1
0
mirror of https://github.com/fumiama/gozel.git synced 2026-06-05 00:10:24 +08:00

feat(examples): add image_scale (#7)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
This commit is contained in:
fumiama
2026-03-29 17:11:22 +08:00
committed by GitHub
parent 68ca8b5e2e
commit 6522bde914
123 changed files with 1074 additions and 163 deletions

View File

@@ -0,0 +1,60 @@
# Image Scaling — GPU Bilinear Resize with Sampler
Downscale an image on the GPU using Level Zero's native **image** and **sampler** objects. The sampler performs hardware-accelerated bilinear interpolation, producing a high-quality resized image in a single kernel dispatch.
## What It Does
1. Decodes an embedded WebP image (1272 × 855) and converts it to RGBA
2. Computes the target dimensions (capped at 512 px on the longest side)
3. Discovers a GPU device and prints its basic & compute properties
4. Creates a SPIR-V module from an OpenCL C kernel compiled offline
5. Uses `zeKernelSuggestGroupSize` to pick an optimal 2-D workgroup size
6. Allocates host/device memory and two Level Zero **image objects** (input & output)
7. Creates a **sampler** with clamp addressing and bilinear filtering
8. Executes three command lists via a command queue:
- **Pre**: copy host pixels → device buffer → input image
- **Compute**: launch the `scale` kernel
- **Post**: copy output image → device buffer → host memory
9. Writes the result to `small.png`
## Run
```bash
go run main.go
```
## Result
| Before Scaling (1272 × 855) | After Scaling (512 × 344) |
|:----------------------------:|:-------------------------:|
| ![input](暖笺贺春.webp) | ![output](small.png) |
### Console Output
```
=============== Image Information ===============
Image Format: webp
Image W/H ratio: 1.4877
Image Size: 1272 x 855
Scale to Image Size: 512 x 344
Scale ratio: 0.4025
Image Data Size: 144802 bytes
=============== 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): (64, 4, 1)
Group Count (X, Y, Z): (8, 86, 1)
Total Elements (srcN, dstN): (4350240, 704512)
Source Buffer Size: 4248.28 KiB
Dest Buffer Size: 688.00 KiB
=============== Calculation Results ===============
GPU Execution Time: 1.579000 ms
GPU Throughput: 2.76 GiB/s
Test Passed!!!
```

View File

@@ -0,0 +1,19 @@
kernel void scale(
read_only image2d_t inputImg,
sampler_t smp,
write_only image2d_t outputImg)
{
uint x = get_global_id(0);
uint y = get_global_id(1);
uint outW = get_image_width(outputImg);
uint outH = get_image_height(outputImg);
float2 normCoord = (float2)(
(float)x / (float)outW,
(float)y / (float)outH
);
float4 pixel = read_imagef(inputImg, smp, normCoord);
write_imagef(outputImg, (int2)(x, y), pixel);
}

