feat(examples): add image_scale (#7)

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examples/vadd/README.md

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+# Vector Addition — Command Queue
+
+> ![Tips]
+> **SYCL** is used to write this kernel, which is not a common practice.
+> Please also have a look at the **OpenCL** kernel examples like [image_scale](../image_scale/).
+
+A classic GPU compute example: perform element-wise addition of two large float32 vectors on the GPU, then validate the result against a CPU reference.
+
+## What It Does
+
+1. Discovers a GPU device and prints its basic & compute properties
+2. Allocates host and device memory for two float32 vectors (256 MiB each)
+3. Fills both vectors with random values and copies them to device memory
+4. Loads a SPIR-V kernel (`vector_add`) that computes `a[i] += b[i]` in parallel
+5. Launches the kernel via a **command queue** with explicit command lists (pre-copy → compute → post-copy)
+6. Reads back the results and validates every element against the CPU reference
+7. Reports GPU vs. CPU execution time and throughput
+
+## Run
+
+```bash
+go run main.go
+```
+
+## Sample Output
+
+```
+===============  Device Basic Properties  ===============
+Running on device: ID = 32103 , Name = Intel(R) Graphics @ 0.00 GHz.
+=============== Device Compute Properties ===============
+Max Group Size (X, Y, Z):    (1024, 1024, 1024)
+Max Group Count (X, Y, Z):   (4294967295, 4294967295, 4294967295)
+Max Total Group Size:        1024
+Max Shared Local Memory:     65536
+Subgroup Sizes:              [8 16 32]
+=============== Computation Configuration ===============
+Group Size (X, Y, Z):        (1024, 1, 1)
+Group Count:                 65536
+Total Elements (N):          67108864
+Buffer Size:                 256 MiB
+===============    Calculation Results    ===============
+GPU Execution Time:          53.858600 ms
+GPU Throughput:              4.98 GiB/s
+===============    Validation Results    ===============
+CPU Execution Time:          65.882900 ms
+CPU Throughput:              4.07 GiB/s
+Test Passed!!!
+```