Update README.md (#2624)

Author: jackl-xilinx

programming_examples/getting_started/01_SAXPY/README.md

@@ -12,15 +12,14 @@ This design consists of the following:
   JIT decorator to compile the design into a binary to run on the NPU, as well as 
   to describe the program that runs on the CPU (host) that calculates a correct 
   reference output, verifies and times our NPU design's execution.
-* `saxpy_scalar_baseline.cc`: A C++ scalar SAXPY kernel.
-* `saxpy_vector.cc`: A C++ vectorized kernel that exposes efficient 
+* `saxpy.cc`: Contains both a scalar C++ SAXPY kernel (saxpy_scalar) and a vectorized kernel (saxpy) that exposes efficient 
   vector operations on the AI Engine using the 
   [AIE API](https://xilinx.github.io/aie_api/index.html).
 * `run.lit`: lit test that runs the design on different NPU devices.
 
 ## Data Movement and Compute
 
-Input tensors `X` and `Y` are moved from DRAM to the AI Engine compute core using ObjectFIFOs `of_x` and `of_y`. The output tensor `Z` is moved from the AI Engine compute core to DRAM using ObjectFIFO `of_z`. The AI Engine program calls the external kernel `saxpy_kernel` defined in `saxpy_vector.cc`.
+Input tensors `X` and `Y` are moved from DRAM to the AI Engine compute core using ObjectFIFOs `of_x` and `of_y`. The output tensor `Z` is moved from the AI Engine compute core to DRAM using ObjectFIFO `of_z`. The AI Engine program calls the external kernel `saxpy_kernel` defined in `saxpy.cc`.
 
 ## Ryzen™ AI Usage