Is there a chance to increase speed with use of FE caching ?

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How to compute:
Average [Count] of each [AnyAttr] per each [Deciminute of day] in the
period Jan-Feb 2008 ?
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dimension [Time] for example Fri 13.4.2008 13:20
attributes
[Year]
[Month]
[Day]
[Hour]
[DeciMinute]
[DayOfWeek] ... Fri
[HourOfDay] ... 13
[DeciMinuteOfDay] ... 13:20
hierarchies
[YMDH]
[Year]
[Month]
[Day]
[Hour]
[DeciMinute]
dimension Any
attributes
[AnyAttr]

measures
[Count]

Following query is correct but too slow for large sets of AnyAttr.children.
Is there a chance to improve it using FE caching ? And how?

with
set [TimeUnits] as [YMDH].[DeciMinute]
member C as count([DeciMinuteOfDay] * [TimeUnits])
member [AvgCount] as [Count] / C
set [Rowset] as { [Any].[AnyAttr].children }
select
{ [DeciMinuteOfDay].children} * {[Count],[AvgCount]} on 0,
[Rowset] on 1
from
(select [YMDH].[2008].[Jan] : [YMDH].[2008].[Feb] on 0 from MYCUBE)

Thanks, Stanislav.