Add some generic SchedWrites and assign resources for Swift and Cortex A9.
Reapply of r183257. (Removed empty InstRW for division on swift)
llvm-svn: 183319
Reapply r177968:
After commit 178074 we can now have undefined scheduler variants.
Move the CortexA9 resources into the CortexA9 SchedModel namespace. Define
resource mappings under the CortexA9 SchedModel. Define resources and mappings
for the SwiftModel.
Incooperate Andrew's feedback.
llvm-svn: 178460
This reverts commit r177968. It is causing failures in a local build bot.
"fatal error: error in backend: Expected a variant SchedClass"
Original commit message:
Move the CortexA9 resources into the CortexA9 SchedModel namespace. Define
resource mappings under the CortexA9 SchedModel. Define resources and mappings
for the SwiftModel.
llvm-svn: 178028
Move the CortexA9 resources into the CortexA9 SchedModel namespace. Define
resource mappings under the CortexA9 SchedModel. Define resources and mappings
for the SwiftModel.
llvm-svn: 177968
This is very much work in progress. Please send me a note if you start to depend
on the added abstract read/write resources. They are subject to change until
further notice.
The old itinerary is still the default.
llvm-svn: 177967
The TargetInstrInfo::getNumMicroOps API does not change, but soon it
will be used by MachineScheduler. Now each subtarget can specify the
number of micro-ops per itinerary class. For ARM, this is currently
always dynamic (-1), because it is used for load/store multiple which
depends on the number of register operands.
Zero is now a valid number of micro-ops. This can be used for
nop pseudo-instructions or instructions that the hardware can squash
during dispatch.
llvm-svn: 159406
This makes it explicit when ScoreboardHazardRecognizer will be used.
"GenericItineraries" would only make sense if it contained real
itinerary values and still required ScoreboardHazardRecognizer.
llvm-svn: 158963
TargetInstrInfo:
Change produceSameValue() to take MachineRegisterInfo as an optional argument.
When in SSA form, targets can use it to make more aggressive equality analysis.
Machine LICM:
1. Eliminate isLoadFromConstantMemory, use MI.isInvariantLoad instead.
2. Fix a bug which prevent CSE of instructions which are not re-materializable.
3. Use improved form of produceSameValue.
ARM:
1. Teach ARM produceSameValue to look pass some PIC labels.
2. Look for operands from different loads of different constant pool entries
which have same values.
3. Re-implement PIC GA materialization using movw + movt. Combine the pair with
a "add pc" or "ldr [pc]" to form pseudo instructions. This makes it possible
to re-materialize the instruction, allow machine LICM to hoist the set of
instructions out of the loop and make it possible to CSE them. It's a bit
hacky, but it significantly improve code quality.
4. Some minor bug fixes as well.
With the fixes, using movw + movt to materialize GAs significantly outperform the
load from constantpool method. 186.crafty and 255.vortex improved > 20%, 254.gap
and 176.gcc ~10%.
llvm-svn: 123905
1. Cortex-A8 load / store multiplies can only issue on ALU0.
2. Eliminate A8_Issue, A8_LSPipe will correctly limit the load / store issues.
3. Correctly model all vld1 and vld2 variants.
llvm-svn: 116134
allow target to correctly compute latency for cases where static scheduling
itineraries isn't sufficient. e.g. variable_ops instructions such as
ARM::ldm.
This also allows target without scheduling itineraries to compute operand
latencies. e.g. X86 can return (approximated) latencies for high latency
instructions such as division.
- Compute operand latencies for those defined by load multiple instructions,
e.g. ldm and those used by store multiple instructions, e.g. stm.
llvm-svn: 115755
1. Cortex-a9 8-bit and 16-bit loads / stores AGU cycles are 1 cycle longer than 32-bit ones.
2. Cortex-a9 is out-of-order so model all read cycles as cycle 1.
3. Lots of other random fixes for A8 and A9.
llvm-svn: 115121
instruction in the class would be decoded to. Or zero if the number of
uOPs must be determined dynamically.
This will be used to determine the cost-effectiveness of predicating a
micro-coded instruction.
llvm-svn: 113513
Arnold Schwaighofer