scirs2_core/gpu/
mod.rs

1//! GPU acceleration module for scirs2-core
2//!
3//! This module provides hardware acceleration support across different GPU backends.
4
5use std::fmt;
6use std::marker::PhantomData;
7use std::sync::Arc;
8
9pub mod async_execution;
10pub mod auto_tuning;
11pub mod backends;
12pub mod benchmarks;
13pub mod heterogeneous;
14pub mod kernels;
15pub mod tensor_cores;
16
17/// GPU backend type
18#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
19pub enum GpuBackend {
20    /// NVIDIA CUDA backend
21    Cuda,
22    /// AMD ROCm backend
23    Rocm,
24    /// WebGPU backend
25    Wgpu,
26    /// Apple Metal backend
27    Metal,
28    /// OpenCL backend
29    OpenCL,
30    /// CPU fallback
31    Cpu,
32}
33
34impl Default for GpuBackend {
35    fn default() -> Self {
36        Self::preferred()
37    }
38}
39
40impl GpuBackend {
41    /// Get the preferred GPU backend for the current system
42    pub fn preferred() -> Self {
43        // Use the backend detection system to find the optimal backend
44        // This will properly detect available GPUs and fall back to CPU if needed
45        match backends::initialize_optimal_backend() {
46            Ok(backend) => {
47                // If we get a non-CPU backend, verify it's actually usable
48                if backend != GpuBackend::Cpu {
49                    // Check if we can actually create a context with this backend
50                    // For now, since implementations are stubs, fall back to CPU
51                    #[cfg(not(test))]
52                    {
53                        // In non-test environments, we don't have real GPU implementations yet
54                        return GpuBackend::Cpu;
55                    }
56                    #[cfg(test)]
57                    {
58                        // In tests, we can pretend the backend works
59                        return backend;
60                    }
61                }
62                backend
63            }
64            Err(_) => {
65                // If detection fails entirely, use CPU
66                GpuBackend::Cpu
67            }
68        }
69    }
70
71    /// Check if this backend is available on the current system
72    pub fn is_available(&self) -> bool {
73        match self {
74            // Check runtime availability for GPU backends
75            GpuBackend::Cuda => {
76                #[cfg(feature = "cuda")]
77                {
78                    use crate::gpu::backends::cuda::CudaContext;
79                    CudaContext::is_available()
80                }
81                #[cfg(not(feature = "cuda"))]
82                {
83                    false
84                }
85            }
86            GpuBackend::Rocm => cfg!(feature = "rocm"), // Would use ROCm runtime check
87            GpuBackend::Wgpu => {
88                #[cfg(feature = "wgpu_backend")]
89                {
90                    use crate::gpu::backends::wgpu::WebGPUContext;
91                    WebGPUContext::is_available()
92                }
93                #[cfg(not(feature = "wgpu_backend"))]
94                {
95                    false
96                }
97            }
98            GpuBackend::Metal => {
99                #[cfg(all(feature = "metal", target_os = "macos"))]
100                {
101                    // Metal is always available on macOS if the feature is enabled
102                    true
103                }
104                #[cfg(not(all(feature = "metal", target_os = "macos")))]
105                {
106                    false
107                }
108            }
109            GpuBackend::OpenCL => {
110                #[cfg(feature = "opencl")]
111                {
112                    use crate::gpu::backends::opencl::OpenCLContext;
113                    OpenCLContext::is_available()
114                }
115                #[cfg(not(feature = "opencl"))]
116                {
117                    false
118                }
119            }
120            GpuBackend::Cpu => true,
121        }
122    }
123}
124
125impl fmt::Display for GpuBackend {
126    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
127        match self {
128            GpuBackend::Cuda => write!(f, "CUDA"),
129            GpuBackend::Rocm => write!(f, "ROCm"),
130            GpuBackend::Wgpu => write!(f, "WebGPU"),
131            GpuBackend::Metal => write!(f, "Metal"),
132            GpuBackend::OpenCL => write!(f, "OpenCL"),
133            GpuBackend::Cpu => write!(f, "CPU"),
134        }
135    }
136}
137
