacement algorithms in terms of hit rates. In this paper,
we introduce a flexible stack-based circuit which can be employed in
hardware implementation of both LRU and FIFO policies. We
propose a simple and efficient architecture such that stack-based
replacement algorithms can be implemented without the drawbacks
of the traditional architectures. The stack is modular and hence, a set
of stack rows can be cascaded depending on the number of blocks in
each cache set. Our circuit can be implemented in conjunction with
the cache controller and static/dynamic memories to form a cache
system. Experimental results exhibit that our proposed circuit
provides an average value of 26% improvement in storage bits and its
maximum operating frequency is increased by a factor of two
Abstract: In this paper, a new robust audio fingerprinting
algorithm in MP3 compressed domain is proposed with high
robustness to time scale modification (TSM). Instead of simply
employing short-term information of the MP3 stream, the new
algorithm extracts the long-term features in MP3 compressed domain
by using the modulation frequency analysis. Our experiment has
demonstrated that the proposed method can achieve a hit rate of
above 95% in audio retrieval and resist the attack of 20% TSM. It has
lower bit error rate (BER) performance compared to the other
algorithms. The proposed algorithm can also be used in other
compressed domains, such as AAC.
Abstract: Currently, web usage make a huge data from a lot of
user attention. In general, proxy server is a system to support web
usage from user and can manage system by using hit rates. This
research tries to improve hit rates in proxy system by applying data
mining technique. The data set are collected from proxy servers in the
university and are investigated relationship based on several features.
The model is used to predict the future access websites. Association
rule technique is applied to get the relation among Date, Time, Main
Group web, Sub Group web, and Domain name for created model.
The results showed that this technique can predict web content for the
next day, moreover the future accesses of websites increased from
38.15% to 85.57 %.
This model can predict web page access which tends to increase
the efficient of proxy servers as a result. In additional, the
performance of internet access will be improved and help to reduce
traffic in networks.