The recent patch to defer substitutions on V3Gate crashes on circular
logic that has cycle length >= 3 with all inlineable signals (cycle
length 2 is detected correctly and is not inlined). Fix by stopping
recursion at the loop-back edge.
Fixes#3543
Adds timing support to Verilator. It makes it possible to use delays,
event controls within processes (not just at the start), wait
statements, and forks.
Building a design with those constructs requires a compiler that
supports C++20 coroutines (GCC 10, Clang 5).
The basic idea is to have processes and tasks with delays/event controls
implemented as C++20 coroutines. This allows us to suspend and resume
them at any time.
There are five main runtime classes responsible for managing suspended
coroutines:
* `VlCoroutineHandle`, a wrapper over C++20's `std::coroutine_handle`
with move semantics and automatic cleanup.
* `VlDelayScheduler`, for coroutines suspended by delays. It resumes
them at a proper simulation time.
* `VlTriggerScheduler`, for coroutines suspended by event controls. It
resumes them if its corresponding trigger was set.
* `VlForkSync`, used for syncing `fork..join` and `fork..join_any`
blocks.
* `VlCoroutine`, the return type of all verilated coroutines. It allows
for suspending a stack of coroutines (normally, C++ coroutines are
stackless).
There is a new visitor in `V3Timing.cpp` which:
* scales delays according to the timescale,
* simplifies intra-assignment timing controls and net delays into
regular timing controls and assignments,
* simplifies wait statements into loops with event controls,
* marks processes and tasks with timing controls in them as
suspendable,
* creates delay, trigger scheduler, and fork sync variables,
* transforms timing controls and fork joins into C++ awaits
There are new functions in `V3SchedTiming.cpp` (used by `V3Sched.cpp`)
that integrate static scheduling with timing. This involves providing
external domains for variables, so that the necessary combinational
logic gets triggered after coroutine resumption, as well as statements
that need to be injected into the design eval function to perform this
resumption at the correct time.
There is also a function that transforms forked processes into separate
functions.
See the comments in `verilated_timing.h`, `verilated_timing.cpp`,
`V3Timing.cpp`, and `V3SchedTiming.cpp`, as well as the internals
documentation for more details.
Signed-off-by: Krzysztof Bieganski <kbieganski@antmicro.com>
Various optimizations to speed up MTasks coarsening (which is the long
pole in the multi-threaded scheduling of very large designs).
The biggest impact ones:
- Use efficient hand written Pairing Heaps for implementing priority
queues and the scoreboard, instead of the old SortByValueMap. This
helps us avoid having to sort a lot of merge candidates that we will
never actually consider and helps a lot in performance.
- Remove unnecessary associative containers and store data structures
(the heap nodes in particular) directly in the object they relate to.
This eliminates a huge amount of lookups and helps a lot in
performance.
- Distribute storage for SiblingMC instances into the LogicMTask
instances, and combine with the sibling maps. This again eliminates
hash table lookups and makes storage structures smaller.
- Remove some now bidirectional edge maps, keep only the forward map.
There are also some other smaller optimizations:
- Replaced more unnecessary dynamic_casts with static_casts
- Templated some functions/classes to reduce the number of static
branches in loops.
- Improves sorting of edges for sibling candidate creation
- Various micro-optimizations here and there
This speeds up MTask coarsening by 3.8x on a large design, which
translates to a 2.5x speedup of the ordering pass in multi-threaded
mode. (Combined with the earlier optimizations, ordering is now 3x
faster.)
Due to the elimination of a lot of the auxiliary data structures, and
ensuring a minimal size for the necessary ones, memory consumption of
the MTask coarsening is also reduced (measured up to 4.4x reduction
though the accuracy of this is low).
The algorithm is identical except for minor alterations of the order
some candidates are added or removed, this can cause perturbation in the
output due to tied scores being broken based on IDs.
Various optimizations to speed up MTasks coarsening (which is the long
pole in the multi-threaded scheduling of very large designs).
The biggest impact ones:
- Use efficient hand written Pairing Heaps for implementing priority
queues and the scoreboard, instead of the old SortByValueMap. This
helps us avoid having to sort a lot of merge candidates that we will
never actually consider and helps a lot in performance.
- Remove unnecessary associative containers and store data structures
(the heap nodes in particular) directly in the object they relate to.
This eliminates a huge amount of lookups and helps a lot in
performance.
- Distribute storage for SiblingMC instances into the LogicMTask
instances, and combine with the sibling maps. This again eliminates
hash table lookups and makes storage structures smaller.
- Remove some now bidirectional edge maps, keep only the forward map.
There are also some other smaller optimizations:
- Replaced more unnecessary dynamic_casts with static_casts
- Templated some functions/classes to reduce the number of static
branches in loops.
- Improves sorting of edges for sibling candidate creation
- Various micro-optimizations here and there
This speeds up MTask coarsening by 3.8x on a large design, which
translates to a 2.5x speedup of the ordering pass in multi-threaded
mode. (Combined with the earlier optimizations, ordering is now 3x
faster.)
Due to the elimination of a lot of the auxiliary data structures, and
ensuring a minimal size for the necessary ones, memory consumption of
the MTask coarsening is also reduced (measured up to 4.4x reduction
though the accuracy of this is low).
The algorithm is identical except for minor alterations of the order
some candidates are added or removed, this can cause perturbation in the
output due to tied scores being broken based on IDs.
* Tests: Add a test to reproduce #3509
* Tests: Compile without tautological-compare check because bit op tree optimization is disabled in the test.
* Internals: Dedup code. No functional change is intended.
* Fix#3509.
"2'b10 == (2'b11 & {1'b0, val[0]})" and "2'b10 != (2'b11 & {1'b0, val[0]})" were
wrongly optimized to "!val[0]" and "val[0]" respectively.
Now properly optimize them to 1'b0 and 1'b1.
* Commentary
* Commentary: Update Changes
* Tests: Add a test to reproduce #3470
* Update LSB during return path of traversal. No functional change is intended.
* Introduce LeafInfo::m_msb
* Update LeafInfo::m_msb when visitin AstCCast
* Internals: Add comment, reorder. No functional change is intended.
* Delete explicit from copy constructor to fix build error.
* Update Changes
* Internals: Remove unused parameter. No functional change is intended.
* Tests: Add explanation to t_const_opt.
VCD tracing is now parallelized using the same thread pool as the model.
We achieve this by breaking the top level trace functions into multiple
top level functions (as many as --threads), and after emitting the time
stamp to the VCD file on the main thread, we execute the tracing
functions in parallel on the same thread pool as the model (which we
pass to the trace file during registration), tracing into a secondary
per thread buffer. The main thread will then stitch (memcpy) the buffers
together into the output file.
This makes the `--trace-threads` option redundant with `--trace`, which
now only affects `--trace-fst`. FST tracing uses the previous offloading
scheme.
This obviously helps a lot in VCD tracing performance, and I have seen
better than Amdahl speedup, namely I get 3.9x on XiangShan 4T (2.7x on
OpenTitan 4T).
V3MergeCond merges consecutive conditional `_ = cond ? _ : _` and
`if (cond) ...` statements. This patch adds an analysis and ordering
phase that moves statements with identical conditions closer to each
other, in order to enable more merging opportunities. This in turn
eliminates a lot of repeated conditionals which reduced dynamic branch
count and branch misprediction rate. Observed 6.5% improvement on
multi-threaded large designs, at the cost of less than 2% increase in
Verilation speed.
