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Re: Problem with large arrays
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Jonathan Bromley <(E-Mail Removed)> wrote:
> On Thu, 17 Nov 2005 20:01:54 +0000 (UTC), Removed) wrote:

> >Hi,
> >
> >I am having trouble with a design that is trying to use a large array: the
> >elaboration tool (Cadence's NCelab) says that the limit is 2^22 locations (I
> >am trying to using an array of signals that is just slightly larger) for the
> >32-bit tool. I tried the 64-bit tool (limit of 2^52) but it says it doesn't
> >have enough disk space for intermediate files (I only have 100MB available).

> Why do you need the gigantic array? Typically you need it to model a
> large external memory. No sensible simulation will access *every*
> location of this very large memory. So the correct approach is to
> model only those locations that are actually used in the simulation.

I am not modeling external memory, but I need to store a lookup table in a
design unit and it will actually be part of the design. This is only because I
want to compare the cost-performance of using a large lookup table versus
using an approximation method: I know this will be a horrible large design, but
I have to do it for comparison purposes.

Previously, instead of signals I used variables and the snapshot was not any
bigger than the approximation method, most likely due to the optimizations
you are describing (it only seemed to store those values that were actually
used). However, now I want to separate the part updating the table from the
part performing control based on value in the table and I think a signal is the
only sythesizeable way to accomplish this. The simulation is of course now much
larger, but synthesis results should not change. Would a shared variable be
synthesizeable (only one process writes, the other only reads)?

I got the 32-bit tool to work by manually partitioning the array (the 64-bit
tool requires more [2x?] space and this would have been very bad, see below).

> In VHDL this is fairly straightforward to do, since you can create
> dynamically-allocated data structures; but it is a non-trivial
> programming problem to make it work really well. Naive approaches
> are likely to simulate rather slowly.

> Generally this idea is known as "sparse memory". I know that NC
> supports sparse memory models in Verilog; I'm not sure about VHDL.
> Trawl through the NC help documentation looking for "sparse memory"
> and see if there's an out-of-the-box solution. If there isn't,
> then my preferred approach for memory modelling is this:

> * Split the memory address (as a bit pattern) into two halves,
> "row address" and "column address". (For a DRAM these have an
> obvious counterpart in the RAM itself, but that's not important.)
> * Make a table of pointers (access type) indexed by the row address,
> so that each pointer points to one row. However, at startup you
> initialise all these pointers to NULL because no rows have yet been
> allocated.
> * When your simulation makes a write access to the memory, find the
> row address pointer. If it's NULL, then this is the very first
> write to any location in that row and you must allocate a new
> row data structure and make the pointer point to it. A row
> data structure is of course just an array of memory locations
> indexed by the column address. Now that you have the real row,
> you can write to the appropriate location in it.
> * On a write access, if the row address pointer is not NULL then
> you've already created that row and it's easy to write to the
> appropriate location in that row.
> * On a read access, if the row address pointer is NULL then you
> know that the corresponding row has never been written and you
> simply return (others => 'U') as the result. But if the row
> exists, you can read the appropriate location in it.

> This technique works really well if the pattern of accesses to
> your memory shows some locality - in other words, if you access
> a location then there's a high probability of accessing other
> nearby locations. It's fast - each access costs only one lookup
> in the table of row address pointers, a dereference of that pointer
> and then a second array access into the row data structure. But
> it works very badly if the pattern of accesses into the memory
> is random or tends to go in columns, because you end up creating
> many row data structures each containing only one or two useful
> locations. If you have that kind of problem, a hashing approach
> will work better. I'm not going to try to explain that here
> --

Thanks for outlining this technique though: it will be useful for my testbench
for this project (which just happens to be a memory controller)! However,
it seems that the NC tools have some way of doing this when it involves
variables (maybe something to do with keeping a history for signals).

Also, it turn out simulation speed is not diminished by the big array of
signals, just that it eats memory (I used some temporary space and it requires
over 300MB -- and this is using the smaller 32-bit tool).

> Jonathan Bromley, Consultant

> DOULOS - Developing Design Know-how
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