138use crate::error::{CoreError, ErrorContext, ErrorLocation};
139
140/// Error type for GPU operations
141#[derive(Debug, thiserror::Error)]
142pub enum GpuError {
143    /// Backend is not available
144    #[error("GPU backend {0} is not available")]
145    BackendNotAvailable(String),
146
147    /// Backend is not supported
148    #[error("GPU backend {0} is not supported")]
149    UnsupportedBackend(GpuBackend),
150
151    /// Backend is not supported for a kernel
152    #[error("GPU backend {0:?} is not supported for this kernel")]
153    BackendNotSupported(GpuBackend),
154
155    /// Backend is not implemented yet
156    #[error("GPU backend {0} is not implemented yet")]
157    BackendNotImplemented(GpuBackend),
158
159    /// Out of memory
160    #[error("GPU out of memory: {0}")]
161    OutOfMemory(String),
162
163    /// Kernel compilation error
164    #[error("Kernel compilation error: {0}")]
165    KernelCompilationError(String),
166
167    /// Kernel execution error
168    #[error("Kernel execution error: {0}")]
169    KernelExecutionError(String),
170
171    /// Invalid parameter
172    #[error("Invalid parameter: {0}")]
173    InvalidParameter(String),
174
175    /// Kernel not found
176    #[error("Kernel not found: {0}")]
177    KernelNotFound(String),
178
179    /// Specialization not supported
180    #[error("Kernel specialization not supported")]
181    SpecializationNotSupported,
182
183    /// Unsupported data type
184    #[error("Unsupported data type: {0:?}")]
185    UnsupportedDataType(kernels::DataType),
186
187    /// Other error
188    #[error("{0}")]
189    Other(String),
190}
191
192/// GPU device abstraction
193#[derive(Debug, Clone, Copy, PartialEq, Eq)]
194pub struct GpuDevice {
195    backend: GpuBackend,
196    device_id: usize,
197}
198
199impl GpuDevice {
200    /// Create a new GPU device
201    pub fn new(backend: GpuBackend, device_id: usize) -> Self {
202        Self { backend, device_id }
203    }
204
205    /// Get the backend type
206    pub fn backend(&self) -> GpuBackend {
207        self.backend
208    }
209
210    /// Get the device ID
211    pub fn device_id(&self) -> usize {
212        self.device_id
213    }
214
215    /// Compile a kernel from source
216    pub fn compile_kernel(&self, _source: &str, entrypoint: &str) -> Result<GpuKernel, GpuError> {
217        // Placeholder implementation
218        Ok(GpuKernel {
219            backend: self.backend,
220            entry_point: entrypoint.to_string(),
221        })
222    }
223}
224
225/// GPU kernel abstraction
226pub struct GpuKernel {
227    backend: GpuBackend,
228    entry_point: String,
229}
230
231impl GpuKernel {
232    /// Get the backend type
233    pub fn backend(&self) -> GpuBackend {
234        self.backend
235    }
236
237    /// Get the entry point name
238    pub fn entry_point(&self) -> &str {
239        &self.entry_point
240    }
241}
242
243/// Convert GPU errors to core errors with semantic preservation
244impl From<GpuError> for CoreError {
245    fn from(err: GpuError) -> Self {
246        match err {
247            GpuError::BackendNotAvailable(backend) => CoreError::ComputationError(
248                ErrorContext::new(format!("GPU backend {backend} is not available"))
249                    .with_location(ErrorLocation::new(file!(), line!())),
250            ),
251            GpuError::UnsupportedBackend(backend) => CoreError::NotImplementedError(
252                ErrorContext::new(format!("GPU backend {backend} is not supported"))
253                    .with_location(ErrorLocation::new(file!(), line!())),
254            ),
255            GpuError::BackendNotSupported(backend) => CoreError::NotImplementedError(
256                ErrorContext::new(format!(
257                    "GPU backend {backend:?} is not supported for this kernel"
258                ))
259                .with_location(ErrorLocation::new(file!(), line!())),
260            ),
261            GpuError::BackendNotImplemented(backend) => CoreError::NotImplementedError(
262                ErrorContext::new(format!("GPU backend {backend} is not implemented yet"))
263                    .with_location(ErrorLocation::new(file!(), line!())),
264            ),
265            GpuError::OutOfMemory(details) => CoreError::MemoryError(
266                ErrorContext::new(details.to_string())
267                    .with_location(ErrorLocation::new(file!(), line!())),
268            ),
269            GpuError::KernelCompilationError(msg) => CoreError::ComputationError(
270                ErrorContext::new(msg.to_string())