View File

@@ -0,0 +1,314 @@
// Package main demonstrates vector addition using the gozel Level Zero bindings.
package main
import (
"bytes"
_ "embed"
"fmt"
"image"
"image/draw"
"image/png"
"math"
"os"
"strconv"
"strings"
"time"
"unsafe"
_ "golang.org/x/image/webp"
"github.com/fumiama/gozel/gozel"
"github.com/fumiama/gozel/ze"
)
//go:generate ocloc compile -file main.cl -spv_only -options "-cl-mad-enable -cl-fast-relaxed-math -cl-finite-math-only -cl-single-precision-constant" -internal_options "-O3" -output main
//go:generate llvm-spirv -to-text main_.spv -o main.spt
//go:embed main_.spv
var kernelspv []byte
//go:embed 暖笺贺春.webp
var imagebytes []byte
func main() {
img, format, err := image.Decode(bytes.NewReader(imagebytes))
if err != nil {
panic(err)
}
bounds := img.Bounds()
width := bounds.Dx()
height := bounds.Dy()
ratio := float64(width) / float64(height)
imgrgba := image.NewRGBA(bounds)
draw.Draw(imgrgba, bounds, img, bounds.Min, draw.Src)
dstw, dsth := width, height
if dstw > 512 {
dstw = 512
dsth = int(float64(dstw) / ratio)
}
if dsth > 512 {
dsth = 512
dstw = int(float64(dsth) * ratio)
}
scaleRatio := float32(float64(dstw) / float64(width))
fmt.Println("=============== Image Information ===============")
fmt.Printf("%-28s %s\n", "Image Format:", format)
fmt.Printf("%-28s %.04f\n", "Image W/H ratio:", ratio)
fmt.Printf("%-28s %d x %d\n", "Image Size:", width, height)
fmt.Printf("%-28s %d x %d\n", "Scale to Image Size:", dstw, dsth)
fmt.Printf("%-28s %.04f\n", "Scale ratio:", scaleRatio)
fmt.Printf("%-28s %d bytes\n", "Image Data Size:", len(imagebytes))
gpus, err := ze.InitGPUDrivers()
if err != nil {
panic(err)
}
if len(gpus) == 0 {
panic("no gpu available")
}
gpu := gpus[0]
ctx, err := gpu.ContextCreate()
if err != nil {
panic(err)
}
devs, err := gpu.DeviceGet()
if err != nil {
panic(err)
}
if len(devs) == 0 {
panic("no device available")
}
dev := devs[0]
prop, err := dev.DeviceGetProperties()
if err != nil {
panic(err)
}
fmt.Println("=============== Device Basic Properties ===============")
name, _, _ := strings.Cut(string(prop.Name[:]), "\x00")
fmt.Println(
"Running on device: ID =", prop.Deviceid, ", Name =", name,
"@", strconv.FormatFloat(float64(prop.Coreclockrate)/1024/1024/1024, 'f', 2, 64), "GHz.",
)
cprop, err := dev.DeviceGetComputeProperties()
if err != nil {
panic(err)
}
fmt.Println("=============== Device Compute Properties ===============")
