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Seeding: What does it mean in UVM context?


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hi,

to explain this is a long story :-) anyway...

if your testbench methodology relies upon random stimulus it also has to rely on "random stability". this means that calls to randomize/srandom/random will yield the same stream of data as long as possible. SV itself does a bad job in preserving the random stability so its likely that changing your tb infrastructure in a minimal sense can change the overall behaviour. you can imagine that this is a killer for any application (think of adding a monitor to your testbench does change the whole scenario).

so uvm+ovm in its core have an algorithm which assigns a seed to any uvm_object computed from a type+logical path+a counter. by doing that each object delivers the same stream of random vales as long possible - adding/removing topology should not have any influence anymore.

so by default you should stick to the use_uvm_seeding which enables this builtin random stability.

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hi,

to explain this is a long story :-) anyway...

if your testbench methodology relies upon random stimulus it also has to rely on "random stability". this means that calls to randomize/srandom/random will yield the same stream of data as long as possible. SV itself does a bad job in preserving the random stability so its likely that changing your tb infrastructure in a minimal sense can change the overall behaviour. you can imagine that this is a killer for any application (think of adding a monitor to your testbench does change the whole scenario).

so uvm+ovm in its core have an algorithm which assigns a seed to any uvm_object computed from a type+logical path+a counter. by doing that each object delivers the same stream of random vales as long possible - adding/removing topology should not have any influence anymore.

so by default you should stick to the use_uvm_seeding which enables this builtin random stability.

Thanks Uwes. That was helpful.

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