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Dimension support for reduce operator (#1147)

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* cache reference nodes

* evaluation based on dim args

* format

* add dimensions for reduce operator

* add dimensions for reduce operator

* add dimensions for reduce operator docs

* add dimensions for reduce operator.

* refactor switch cases

* Update CHANGELOG.md

* updated doc with data example

* updated doc with data example for reduce operation.

* added fallthrough in switch case sum.

* changelog.md

* format

* fix bug in constuct_test_data()

[ROCm/rocprofiler-sdk commit: 472907a576]
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venkat1361
2024-11-11 07:07:28 -06:00
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commit 46cb82b75f
4 changed files with 294 additions and 64 deletions
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projects/rocprofiler-sdk/source/docs/api-reference/counter_collection_services.md
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@@ -289,6 +289,50 @@ Expression: 100*reduce(GL2C_HIT,sum)/(reduce(GL2C_HIT,sum)+reduce(GL2C_MISS,sum)
The reduce function reduces counter values across all dimensions such as shader engine, SIMD, and so on, to produce a single output value. This helps to collect and compare values across the entire device.
Here are the common reduction operations:
- `sum`: Sums to create a single output. For example, `reduce(GL2C_HIT,sum)` sums all `GL2C_HIT` hardware register values.
- `avr`: Calculates the average across all dimensions.
- `min`: Selects minimum value across all dimensions.
- `max`: Selects the maximum value across all dimensions.
```yaml
expression: reduce(X,sum,[DIMENSION_XCC])
```
Reduce() also supports dimension wise reduction, when provided dimensions in 3rd parameter. In the expression above, if `X` has two dimensions `DIMENSION_XCC`, `DIMENSION_SHADER_ARRAY`, and `DIMENSION_WGP`, the reduce happens across counter values where `DIMENSION_SHADER_ARRAY` and `DIMENSION_WGP` dimensions are same as shown below.
Let's say DIM sizes of XCC, SHADER_ARRAY(SH), WGP be 2, 4, 4 respectively.
Raw Counter Data in 3D space:
#### XCC[0]:
| |WGP[0]|WGP[1]|WGP[2]|WGP[3]|
|-------|------|------|------|------|
| SH[0] | 1 | 2 | 3 | 4 |
| SH[1] | 5 | 6 | 7 | 8 |
| SH[2] | 9 | 10 | 11 | 12 |
| SH[3] | 13 | 14 | 15 | 16 |
#### XCC[1]:
| |WGP[0]|WGP[1]|WGP[2]|WGP[3]|
|-------|------|------|------|------|
| SH[0] | 1 | 2 | 3 | 4 |
| SH[1] | 5 | 6 | 7 | 8 |
| SH[2] | 9 | 10 | 11 | 12 |
| SH[3] | 13 | 14 | 15 | 16 |
Reducing XCC dim with sum, results to 2D space with only WGP and SH.
| |WGP[0]|WGP[1]|WGP[2]|WGP[3]|
|-------|------|------|------|------|
| SH[0] | 2 | 4 | 6 | 8 |
| SH[1] | 10 | 12 | 14 | 16 |
| SH[2] | 18 | 20 | 22 | 24 |
| SH[3] | 26 | 28 | 30 | 32 |
similarly, for `reduce(X,sum,[DIMENSION_XCC,DIMENSION_SHADER_ARRAY])` results in only WGP dimension.
| |WGP[0]|WGP[1]|WGP[2]|WGP[3]|
|-------|------|------|------|------|
| | 56 | 64 | 72 | 80 |
### Select Function
@@ -333,13 +377,6 @@ similarly, for `select(Y, [DIMENSION_XCC=[0],DIMENSION_SHADER_ENGINE=[2]])` resu
|-------|------|------|------|------|
| | 9 | 10 | 11 | 12 |
### Accumulate Function
- `sum`: Sums to create a single output. For example, `reduce(GL2C_HIT,sum)` sums all `GL2C_HIT` hardware register values.
- `avr`: Calculates the average across all dimensions.
- `min`: Selects minimum value across all dimensions.
- `max`: Selects the maximum value across all dimensions.
### Accumulate function
```yaml