[CK_TILE] Add depthwise conv2d forward kernel (FP16/FP32) (#6838)
## Motivation
CK currently has no kernel optimized for depthwise convolution
(G=C_in=C_out, C=K=1 per group) and existing generic paths perform
poorly for this workload. This PR adds a dedicated depthwise conv
forward kernel in CK Tile.
## Technical Details
Adds a dedicated depthwise conv2d forward op to CK Tile that performs
direct convolution rather than falling back to the generic GEMM path.
The kernel is templatized by filter size, stride, and data type, and
compiled into ~60 instances covering common configurations (kernel
3/5/7/9, stride 1/2, FP16/FP32). Supports both CDNA (gfx942/gfx950) and
RDNA (gfx1100/gfx1200) architectures.
## Test Plan
- [x] Correctness and performance validated on gfx942, gfx950, and
gfx1100, with ckProfiler `grouped_conv_fwd` as baseline.
- [ ] MI300A (gfx942) and gfx1200 validation.
## Submission Checklist
- [x ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
AICK-1137
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Co-authored-by: GenDu <Gen.Du@amd.com>
[CK] add composable kernel support on gfx1250 (#6978)
## Motivation
Add composable kernel support on gfx1250.
## Technical Details
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## Test Plan
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## Test Result
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## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
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Co-authored-by: Qun Lin <qlin@amd.com>
Co-authored-by: jialuo12_amdeng <jia.luo@amd.com>
Co-authored-by: Andriy Roshchenko <andriy.roshchenko@amd.com>
Co-authored-by: hsivasun_amdeng <haresh.sivasuntharampillai@amd.com>
[CK_TILE] Add CK Tile bwd weight profiler (#4797)
## Motivation
To compare old CK and CK Tile, we need to extend the current CK profiler
to support running also CK Tile instance with the same API. In order to
have the same instance coverage in CK Tile compared to the old CK, I've
added code generation from old CK configurations to CK Tile instances
using the CK Builder.
## Technical Details
- The codegen python script for CK Tile fwd convs is extended to support
also bwd weight and bwd data.
- The generated instances are added to the CMake build (target
`device_grouped_conv_bwd_weight_tile_instance`s).
- A new profiler op (`grouped_conv_bwd_weight_tile`) has been added to
the CK Profiler.
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Co-authored-by: Ville Pietilä <>
Co-authored-by: Bartlomiej Kocot <barkocot@amd.com>