fmt.Printf("%-28s (%d, %d, %d)\n", "Max Group Size (X, Y, Z):", cprop.Maxgroupsizex, cprop.Maxgroupsizey, cprop.Maxgroupsizez)
fmt.Printf("%-28s (%d, %d, %d)\n", "Max Group Count (X, Y, Z):", cprop.Maxgroupcountx, cprop.Maxgroupcounty, cprop.Maxgroupcountz)
fmt.Printf("%-28s %d\n", "Max Total Group Size:", cprop.Maxtotalgroupsize)
fmt.Printf("%-28s %d\n", "Max Shared Local Memory:", cprop.Maxsharedlocalmemory)
fmt.Printf("%-28s %v\n", "Subgroup Sizes:", cprop.Subgroupsizes[:cprop.Numsubgroupsizes])
mod, err := ctx.ModuleCreate(dev, kernelspv)
if err != nil {
panic(err)
}
defer mod.Destroy()
krn, err := mod.KernelCreate("scale")
if err != nil {
panic(err)
}
defer krn.Destroy()
gX, gY, _, err := krn.SuggestGroupSize(uint32(dstw), uint32(dsth), 1)
if err != nil {
panic(err)
}
var (
X = uintptr(gX)
Y = uintptr(gY)
groupCountX = uint32(math.Ceil(float64(dstw) / float64(X)))
groupCountY = uint32(math.Ceil(float64(dsth) / float64(Y)))
srcN = uintptr(width * height * 4) // 4 for RGBA
dstN = X * uintptr(groupCountX) * Y * uintptr(groupCountY) * 4 // 4 for RGBA
srcbufsz = srcN * unsafe.Sizeof(uint8(0))
dstbufsz = dstN * unsafe.Sizeof(uint8(0))
)
fmt.Println("=============== Computation Configuration ===============")
fmt.Printf("%-28s (%d, %d, %d)\n", "Group Size (X, Y, Z):", X, Y, 1)
fmt.Printf("%-28s (%d, %d, %d)\n", "Group Count (X, Y, Z):", groupCountX, groupCountY, 1)
fmt.Printf("%-28s (%d, %d)\n", "Total Elements (srcN, dstN):", srcN, dstN)
fmt.Printf("%-28s %.02f KiB\n", "Source Buffer Size:", float64(srcbufsz)/1024)
fmt.Printf("%-28s %.02f KiB\n", "Dest Buffer Size:", float64(dstbufsz)/1024)
q, err := ctx.CommandQueueCreate(dev, gozel.ZE_COMMAND_QUEUE_MODE_DEFAULT)
if err != nil {
panic(err)
}
defer q.Destroy()
hbuf, err := ctx.MemAllocHost(srcbufsz, 1)
if err != nil {
panic(err)
}
defer ctx.MemFree(hbuf)
dbuf, err := ctx.MemAllocDevice(dev, srcbufsz, 1)
if err != nil {
panic(err)
}
defer ctx.MemFree(dbuf)
himg := unsafe.Slice((*uint8)(hbuf), srcN)
copy(himg, imgrgba.Pix)
rgbaFmt := gozel.ZeImageFormat{
Layout: gozel.ZE_IMAGE_FORMAT_LAYOUT_8_8_8_8,
Type: gozel.ZE_IMAGE_FORMAT_TYPE_UNORM, // UNORM: bilinear sampling returns float [0,1]
X: gozel.ZE_IMAGE_FORMAT_SWIZZLE_R,
Y: gozel.ZE_IMAGE_FORMAT_SWIZZLE_G,
Z: gozel.ZE_IMAGE_FORMAT_SWIZZLE_B,
W: gozel.ZE_IMAGE_FORMAT_SWIZZLE_A,
}
input, err := ctx.ImageCreate(dev, 0, rgbaFmt, uint64(width), uint32(height))
if err != nil {
panic(err)
}
defer input.Destroy()
