From ddc9f704bfb57c249b83c6a79f538961a2e20192 Mon Sep 17 00:00:00 2001
From: LoserCheems <losercheems@gmail.com>
Date: Tue, 16 Dec 2025 11:33:22 +0800
Subject: [PATCH 1/2] Implements PyTorch GEMM helper

Adds a matrix update utility that composes matmul with alpha and beta scaling to enable reuse of GEMM semantics in PyTorch flows
---
 kernel_course/pytorch_ops/gemm.py | 28 ++++++++++++++++++++++++++++
 1 file changed, 28 insertions(+)
 create mode 100644 kernel_course/pytorch_ops/gemm.py

diff --git a/kernel_course/pytorch_ops/gemm.py b/kernel_course/pytorch_ops/gemm.py
new file mode 100644
index 0000000..9d92976
--- /dev/null
+++ b/kernel_course/pytorch_ops/gemm.py
@@ -0,0 +1,28 @@
+import torch
+
+
+def gemm(
+    A: torch.Tensor,
+    B: torch.Tensor,
+    C: torch.Tensor,
+    alpha: float,
+    beta: float,
+) -> torch.Tensor:
+    """
+    Updates tensor `C` by adding the product of matrices `A` and `B`
+    scaled by `alpha`, and `C` scaled by `beta` using PyTorch operations.
+
+    Args:
+        A (torch.Tensor): First matrix tensor.
+        B (torch.Tensor): Second matrix tensor to be multiplied with `A`.
+        C (torch.Tensor): Matrix tensor to be updated.
+        alpha (float): Scaling factor for the product of `A` and `B`.
+        beta (float): Scaling factor for `C`.
+
+    Returns:
+        torch.Tensor: The updated tensor `C`.
+    """
+
+    C = torch.add(torch.mul(alpha, torch.matmul(A, B)), torch.mul(beta, C))
+
+    return C

From 87753166292ff7523b3a49ada59da20572bb9320 Mon Sep 17 00:00:00 2001
From: LoserCheems <losercheems@gmail.com>
Date: Tue, 16 Dec 2025 11:34:25 +0800
Subject: [PATCH 2/2] Update GEMM entry in README to reflect PyTorch
 implementation status

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 5eb4487..f2097bc 100644
--- a/README.md
+++ b/README.md
@@ -24,7 +24,7 @@ The following common BLAS kernels have been implemented in multiple frameworks.
 | [dot](./docs/dot.md) | dot product | $z = x^\top y$ | $2n$ | $2n$ | [✅](./kernel_course/python_ops/dot.py) | [✅](./kernel_course/pytorch_ops/dot.py) | [✅](./kernel_course/triton_ops/dot.py) | ❌ | [✅](./tests/test_dot.py) |
 | [gemv](./docs/gemv.md) | general matrix-vector multiply | $y = \alpha A x + \beta y$ | $2mn$ | $mn + n + 2m$ | [✅](./kernel_course/python_ops/gemv.py) | [✅](./kernel_course/pytorch_ops/gemv.py) | [✅](./kernel_course/triton_ops/gemv.py) | ❌ | [✅](./tests/test_gemv.py) |
 | [geru](./docs/geru.md) | general rank-1 update | $A = A + \alpha x y^\top$ | $2mn$ | $2mn + m + n$ | [✅](./kernel_course/python_ops/geru.py) | [✅](./kernel_course/pytorch_ops/geru.py) | [✅](./kernel_course/triton_ops/geru.py) | ❌ | [✅](./tests/test_geru.py) |
-| [gemm](./docs/gemm.md) | general matrix-matrix multiply | $C = \alpha A B + \beta C$ | $2mnk$ | $mk + nk + 2mn$ | [✅](./kernel_course/python_ops/gemm.py) | ❌ | ❌ | ❌ | ❌ |
+| [gemm](./docs/gemm.md) | general matrix-matrix multiply | $C = \alpha A B + \beta C$ | $2mnk$ | $mk + nk + 2mn$ | [✅](./kernel_course/python_ops/gemm.py) | [✅](./kernel_course/pytorch_ops/gemm.py) | ❌ | ❌ | ❌ |
 
 
 ## Transformer Modules