This 4 th generation Alpha microprocessor running at 1.2GHz delivers up to 44.8GB/s chip pin bandwidth. It contains a 1.75MB, ECC protected, 7-way set associative 2 nd level write back-cache that delivers 19.2GB/s bandwidth; two memory controllers supporting 8 Rambus™ channels running at 800Mb/s; four 6.4GB/s inter-processor communication ports; and a separate IO port capable of 6.4GB/s operation. The 21.1x18.8mm 2 chip contains 152M transistors and dissipates 125W at 1.5V. It is packaged in a 1443-pin LGA package and air-cooled. It is fabricated in a 0.18µm, bulk CMOS process with 7 levels of copper interconnect. The chip is partitioned into four clocking domains and uses digital delay line loop to provide low skew, controlled edge rate, synchronous clocks across the chip. Figure 15.6.1 shows the major functional units. The CPU of the chip is leveraged from an earlier Alpha design [1,2].The Level-2 Cache Controller Unit manages the L2 cache and coordinates with the memory controllers and the router to service memory fills and cache coherence requests. It queues up to 16 Level-1 cache miss addresses, 16 L1/L2 victim addresses, 35 cache coherence requests and response addresses, and 4 write IO addresses. The address queues are implemented in a single 73entry Address Register File with multiple read, write and CAM ports (Figure 15.6.2). The data can be read or written every cycle from the top or bottom of the register file to minimize routing distance. The entry status bits are stored in a separate array. The address queues and status arrays generate up to 25 requests that the arbiter dynamically schedules onto 6 unique resources every cycle.Misses from local or remote processors arrive at the memory controller and are stored in two 32-entry Directory In Flight Tables (DIFT). Incoming transactions are compared against pending DIFT entries. Depending on the result of the CAM lookup, the transaction is either serialized to avoid hazards, or merged to deliver a response to a pending transaction, or a new entry is created. The DIFT tracks the coherence state for 32 possible outstanding transactions. The DIFT issue logic picks 1 of these 32 arbitrating entries. A scoreboard tracks the availability of 3 physical resources, which are used by 5 different classes of transactions. The issue logic is pipelined over 2 cycles and accounts for entries selected from the previous cycle. The DIFT can issue to the 3 resources each cycle, one of which is the DRAM controller ( Figure 15.6.3). The DIFT arbiter can pick an entry each cycle while avoiding deadlock and maintaining fairness.The DRAM controller (Figure 15.6.4) has a conflict-detection pipeline that maximizes parallelism and minimizes DRAM bank conflicts. It translates the request address into device, bank, row, and column fields optimized for the RDRAM™ configuration in the 1st cycle. It indexes a table that tracks open pages and active banks in the RDRAMs and determines the appropriate action in the memory system in the 2 nd cycle. It then compares the address against a 2...

In this paper, a new population based hybrid meta-heuristic algorithm called the Hybrid Whale-Particle Swarm Optimization Algorithm (HWPSO) for solving complex optimization problems has been proposed. The proposed algorithm tries to overcome the limitations associated in a Particle Swarm Optimization (PSO) exploration phase i.e. Stagnation Effect, by hybridizing with a whale optimization algorithm (WOA) in a novel way as WOA has been reported to have very good exploration capability. During hybridization, two novel techniques have been employed, namely 'Forced' Whale and 'Capping' Phenomenon. The 'Forced' WOA is introduced in exploration phase and it enables the WOA to guide PSO for better local optima avoidance and concurrently a new 'Capping' phenomenon is employed which restricts the WOA search mechanism during exploitation phase, thereby converging the solution faster to a global optimum value. The performance of the proposed HWPSO has tested on 18 benchmark mathematical functions and 3 Electronics Design Optimization problems. The simulation results indicate that the proposed algorithm outperforms many state of the art algorithms by achieving a better optima with a very low standard deviation for most of the benchmark functions used. The effectiveness of the proposed HWPSO has been also validated by statistical as well as complexity analysis. The performance of HWPSO algorithm is also found to be satisfactory in all three cases of electronics design optimization problems, which have been further validated with standard design tools and found to be in close agreement with each other.

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The performance of a fiber-optic sensor and its overall cost depend on the packaging of the sensor. Alignment of different optical, optoelectronic, and mechanical components is a key problem in the package design of a fiber-optic sensor. An intensity based fiber-optic sensor that can be used as a refractive-index or displacement sensor is considered as a case study in analyzing the effects of alignment on the performance of a fiber-optic sensor. Alignability of this sensor package is defined and calculated, taking into account the coupling efficiency and effects of various misalignments. Guidelines for making the package so that the fiber-optic sensor works more efficiently are developed from our calculations.

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