smp, err := ctx.SamplerCreate(
dev, gozel.ZE_SAMPLER_ADDRESS_MODE_CLAMP,
gozel.ZE_SAMPLER_FILTER_MODE_LINEAR, 1,
)
if err != nil {
panic(err)
}
defer smp.Destroy()
output, err := ctx.ImageCreate(
dev, gozel.ZE_IMAGE_FLAG_KERNEL_WRITE,
rgbaFmt, uint64(dstw), uint32(dsth),
)
if err != nil {
panic(err)
}
defer output.Destroy()
err = krn.SetArgumentValue(0, input)
if err != nil {
panic(err)
}
err = krn.SetArgumentValue(1, smp)
if err != nil {
panic(err)
}
err = krn.SetArgumentValue(2, output)
if err != nil {
panic(err)
}
err = krn.SetGroupSize(uint32(X), uint32(Y), 1)
if err != nil {
panic(err)
}
lstpre, err := ctx.CommandListCreate(dev)
if err != nil {
panic(err)
}
defer lstpre.Destroy()
err = lstpre.AppendMemoryCopy(dbuf, hbuf, srcbufsz, 0)
if err != nil {
panic(err)
}
err = lstpre.AppendBarrier(0)
if err != nil {
panic(err)
}
err = lstpre.AppendImageCopyFromMemory(input, dbuf, nil, 0)
if err != nil {
panic(err)
}
err = lstpre.AppendBarrier(0)
if err != nil {
panic(err)
}
err = lstpre.Close()
if err != nil {
panic(err)
}
lstcalc, err := ctx.CommandListCreate(dev)
if err != nil {
panic(err)
}
defer lstcalc.Destroy()
err = lstcalc.AppendLaunchKernel(krn, &gozel.ZeGroupCount{
Groupcountx: groupCountX, Groupcounty: groupCountY, Groupcountz: 1,
}, 0)
if err != nil {
panic(err)
}
err = lstcalc.AppendBarrier(0)
if err != nil {
panic(err)
}
err = lstcalc.Close()
if err != nil {
panic(err)
}
lstpost, err := ctx.CommandListCreate(dev)
if err != nil {
panic(err)
}
defer lstpost.Destroy()
err = lstpost.AppendImageCopyToMemory(dbuf, output, nil, 0)
if err != nil {
panic(err)
}
err = lstpost.AppendMemoryCopy(hbuf, dbuf, dstbufsz, 0)
if err != nil {
panic(err)
}
err = lstpost.Close()
if err != nil {
panic(err)
}
start := time.Now()
err = q.ExecuteCommandLists(lstpre, lstcalc, lstpost)
if err != nil {
panic(err)
}
err = q.Synchronize(math.MaxUint64)
if err != nil {
panic(err)
}
elapsed := time.Since(start)
fmt.Println("=============== Calculation Results ===============")
fmt.Printf("%-28s %.6f ms\n", "GPU Execution Time:", elapsed.Seconds()*1000)
fmt.Printf("%-28s %.2f GiB/s\n", "GPU Throughput:", float64(srcbufsz)/elapsed.Seconds()/1e9)
newimgrgba := image.NewRGBA(image.Rect(0, 0, dstw, dsth))
copy(newimgrgba.Pix, himg)
file, err := os.Create("small.png")
if err != nil {
panic(err)
}
defer file.Close()
err = png.Encode(file, newimgrgba)
if err != nil {
panic(err)
}
fmt.Println("Test Passed!!!")
}

