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Efficient VLSI for Lempel-Ziv compression in wireless data communication networks

机译:无线数据通信网络中用于Lempel-Ziv压缩的高效VLSI

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We present a parallel algorithm, architecture, and implementation for efficient Lempel-Ziv (LZ)-based data compression. The parallel algorithm exhibits a scalable, parameterized, and regular structure and is well suited for VLSI array implementation. Based on our parallel algorithm and systematic design methodologies, two semisystolic array architectures have been developed which are low power and area efficient. The first architecture trades off the compression speed for the area and has a low run-time overhead for multichannel compression. The second architecture achieves a high compression rate (one data symbol per clock) at the expense of the area due to a large clock load and global wiring. Compared to a recent state-of-the-art parallel architecture, our first array structure requires significantly less chip area (/spl sime/330 k versus /spl sime/36 k transistors) and more than an order of magnitude less power (/spl ap/1.0 W versus /spl ap/70 mW) while still providing the compression speed required for most data communication applications. Hence, data compression can be adopted in portable data communication as well as wireless local area networks. The second architecture has at least three times less area and power while providing the same constant compression rate. To demonstrate the correctness of our design, a prototype module for the first architecture has been implemented using 1.2 /spl mu/ complementary metal-oxide-semiconductor (CMOS) technology. The compression module contains 32 simple and identical processors, has an average compression rate of 12.5 million bytes/s, and consumes 18.34 mW without the dictionary (/spl ap/70 mW with a 4.1k SRAM for the dictionary) while operating at a 100 MHz clock rate (simulated).
机译:我们提出了一种基于有效Lempel-Ziv(LZ)的数据压缩的并行算法,体系结构和实现。并行算法具有可伸缩,参数化和规则的结构,非常适合VLSI阵列的实现。基于我们的并行算法和系统设计方法,已开发出两种半收缩阵列架构,它们具有低功耗和高面积效率的特点。第一种体系结构折衷了该区域的压缩速度,并且多通道压缩的运行时开销较低。由于大的时钟负载和全局布线,第二种架构以面积为代价实现了高压缩率(每个时钟一个数据符号)。与最近的最新并行架构相比,我们的第一个阵列结构需要的芯片面积(/ spl sime / 330 k晶体管// spl sime / 36 k晶体管)显着减少,功耗也降低了一个数量级(/ spl ap / 1.0 W vs / spl ap / 70 mW),同时仍提供大多数数据通信应用所需的压缩速度。因此,可以在便携式数据通信以及无线局域网中采用数据压缩。第二种架构在提供相同的恒定压缩率的同时,面积和功耗至少减少了三倍。为了证明我们设计的正确性,已经使用1.2 / spl mu /互补金属氧化物半导体(CMOS)技术实现了第一个体系结构的原型模块。压缩模块包含32个简单且相同的处理器,平均压缩速率为1,250万字节/秒,不使用字典时功耗为18.34 mW(以字典为4.1k SRAM时为/ spl ap / 70 mW),而在100℃下运行MHz时钟速率(模拟)。

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