By analyzing the characteristics of energy consumption in wireless sensor networks, this study finds out that the pivotal aspect in controlling energy consumption is the media access control protocol, and introduces the media access control protocol of typical wireless sensor network in various categories, meanwhile, abstractly divides the context of use into three conditions. Based on the OPNET, this paper simulates different scenarios in terms of the energy consumption and delay performance under the varieties of protocol, generating the result that none of them could provide the optimal performance in the different scenarios. Therefore, for the sake of adapting into complex application scenarios, it is necessary to develop the media access control protocol with further improvements, in terms of the general applicability or business mode with adaptive ability.

This paper advocates a lifetime-aware progressive programming concept to improve single-level per cell NAND flash memory write endurance. NAND flash memory program/erase (P/E) cycling gradually degrades memory cell storage noise margin, and sufficiently strong fault tolerance must be used to ensure the memory P/E cycling endurance. As a result, the relatively large cell storage noise margin in early memory lifetime is essentially wasted in conventional design practice. This paper proposes to always fully utilize the available cell storage noise margin by adaptively adjusting the number of storage levels per cell, and progressively use these levels to realize multiple 1-bit programming operations between two consecutive erase operations. This simple progressive programming design concept is realized by two different implementation strategies, which are discussed and compared in detail. On the basis of an approximate NAND flash memory device model, we carried out simulations to quantitatively evaluate this design concept. The results show that it can improve the write endurance by 35.9% and in the meanwhile improve the average programming speed by 12% without sacrificing read speed.

Future flash-based solid-state drives (SSDs) must employ increasingly powerful error correction code (ECC) and digital signal processing (DSP) techniques to compensate the negative impact of technology scaling on NAND flash memory device reliability. Currently, all the ECC and DSP functions are implemented in a central SSD controller. However, the use of more powerful ECC and DSP makes such design practice subject to significant speed performance degradation and complicated controller implementation. An EZ-NAND (Error Zero NAND) flash memory design strategy is emerging in the industry, which moves all the ECC and DSP functions to each memory chip. Although EZ-NAND flash can simplify controller design and achieve high system speed performance, its high silicon cost may not be affordable for large-capacity SSDs in computing systems. We propose a quasi-EZ-NAND design strategy that hierarchically distributes ECC and DSP functions on both NAND flash memory chips and the central SSD controller. Compared with EZ-NAND design concept, it can maintain almost the same speed performance while reducing silicon cost overhead. Assuming the use of low-density parity-check (LDPC) code and postcompensation DSP technique, trace-based simulations show that SSDs using quasi-EZ-NAND flash can realize almost the same speed as SSDs using EZ-NAND flash, and both can reduce the average SSD response time by over 90 percent compared with conventional design practice. Silicon design at 65 nm node shows that quasi-EZ-NAND can reduce the silicon cost overhead by up to 44 percent compared with EZ-NAND.

This brief presents a NAND Flash memory wear-leveling algorithm that explicitly uses memory raw bit error rate (BER) as the optimization target. Although NAND Flash memory wear-leveling has been well studied, all the existing algorithms aim to equalize the number of programming/erase cycles among all the memory blocks. Unfortunately, such a conventional design practice becomes increasingly suboptimal as inter-block variation becomes increasingly significant with the technology scaling. This brief presents a dynamic BER-based greedy wear-leveling algorithm that uses BER statistics as the measurement of memory block wear-out pace, and guides dynamic memory block data swapping to fully maximize the wear-leveling efficiency. Simulations have been carried out to quantitatively demonstrate its advantages over existing wear-leveling algorithms.

As new nonvolatile memory technologies become increasingly mature, there has been a growing interest on investigating their use in future field-programmable gate arrays (FPGAs). Similar to existing FPGAs with embedded Flash memory, future FPGAs can embed these new nonvolatile memories to persistently store configuration data. By comparing with prior work, we first propose the more appropriate design style for new nonvolatile configuration data storage memory. Moreover, this brief studies a dynamic random-access memory (DRAM)-based FPGA design strategy enabled by high-density embedded nonvolatile memory. Existing FPGAs do not use on-chip DRAM cells for configuration data storage mainly because DRAM self-refresh involves destructive DRAM read. This problem can be solved, if we use embedded nonvolatile memory as primary FPGA configuration data storage and externally refresh on-chip DRAM cells. Analysis and simulations have been carried out to demonstrate the potential advantages of such a design strategy.