View File

@@ -0,0 +1,119 @@
119734787 65536 393230 61 0
2 Capability Addresses
2 Capability Linkage
2 Capability Kernel
2 Capability Int64
2 Capability ImageBasic
5 ExtInstImport 1 "OpenCL.std"
3 MemoryModel 2 2
6 EntryPoint 6 53 "scale" 5
16 String 59 "kernel_arg_type.scale.image2d_t,sampler_t,image2d_t,"
10 String 60 "kernel_arg_type_qual.scale.,,,"
3 Source 3 102000
11 Name 5 "__spirv_BuiltInGlobalInvocationId"
4 Name 11 "scale"
5 Name 12 "inputImg"
3 Name 13 "smp"
5 Name 14 "outputImg"
4 Name 15 "entry"
4 Name 21 "call"
4 Name 23 "conv"
4 Name 26 "call1"
4 Name 27 "conv2"
4 Name 30 "call31"
4 Name 31 "call3"
4 Name 32 "call42"
4 Name 33 "call4"
4 Name 35 "conv5"
4 Name 36 "conv6"
3 Name 37 "div"
4 Name 40 "vecinit"
4 Name 41 "conv7"
4 Name 42 "conv8"
4 Name 43 "div9"
5 Name 44 "vecinit10"
7 Name 46 "TempSampledImage"
4 Name 49 "call11"
5 Name 51 "vecinit13"
5 Name 52 "vecinit14"
5 Name 54 "inputImg"
3 Name 55 "smp"
5 Name 56 "outputImg"
13 Decorate 5 LinkageAttributes "__spirv_BuiltInGlobalInvocationId" Import
3 Decorate 5 Constant
4 Decorate 5 BuiltIn 28
6 Decorate 11 LinkageAttributes "scale" Export
4 Decorate 37 FPFastMathMode 16
4 Decorate 43 FPFastMathMode 16
4 TypeInt 2 64 0
4 TypeInt 22 32 0
5 Constant 2 18 0 0
4 Constant 22 29 0
4 TypeVector 3 2 3
4 TypePointer 4 1 3
2 TypeVoid 6
10 TypeImage 7 6 1 0 0 0 0 0 0
2 TypeSampler 8
10 TypeImage 9 6 1 0 0 0 0 0 1
6 TypeFunction 10 6 7 8 9
2 TypeBool 19
4 TypeVector 28 22 2
3 TypeFloat 34 32
4 TypeVector 38 34 2
3 TypeSampledImage 45 7
4 TypeVector 47 34 4
4 Variable 4 5 1
3 ConstantTrue 19 20
3 Undef 38 39
4 Constant 34 48 0
3 Undef 28 50
5 Function 6 11 0 10
3 FunctionParameter 7 12
3 FunctionParameter 8 13
3 FunctionParameter 9 14
2 Label 15
6 Load 3 16 5 2 32
5 CompositeExtract 2 17 16 0
6 Select 2 21 20 17 18
4 UConvert 22 23 21
6 Load 3 24 5 2 32
5 CompositeExtract 2 25 24 1
6 Select 2 26 20 25 18
4 UConvert 22 27 26
5 ImageQuerySizeLod 28 30 14 29
5 CompositeExtract 22 31 30 0
5 ImageQuerySizeLod 28 32 14 29
5 CompositeExtract 22 33 32 1
4 ConvertUToF 34 35 23
4 ConvertUToF 34 36 31
5 FDiv 34 37 35 36
6 CompositeInsert 38 40 37 39 0
4 ConvertUToF 34 41 27
4 ConvertUToF 34 42 33
5 FDiv 34 43 41 42
6 CompositeInsert 38 44 43 40 1
5 SampledImage 45 46 12 13
7 ImageSampleExplicitLod 47 49 46 44 2 48
6 CompositeInsert 28 51 23 50 0
6 CompositeInsert 28 52 27 51 1
4 ImageWrite 14 52 49
1 Return
1 FunctionEnd
5 Function 6 53 0 10
3 FunctionParameter 7 54
3 FunctionParameter 8 55
3 FunctionParameter 9 56
2 Label 57
7 FunctionCall 6 58 11 54 55 56
1 Return
1 FunctionEnd