271                    .with_location(ErrorLocation::new(file!(), line!())),
272            ),
273            GpuError::KernelExecutionError(msg) => CoreError::ComputationError(
274                ErrorContext::new(msg.to_string())
275                    .with_location(ErrorLocation::new(file!(), line!())),
276            ),
277            GpuError::InvalidParameter(msg) => CoreError::InvalidArgument(
278                ErrorContext::new(msg.to_string())
279                    .with_location(ErrorLocation::new(file!(), line!())),
280            ),
281            GpuError::KernelNotFound(name) => CoreError::ComputationError(
282                ErrorContext::new(name.to_string())
283                    .with_location(ErrorLocation::new(file!(), line!())),
284            ),
285            GpuError::SpecializationNotSupported => CoreError::NotImplementedError(
286                ErrorContext::new("Kernel specialization not supported".to_string())
287                    .with_location(ErrorLocation::new(file!(), line!())),
288            ),
289            GpuError::UnsupportedDataType(dtype) => CoreError::TypeError(
290                ErrorContext::new(format!("{dtype:?}"))
291                    .with_location(ErrorLocation::new(file!(), line!())),
292            ),
293            GpuError::Other(msg) => CoreError::ComputationError(
294                ErrorContext::new(msg).with_location(ErrorLocation::new(file!(), line!())),
295            ),
296        }
297    }
298}
299
300/// Trait for types that can be used with GPU operations
301pub trait GpuDataType: Copy + Send + Sync + 'static {}
302
303/// GPU memory pointer abstraction
304#[derive(Debug)]
305pub struct GpuPtr<T: GpuDataType> {
306    ptr: u64,
307    size: usize,
308    phantom: PhantomData<T>,
309}
310
311impl<T: GpuDataType> GpuPtr<T> {
312    /// Allocate GPU memory
313    pub fn allocate(size: usize) -> Result<Self, GpuError> {
314        Ok(GpuPtr {
315            ptr: 0x1000_0000, // Placeholder address
316            size,
317            phantom: PhantomData,
318        })
319    }
320
321    /// Get the raw pointer value
322    pub fn as_ptr(&self) -> u64 {
323        self.ptr
324    }
325
326    /// Get the size in elements
327    pub fn len(&self) -> usize {
328        self.size
329    }
330
331    /// Check if the pointer is empty (size is 0)
332    pub fn is_empty(&self) -> bool {
333        self.size == 0
334    }
335}
336
337/// Kernel argument types for GPU kernel execution
338#[derive(Debug, Clone)]
339pub enum KernelArg<'a, T: GpuDataType> {
340    /// Buffer argument
341    Buffer(&'a GpuPtr<T>),
342    /// Scalar argument
343    Scalar(T),
344}
345
346/// Non-generic kernel argument for mixed-type kernel calls
347#[derive(Debug, Clone)]
348pub enum DynamicKernelArg {
349    /// Buffer argument (type-erased)
350    Buffer(u64), // Raw pointer
351    /// f32 scalar
352    F32(f32),
353    /// f64 scalar
354    F64(f64),
355    /// i32 scalar
356    I32(i32),
357    /// u32 scalar
358    U32(u32),
359    /// usize scalar
360    Usize(usize),
361}
362
363/// GPU communication channel for multi-GPU operations
364pub struct GpuChannel {
365    #[allow(dead_code)]
366    source_device: usize,
367    #[allow(dead_code)]
368    target_device: usize,
369    #[allow(dead_code)]
370    bandwidth: f64, // GB/s
371}
372
373// Implement for common types
374impl GpuDataType for f32 {}
375impl GpuDataType for f64 {}
376impl GpuDataType for i32 {}
377impl GpuDataType for u32 {}
378impl GpuDataType for u8 {}
379impl GpuDataType for i8 {}
380impl GpuDataType for u16 {}
381impl GpuDataType for i16 {}
382impl GpuDataType for u64 {}
383impl GpuDataType for i64 {}
384impl GpuDataType for usize {}
385impl GpuDataType for isize {}
386
387/// GPU buffer
388pub struct GpuBuffer<T: GpuDataType> {
389    inner: Arc<dyn GpuBufferImpl>,
390    size: usize,
391    phantom: PhantomData<T>,
392}
393
394impl<T: GpuDataType> GpuBuffer<T> {
395    /// Create a new buffer with the given size
396    pub(crate) fn new(inner: Arc<dyn GpuBufferImpl>, size: usize) -> Self {
397        Self {
398            inner,
399            size,
400            phantom: PhantomData,
401        }
402    }
403
404    /// Get the size of the buffer in elements
405    pub fn len(&self) -> usize {
406        self.size
407    }
408
409    /// Check if the buffer is empty
410    pub fn is_empty(&self) -> bool {
411        self.size == 0
412    }
413
414    /// Copy data from the host to the device
415    pub fn copy_from_host(&self, data: &[T]) -> Result<(), GpuError> {
416        if data.len() > self.size {
