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The derivative of the scalar with respect to the matrix A is de ned by d d d da1n da11 da12 d d d da2n da21 d da22 (B54) = dA d d d damn dam1 dam2 For the scalar operation de ned by the trace, the following di erentiation formulas are useful: d trace(AB) dA d trace(ABA ) dA = B (AB must be square) (B55)

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Volatility is another signi cant consideration for multiple option strategies Buying multiple options in low volatility and entering a period of increasing volatility is an excellent strategy for multiple options When volatility is historically low, the most likely direction is up, and having several options to experience increases in premium value is certainly preferable to only one option When volatility is high, the multiple option strategy has a great deal more to lose because the vega is basically the same; when volatility is low, the multiple option strategy will have several times the vega rate as a single option position To calculate the delta on multiple options as one position, we just add the deltas together Then we can keep track of the positions as if they were a single position with a high delta In the example in Figure 45 the 1800 call has a delta of 58 per option or a total delta of 290 The multiple option strategy has an individual option delta of 40, but, when you combine the delta of 10 option the total delta equals 400 In the case of Microsoft stock, that represents 110 more shares worth of delta over the ve-call purchase

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(B must be symmetric) (B56)

B14

or latency in getting data to the CPUs You will see in tables appearing later in this chapter that the Intel CPUs in the Oracle Exadata Database Machine have continued to advance in processing power and number of cores Clearly, the closer data is to the CPUs in a system, the better the performance of queries and operations upon the data Closest to the CPUs are small amounts of memory called cache For example, Intel-based CPUs in the Oracle Exadata Database Machines contain multiple cache levels The Level 1 cache is smaller than the Level 2 cache on a per-core basis The smaller the cache size, the faster all of the information in the cache can be retrieved Today s Level 1 and Level 2 caches generally contain tens to hundreds of KB per core Since these cache sizes are so small, they typically contain data coherency objects and the like Where Level 3 cache is present, it can scale into a few MB and might contain some data Main memory in the database server nodes provides much more capacity For example, each database server node contains 96GB of memory in X2-2 nodes and 1TB of memory in X2-8 nodes The memory is linked to the CPUs via an on-die memory controller However, the amount of memory in an individual node or even a cluster is not enough to hold the volume of data needed in large-scale transaction and data warehousing systems by itself Disk storage devices are sized to hold the remaining data in an uncompressed state, a compressed state, or a combination of the two options Individual disks have grown in size to terabytes But as we noted previously, they are limited in delivering needed throughput To offset that, you ll observe that there are a large number of disks in the Database Machine More recently, an additional storage solution delivering a higher level of performance entered the picture in the form of flash solid-state storage The Sun flash technology in the Oracle Exadata Database Machine that is the Exadata Smart Flash Cache scales to more than 5TB of storage in a Full Rack configuration and provides much faster throughput It functions much like the cache in a conventional storage array, providing an important intermediate level of storage larger in capacity than memory but also providing more throughput than disk To assure the flash will not wear out prematurely, the flash controller hardware features wear leveling to assure writes and erase cycles are rotated among all of the blocks in the device (There are actually 32GB of pages on each Smart Flash Cache card for every 24GB of raw storage presented) Even where 25TB per day are written to flash in an Exadata Storage Server cell, the design point of supporting 100,000 write and/or erase cycles will not be exceeded in a five-year period.

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