Binary file not shown.

Binary file not shown.

After

Width:  |  Height:  |  Size: 251 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 141 KiB

View File

@@ -0,0 +1,21 @@
# Quick Start — Device Enumeration
The simplest gozel example: initialize the Level Zero runtime, enumerate all available GPU drivers and their devices, and print device names.
## What It Does
- Initializes Level Zero and retrieves all GPU driver handles
- Iterates over devices under each driver, queries and prints device properties (name)
## Run
```bash
go run main.go
```
## Sample Output
```
Found 1 GPU driver(s)
Device: Intel(R) Graphics
```

48
examples/vadd/README.md Normal file
View File

@@ -0,0 +1,48 @@
# 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!!!
```

View File

@@ -16,10 +16,11 @@ import (
"github.com/fumiama/gozel/ze"
)
//go:generate clang++ -fsycl -fsycl-device-only -fsycl-targets=spirv64 -Xclang -emit-llvm-bc main.cpp -o device_kern.bc
//go:generate sycl-post-link -symbols -split=auto -o device_kern.table device_kern.bc
//go:generate llvm-spirv -o main.spv device_kern_0.bc
//go:generate clang++ -fsycl -fsycl-device-only -fno-sycl-instrument-device-code -fsycl-targets=spirv64 -Xclang -emit-llvm-bc main.cpp -o device_kern.bc
//go:generate sycl-post-link -symbols -split=auto -emit-param-info -properties -o device_kern.table device_kern.bc
//go:generate llvm-spirv --sycl-opt -o main.spv device_kern_0.bc
//go:generate clang++ -target spirv64-unknown-unknown -S -emit-llvm -x ir device_kern_0.bc -o main.ll
//go:generate llvm-spirv -to-text main.spv -o main.spt
//go:embed main.spv
var kernelspv []byte

79
examples/vadd/main.spt Normal file
View File

@@ -0,0 +1,79 @@
119734787 66560 393230 34 0
2 Capability Addresses
2 Capability Linkage
2 Capability Kernel
2 Capability Int64
5 ExtInstImport 1 "OpenCL.std"
3 MemoryModel 2 2
12 EntryPoint 6 29 "__sycl_kernel_vector_add" 5 6
3 ExecutionMode 29 31
3 Source 4 100000
11 Name 5 "__spirv_BuiltInGlobalInvocationId"
9 Name 6 "__spirv_BuiltInGlobalOffset"
9 Name 11 "__sycl_kernel_vector_add"
13 Decorate 5 LinkageAttributes "__spirv_BuiltInGlobalInvocationId" Import
3 Decorate 5 Constant
4 Decorate 5 BuiltIn 28
4 Decorate 5 Alignment 32
11 Decorate 6 LinkageAttributes "__spirv_BuiltInGlobalOffset" Import
3 Decorate 6 Constant
4 Decorate 6 BuiltIn 33
4 Decorate 6 Alignment 32
11 Decorate 11 LinkageAttributes "__sycl_kernel_vector_add" Export
4 Decorate 12 FuncParamAttr 5
4 Decorate 12 Alignment 4
4 Decorate 13 FuncParamAttr 5
4 Decorate 13 FuncParamAttr 6
4 Decorate 13 Alignment 4
4 Decorate 30 FuncParamAttr 5
4 Decorate 30 Alignment 4
4 Decorate 31 FuncParamAttr 5
4 Decorate 31 FuncParamAttr 6
4 Decorate 31 Alignment 4
4 TypeInt 2 64 0
5 Constant 2 21 2147483648 0
4 TypeVector 3 2 3
4 TypePointer 4 5 3
2 TypeVoid 7
3 TypeFloat 8 32
4 TypePointer 9 5 8
5 TypeFunction 10 7 9 9
4 TypePointer 15 5 2
2 TypeBool 22
4 Variable 4 5 5
4 Variable 4 6 5
5 Function 7 11 0 10
3 FunctionParameter 9 12
3 FunctionParameter 9 13
2 Label 14
4 Bitcast 15 16 5
6 Load 2 17 16 2 32
4 Bitcast 15 18 6
6 Load 2 19 18 2 32
5 ISub 2 20 17 19
5 ULessThan 22 23 20 21
5 InBoundsPtrAccessChain 9 24 13 20
6 Load 8 25 24 2 4
5 InBoundsPtrAccessChain 9 26 12 20
6 Load 8 27 26 2 4
5 FAdd 8 28 27 25
5 Store 26 28 2 4
1 Return
1 FunctionEnd
5 Function 7 29 0 10
3 FunctionParameter 9 30
3 FunctionParameter 9 31
2 Label 32
6 FunctionCall 7 33 11 30 31
1 Return
1 FunctionEnd

View File

@@ -0,0 +1,61 @@
# Vector Addition — Immediate Command List with Events
> ![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/).
The same vector addition workload as the `vadd` example, but driven by an **immediate command list** and **events** instead of explicit command queues. This demonstrates fine-grained dependency tracking: memory copies signal events, and the kernel launch waits on those events before executing.
## 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
4. Loads a SPIR-V kernel (`vector_add`) that computes `a[i] += b[i]` in parallel
5. Creates an **event pool** with 3 events to express data-flow dependencies
6. Submits all work through a single **immediate command list**:
- Two H→D copies, each signaling its own event
- Kernel launch that **waits** on both copy events before executing
- D→H copy that waits on the kernel event
7. Synchronizes via `HostSynchronize` on the immediate command list
8. Validates every element against the CPU reference
## Key Difference from `vadd`
| Aspect | `vadd` | `vadd_event` |
|--------|--------|-------------|
| Submission | 3 separate command lists executed on a command queue | 1 immediate command list |
| Synchronization | `zeCommandQueueSynchronize` | `zeCommandListHostSynchronize` |
| Dependencies | Implicit via command list ordering + barriers | Explicit via events (wait lists) |
## 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
Num Subgroup Sizes: 3
Subgroup Sizes: [8 16 32 0 0 0 0 0]
=============== 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: 51.768500 ms
GPU Throughput: 5.19 GiB/s
=============== Validation Results ===============
CPU Execution Time: 38.237400 ms
CPU Throughput: 7.02 GiB/s
Test Passed!!!
```