417            return Err(GpuError::InvalidParameter(
418                "Data size exceeds buffer size".to_string(),
419            ));
420        }
421        unsafe {
422            self.inner
423                .copy_from_host(data.as_ptr() as *const u8, std::mem::size_of_val(data));
424        }
425        Ok(())
426    }
427
428    /// Copy data from the device to the host
429    pub fn copy_to_host(&self, data: &mut [T]) -> Result<(), GpuError> {
430        if data.len() > self.size {
431            return Err(GpuError::InvalidParameter(
432                "Data size exceeds buffer size".to_string(),
433            ));
434        }
435        unsafe {
436            self.inner
437                .copy_to_host(data.as_mut_ptr() as *mut u8, std::mem::size_of_val(data));
438        }
439        Ok(())
440    }
441
442    /// Convert the buffer contents to a vector
443    pub fn to_vec(&self) -> Vec<T> {
444        let mut result = vec![unsafe { std::mem::zeroed() }; self.size];
445        let _ = self.copy_to_host(&mut result);
446        result
447    }
448}
449
450/// GPU kernel handle
451#[derive(Clone)]
452pub struct GpuKernelHandle {
453    inner: Arc<dyn GpuKernelImpl>,
454}
455
456impl GpuKernelHandle {
457    /// Create a new kernel handle
458    pub(crate) fn new(inner: Arc<dyn GpuKernelImpl>) -> Self {
459        Self { inner }
460    }
461
462    /// Set a buffer parameter
463    pub fn set_buffer<T: GpuDataType>(&self, name: &str, buffer: &GpuBuffer<T>) {
464        self.inner.set_buffer(name, &buffer.inner);
465    }
466
467    /// Set a u32 parameter
468    pub fn set_u32(&self, name: &str, value: u32) {
469        self.inner.set_u32(name, value);
470    }
471
472    /// Set an i32 parameter
473    pub fn set_i32(&self, name: &str, value: i32) {
474        self.inner.set_i32(name, value);
475    }
476
477    /// Set an f32 parameter
478    pub fn set_f32(&self, name: &str, value: f32) {
479        self.inner.set_f32(name, value);
480    }
481
482    /// Set an f64 parameter
483    pub fn set_f64(&self, name: &str, value: f64) {
484        self.inner.set_f64(name, value);
485    }
486
487    /// Dispatch the kernel with the given work group counts
488    pub fn dispatch(&self, workgroups: [u32; 3]) {
489        self.inner.dispatch(workgroups);
490    }
491}
492
493/// GPU compiler for dynamic kernels
494pub struct GpuCompiler {
495    inner: Arc<dyn GpuCompilerImpl>,
496}
497
498impl GpuCompiler {
499    /// Create a new compiler
500    pub(crate) fn new(inner: Arc<dyn GpuCompilerImpl>) -> Self {
501        Self { inner }
502    }
503
504    /// Compile a kernel from source
505    pub fn compile(&self, source: &str) -> Result<GpuKernelHandle, GpuError> {
506        let kernel = self.inner.compile(source)?;
507        Ok(GpuKernelHandle::new(kernel))
508    }
509
510    /// Compile a kernel for the specified input and output types
511    pub fn compile_kernel<I: GpuDataType, O: GpuDataType>(&self, name: &str) -> GpuKernelHandle {
512        let kernel = self.inner.compile_typed(
513            name,
514            std::any::TypeId::of::<I>(),
515            std::any::TypeId::of::<O>(),
516        );
517        GpuKernelHandle::new(kernel)
518    }
519}
520
521/// GPU context for managing GPU resources and operations
522pub struct GpuContext {
523    inner: Arc<dyn GpuContextImpl>,
524    backend: GpuBackend,
525    kernel_registry: kernels::KernelRegistry,
526}
527
528impl GpuContext {
529    /// Create a new GPU context with the specified backend
530    pub fn new(backend: GpuBackend) -> Result<Self, GpuError> {
531        // First check if the backend is available at compile time
532        if !backend.is_available() {
533            return Err(GpuError::BackendNotAvailable(backend.to_string()));
534        }
535
536        // For non-CPU backends, also check runtime availability
537        if backend != GpuBackend::Cpu {
538            let detection_result = backends::detect_gpu_backends();
539            let backend_available = detection_result
540                .devices
541                .iter()
542                .any(|d| d.backend == backend && d.backend != GpuBackend::Cpu);
543
544            if !backend_available {
545                return Err(GpuError::BackendNotAvailable(format!(
546                    "{backend} (no devices detected at runtime)"
547                )));
548            }
549        }
550
551        let inner = match backend {
552            GpuBackend::Cuda => {
553                #[cfg(feature = "cuda")]
554                {
555                    use crate::gpu::backends::cuda::CudaContext;
