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to transfer data, and hence the seek requests will be blocked when the channel is busy with data transfers We consider that 1 The seek frequency is qs /s 2 The channels are busy with data transfer qbtt /Q of the available time 3 The average delay when encountering a data transfer activity is 1 btt 2 Then, in a period Q, the sum of the delays encountered when attempting to move seek commands to a controller or disk is the product of these three factors To obtain fus in terms of the seek load qs , as fus is used in Eq 5-8, the delays and the base load from Eq 5-11 give a factor fus = qs qbtt 1 1 btt qbtt P 2 btt q + fus = 2s Q + pc t s Q s 5-12
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With large values of btt, ie, large blocks, fast seeks, and active channels, this factor becomes quite large, perhaps adding 25% or more to the seek delays We nd that large block sizes can have signi cant detrimental e ects on the total channel capacity in class 3, 4, or 5 machines This secondary demand on channel capacity is frequently unjusti ably neglected, and has surprised people who expected better le performance from their systems
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An extreme case is the IBM implementation of ISAM on a 360-type computer The entire process of following the over ow chain is carried out by a loop in the channelcontrol program This reduces the load on the CPU but makes any shared access to other devices on the same channel during this period impossible Multiplexing capability has been introduced into the channel on the 370 series machines to mitigate this e ect
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In this section we have distributed the constituents of the demand over the appropriate hardware-component categories: disks, controllers, channels, and processors We still can expect to nd that the disk component is as heavily loaded as the estimate on the entire system originally indicated, since the disk units are required for all constituents of le activity We have not yet determined the extent of the bene cial e ect of multiple disks, channels, or processors 5-4-4 Load Distribution among Parallel Components Having parallel components, that is, multiple units of the same type, permits sharing of the load assigned to the type of device For instance, if there are two channels, each channel can be used to transmit data up to its own capacity, and it appears that the system s data-transmission capability could be doubled If there are four disk units, some of them can be seeking and others transmitting data, again greatly increasing the aggregate capability of the system Two factors have to be considered when an evaluation of the increase of system performance due to parallel components is to be made 1 The design of the applications has to distribute the service demands equally over the parallel components 2 The interference between simultaneous requests has to be assessed We will deal with both issues The problem of interference is the one which can be formally addressed The initial application load distribution requires much judgment
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The distribution of the load over parallel storage components has to balance the data quantity and the access rates to the data Load balancing takes place at several levels Parallel user activity Users who work during the same time period can have their private les assigned to distinct devices Parallel le activity Files used simultaneously by one application can be assigned to distinct devices This technique is common in sort programs Distribution of le fragments Fragments of a le, for instance, multiple indexes or pointer lists, can be placed on distinct devices, and the computation which accesses these sub les can initiate multiple processes to permit parallel utilization The discussion which follows will treat the assignment problem in the aggregate sense, and the result can be applied to any level above If there is no access load problem, the data les may simply be distributed so that the storage space is well utilized For dev parallel devices, the objective is to udi udj and D=
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