View File

@@ -16,10 +16,11 @@ import (
"github.com/fumiama/gozel/ze"
)
//go:generate clang++ -fsycl -fsycl-device-only -fsycl-targets=spirv64 -Xclang -emit-llvm-bc main.cpp -o device_kern.bc
//go:generate sycl-post-link -symbols -split=auto -o device_kern.table device_kern.bc
//go:generate llvm-spirv -o main.spv device_kern_0.bc
//go:generate clang++ -fsycl -fsycl-device-only -fno-sycl-instrument-device-code -fsycl-targets=spirv64 -Xclang -emit-llvm-bc main.cpp -o device_kern.bc
//go:generate sycl-post-link -symbols -split=auto -emit-param-info -properties -o device_kern.table device_kern.bc
//go:generate llvm-spirv --sycl-opt -o main.spv device_kern_0.bc
//go:generate clang++ -target spirv64-unknown-unknown -S -emit-llvm -x ir device_kern_0.bc -o main.ll
//go:generate llvm-spirv -to-text main.spv -o main.spt
//go:embed main.spv
var kernelspv []byte

View File

@@ -0,0 +1,79 @@
119734787 66560 393230 34 0
2 Capability Addresses
2 Capability Linkage
2 Capability Kernel
2 Capability Int64
5 ExtInstImport 1 "OpenCL.std"
3 MemoryModel 2 2
12 EntryPoint 6 29 "__sycl_kernel_vector_add" 5 6
3 ExecutionMode 29 31
3 Source 4 100000
11 Name 5 "__spirv_BuiltInGlobalInvocationId"
9 Name 6 "__spirv_BuiltInGlobalOffset"
9 Name 11 "__sycl_kernel_vector_add"
13 Decorate 5 LinkageAttributes "__spirv_BuiltInGlobalInvocationId" Import
3 Decorate 5 Constant
4 Decorate 5 BuiltIn 28
4 Decorate 5 Alignment 32
11 Decorate 6 LinkageAttributes "__spirv_BuiltInGlobalOffset" Import
3 Decorate 6 Constant
4 Decorate 6 BuiltIn 33
4 Decorate 6 Alignment 32
11 Decorate 11 LinkageAttributes "__sycl_kernel_vector_add" Export
4 Decorate 12 FuncParamAttr 5
4 Decorate 12 Alignment 4
4 Decorate 13 FuncParamAttr 5
4 Decorate 13 FuncParamAttr 6
4 Decorate 13 Alignment 4
4 Decorate 30 FuncParamAttr 5
4 Decorate 30 Alignment 4
4 Decorate 31 FuncParamAttr 5
4 Decorate 31 FuncParamAttr 6
4 Decorate 31 Alignment 4
4 TypeInt 2 64 0
5 Constant 2 21 2147483648 0
4 TypeVector 3 2 3
4 TypePointer 4 5 3
2 TypeVoid 7
3 TypeFloat 8 32
4 TypePointer 9 5 8
5 TypeFunction 10 7 9 9
4 TypePointer 15 5 2
2 TypeBool 22
4 Variable 4 5 5
4 Variable 4 6 5
5 Function 7 11 0 10
3 FunctionParameter 9 12
3 FunctionParameter 9 13
2 Label 14
4 Bitcast 15 16 5
6 Load 2 17 16 2 32
4 Bitcast 15 18 6
6 Load 2 19 18 2 32
5 ISub 2 20 17 19
5 ULessThan 22 23 20 21
5 InBoundsPtrAccessChain 9 24 13 20
6 Load 8 25 24 2 4
5 InBoundsPtrAccessChain 9 26 12 20
6 Load 8 27 26 2 4
5 FAdd 8 28 27 25
5 Store 26 28 2 4
1 Return
1 FunctionEnd
5 Function 7 29 0 10
3 FunctionParameter 9 30
3 FunctionParameter 9 31
2 Label 32
6 FunctionCall 7 33 11 30 31
1 Return
1 FunctionEnd