Hi @MarisaKirisame , I have several questions during the learning of AAM, about
the advantage of implementing AAM over using the normal Dataflow Analysis
framework (like the proposed one above) in the context of Relay. Because I have
no experience in Relay at all, I would appreciate it if you ca
@MarisaKirisame : I might still be a little confused about the semantic and
**internal memory representation** of RelayIR. I would appreciated if you can
enlighten me: in the official document, the picture for ANF is still a DAG (a
child can have several different parent) with respect to **inte
Hi @MarisaKirisame , I currently have a question about representing "location
inside the program" because when the users want to query about the
Dataflow-Info, they will need to use "location".
**TLDR**: Pointers to ASTNodes are not one-to-one correspondent to "locations
in the program". Can th
Hi @MarisaKirisame , thanks for commenting!
So which one are you looking for? ADI or AAM?
I am not familiar with either, but I remember AAM requires a state machine
transition definition of the semantics, where ADI requires a definitional
interpreter to define the semantics.
My another question
Hi @comaniac , Thanks for your suggestion! :)
Because of your suggestion and [Unified IR
Post](https://discuss.tvm.ai/t/ir-unified-tvm-ir-infra/4801), I think I need to
dig into the design and infrastructure of Relay for a while to see how to
design an DFA infrastructure that fits into both IRs.
Hi @comaniac , Thanks for commenting. :)
Yes. This is a real problem happening in the industrial context. The current
solution is either over-conservative or unsound.
About the name of "Data-flow Analysis", I think it is more a terminology
question. For example the CFA is also a kind of pr
Hi @junrushao1994 ,
an over-simplified example from the industrial context is the following:
```python
...
B0 = tvm.compute((m,n), lambda i,j: A0[i,j] + 2*A1[i,j], name = "B0")
C0 = tvm.compute((m,n), lambda i,j: A0[i,j] + 2*A1[i,j], name = "C0")
D0 = tvm.compute((m,n), lambda i,j: B0[i,j] + 3*
Hi @junrushao1994 , Thanks for the comments! :) I will get back to you about a
real world example as soon as possible.
But generally speaking, dead code elimination pass is required in some
workloads; and after TVM output program with intrinsics and not even targetting
CPU or GPU, LLVM or other
### Comments: IsLattice
The basic usage is just:
```cpp
template
struct STD_SET_IS_LATTICE : public IsLattice> {
using SET = std::set;
public:
SET join(const SET& a, const SET& b);
SET meet(const SET& a, const SET& b);
const SET& top();
const SET& bottom();
bool equal
# Problem
When developing program passes on TVM IR (the one once was Halide IR), it is
normal to ask for all sorts of information requiring program analysis, for
example, live variable analysis for dead code elimination. This requirement
becomes urgent when TVM has to directly issue intrinsic a
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