Use cutlass for a pure julia fallback

src/blasfallback.jl

@@ -0,0 +1,36 @@
+
+function block_matrix_product(state, A, B, C) where {ThreadItemsY, ThreadItemsX}
+
+    # Fragments used to store data fetched from SMEM
+    frag_a = @LocalMemory(state, T, ThreadItemsY)
+    frag_b = @LocalMemory(state, T, ThreadItemsX)
+
+    # Accumulator storage
+    accumulator = @LocalMemory(state, T, ThreadItemsX, ThreadItemsY)
+
+    # GEMM Mainloop - iterates over the entire K dimension - not unrolled
+    for kblock in Int32(1):BlockItemsK:K_dim
+        # Load A and B tiles from global memory and store to SMEM
+        #
+        # (not shown for brevity - see the CUTLASS source for more detail)
+
+        synchronize_threads(state)
+        # Warp tile structure - iterates over the Thread Block tile
+        #pragma unroll
+        for warp_k in Int32(1):WarpItemsK:BlockItemsK
+            # Fetch frag_a and frag_b from SMEM corresponding to k-index
+            #
+            # (not shown for brevity - see CUTLASS source for more detail)
+
+            # Thread tile structure - accumulate an outer product
+            #pragma unroll
+            for thread_x in Int32(1):ThreadItemsX
+                #pragma unroll
+                for thread_y in Int32(1):ThreadItemsY
+                    accumulator[thread_x, thread_y] += frag_a[y] * frag_b[x]
+                end
+            end
+        end
+        synchronize_threads(state)
+    end
+end