The proposed technique completely reduces the LPM problem to only three search cycles in proposed TCAM memory architecture. Difference in search cycle time has been observed to be comparable to the conventional TCAM. Functionality of modified cell is verified by simulating 32-bit TCAM word in UMC 180 nm technology in Spectre. To implement the proposed method for LPM, TCAM cell is modified by including two control transistors which control connection of cell either with Bit Match Line (BML) or with Word Match Line (WML). This has advantage in large capacity routing tables as proposed technique uses a priority encoder only of size equal to the number of bits in destination address to find the longest prefix length. eliminates the priority encoder needed to find the longest prefix match in conventional techniques. The proposed architecture eliminates sorting of table entries during table update. In this paper we propose a new Ternary Content Addressable Memory (TCAM) based system architecture for the LPM problem in routers. Network Routers find most defined path for an arriving packet by the destination address in the packet using longest prefix matching (LPM) with Routing table entries. We find that with hardware support Bankshot can offer upto 5x speedup over conventional caching systems. We evaluate several design decisions in Bankshot including different cache management policies and different levels of hardware, software support for tracking dirty data and maintaining meta-data. We propose Bankshot, a caching architecture that allows cache hits to bypass the OS (and the associated software overheads) entirely, while relying on the OS for heavy-weight operations like servicing misses and performing write backs. flash-based SSDs) introduce significant software overhead that can obscure the performance benefits of faster memories. Existing storage caching architectures (even those that use fast. The density and price gap between NVMs and denser storage make NVM economically most suitable as a cache for larger, more conventional storage (i.e., NAND flashbased SSDs and disks). View full-textĮmerging non-volatile storage (e.g., Phase Change Memory, STTRAM) allow access to persistent data at latencies an order of magnitude lower than SSDs. To show the potential of instruction-based prediction we propose and evaluate four different optimizations: i) a migratory sharing optimization, ii) a wide sharing optimization iii) a pairwise sharing optimization, and i. In contrast, address-based prediction typically requires storage proportional to the memory and/or cache size. The advantage of this technique is that it requires very few hardware resources in the form of very small prediction tables per node. optimizing transparent shared-memory where prediction -in the form of adaptive cache coherence protocols- is typically address-based. Although this technique is well established in the uniprocessor world it has not been widely applied for. Instruction-based prediction is based on observing the behavior of load and store instructions in relation to coherent events and predicting their future behavior. Optomicrofluidics (read more at ) employs photonics in conjunction with microfluidics, whose applications range from use in sensors to type lab-on-chips.Ī complete list of 50 INFO subprojects can be seen here.In this paper we propose Instruction-based Prediction as a means to optimize directory-based cache coherent NUMA shared-memory. Nonlinear Photonics can be defined as the junction of some traditional areas of optics, particularly nonlinear optics (read more in ), whose scientific development has generated devices and applications in the field of photonics, such as sources of supercontinuum generation, optical harmonics or optical amplifiers in bulk or integrated devicesīiophotonics (read more at ) is a multidisciplinary area of interface between photonics and biomedical areas, with important social impact. In these three sub-areas, 50 sub-projects are led by the INFO researchers, with 23 sub-projects in Non-Linear Photonics, Devices and Applications 17 sub-projects in Biophotonics and 10 sub-projects in Optomicrofluidics.
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