This paper advocates a quasi-nonvolatile solid-state drive (SSD) design strategy for enterprise applications. The basic idea is to trade data retention time of NAND flash memory for other system performance metrics including program/erase (P/E) cycling endurance and memory programming speed, and meanwhile use explicit internal data refresh to accommodate very short data retention time (e.g., few weeks or even days). We also propose SSD scheduling schemes to minimize the impact of internal data refresh on normal I/O requests. Based upon detailed memory cell device modeling and SSD system modeling, we carried out simulations that clearly show the potential of using this simple quasi-nonvolatile SSD design strategy to improve system cycling endurance and speed performance. We also performed detailed energy consumption estimation, which shows the energy consumption overhead induced by data refresh is negligible.

Today and future NAND flash memory will heavily rely on system-level fault-tolerance techniques such as error correction code (ECC) to ensure the overall system storage integrity. Since ECC demands the storage of coding redundancy and hence degrades effective cell storage efficiency, it is highly desirable to use more powerful coding solutions that can maintain the system storage reliability at less coding redundancy. This has motivated a growing interest in the industry to search for alternatives to BCH code being used in today. Regardless to specific ECCs, it is of great practical importance to know the theoretical limit on the achievable cell storage efficiency, which motivates this work. We first develop an approximate NAND flash memory channel model that explicitly incorporates program/erase (P/E) cycling effects and cell-to-cell interference, based on which we then develop strategies for estimating the information-theoretical bounds on cell storage efficiency. We show that it can readily reveal the tradeoffs among cell storage efficiency, P/E cycling endurance, and retention limit, which can provide important insights for system designers. Finally, motivated by the dynamics of P/E cycling effect revealed by the information-theoretical study, we propose two memory system design techniques that can improve the average NAND flash memory programming speed and increase the total amount of user data that can be stored in NAND flash cell over its entire lifetime.

Motivated by the emerging three-dimensional (3D integration technologies, this paper studies the potential of applying 3D memory stacking to enable FPGA devices use on-chip DRAM cells to store configuration data. In current design practice, FPGAs do not use on-chip DRAM cells for configuration data storage mainly because on-chip DRAM self-refreshing involves destructive DRAM read operations. This problem can be solved if we use a 3D stacked memory as primary FPGA configuration data storage and externally refresh on-chip DRAM cells. Since the 3D stacked memory can easily store multiple sets of configuration data, it can meanwhile enable high-speed FPGA dynamic reconfiguration. In this paper, we study such DRAM-based FPGA design enabled by 3D memory stacking and investigate potential design issues, and employ the VPR tool set to demonstrate that DRAM-based FPGAs can noticeably reduce FPGA die area and hence improve speed and energy consumption performance, compared their SRAM-based counterparts.

This work studies the potential of using emerging 3D integration to improve embedded VLIW computing system. We focus on the 3D integration of one VLIW processor die with multiple high-capacity DRAM dies. Our proposed memory architecture employs 3D stacking technology to bond one die containing several processing clusters to multiple DRAM dies for a primary memory. The 3D technology also enables wide low-latency buses between clusters and memory and enable the latency of 3D DRAM L2 cache comparable to 2D SRAM L2 cache. These enable it to replace the 2D SRAM L2 cache with 3D DRAM L2 cache. The die area for 2D SRAM L2 cache can be re-allocated to additional clusters that can improve the performance of the system. From the simulation results, we find 3D stacking DRAM main memory can improve the system performance by 10%~80% than 2D off-chip DRAM main memory depending on different benchmarks. Also, for a similar logic die area, a four clusters system with 3D DRAM L2 cache and 3D DRAM main memory outperforms a two clusters system with 2D SRAM L2 cache and 3D DRAM main memory by about 10%.