556                    match CudaContext::new() {
557                        Ok(ctx) => Arc::new(ctx) as Arc<dyn GpuContextImpl>,
558                        Err(e) => return Err(e),
559                    }
560                }
561                #[cfg(not(feature = "cuda"))]
562                {
563                    return Err(GpuError::UnsupportedBackend(backend));
564                }
565            }
566            GpuBackend::Rocm => {
567                #[cfg(feature = "rocm")]
568                {
569                    // This is just a stub - in a real implementation, we would use the hip-sys crate
570                    // to create a ROCm context and return it
571                    #[cfg(test)]
572                    {
573                        // For testing, we can use a mock implementation
574                        Arc::new(CpuContext::new()) as Arc<dyn GpuContextImpl>
575                    }
576                    #[cfg(not(test))]
577                    {
578                        return Err(GpuError::BackendNotImplemented(backend));
579                    }
580                }
581                #[cfg(not(feature = "rocm"))]
582                {
583                    return Err(GpuError::UnsupportedBackend(backend));
584                }
585            }
586            GpuBackend::Wgpu => {
587                #[cfg(feature = "wgpu_backend")]
588                {
589                    use crate::gpu::backends::wgpu::WebGPUContext;
590                    match WebGPUContext::new() {
591                        Ok(ctx) => Arc::new(ctx) as Arc<dyn GpuContextImpl>,
592                        Err(e) => return Err(e),
593                    }
594                }
595                #[cfg(not(feature = "wgpu_backend"))]
596                {
597                    return Err(GpuError::UnsupportedBackend(backend));
598                }
599            }
600            GpuBackend::Metal => {
601                #[cfg(all(feature = "metal", target_os = "macos"))]
602                {
603                    use crate::gpu::backends::metal::MetalContext;
604                    match MetalContext::new() {
605                        Ok(ctx) => Arc::new(ctx) as Arc<dyn GpuContextImpl>,
606                        Err(e) => return Err(e),
607                    }
608                }
609                #[cfg(not(all(feature = "metal", target_os = "macos")))]
610                {
611                    return Err(GpuError::UnsupportedBackend(backend));
612                }
613            }
614            GpuBackend::OpenCL => {
615                #[cfg(feature = "opencl")]
616                {
617                    use crate::gpu::backends::opencl::OpenCLContext;
618                    match OpenCLContext::new() {
619                        Ok(ctx) => Arc::new(ctx) as Arc<dyn GpuContextImpl>,
620                        Err(e) => return Err(e),
621                    }
622                }
623                #[cfg(not(feature = "opencl"))]
624                {
625                    return Err(GpuError::UnsupportedBackend(backend));
626                }
627            }
628            GpuBackend::Cpu => Arc::new(CpuContext::new()) as Arc<dyn GpuContextImpl>,
629        };
630
631        Ok(Self {
632            inner,
633            backend,
634            kernel_registry: kernels::KernelRegistry::with_default_kernels(),
635        })
636    }
637
638    /// Get the backend type
639    pub fn backend(&self) -> GpuBackend {
640        self.backend
641    }
642
643    /// Get the backend name
644    pub fn backend_name(&self) -> &str {
645        match self.backend {
646            GpuBackend::Cuda => "CUDA",
647            GpuBackend::Rocm => "ROCm",
648            GpuBackend::Wgpu => "WebGPU",
649            GpuBackend::Metal => "Metal",
650            GpuBackend::OpenCL => "OpenCL",
651            GpuBackend::Cpu => "CPU",
652        }
653    }
654
655    /// Create a buffer with the given size
656    pub fn create_buffer<T: GpuDataType>(&self, size: usize) -> GpuBuffer<T> {
657        let byte_size = size.saturating_mul(std::mem::size_of::<T>());
658        let inner = self.inner.create_buffer(byte_size);
659        GpuBuffer::new(inner, size)
660    }
661
662    /// Create a buffer from a slice
663    pub fn create_buffer_from_slice<T: GpuDataType>(&self, data: &[T]) -> GpuBuffer<T> {
664        let buffer = self.create_buffer::<T>(data.len());
665        let _ = buffer.copy_from_host(data);
666        buffer
667    }
668
669    /// Execute a function with a compiler
670    pub fn execute<F, R>(&self, f: F) -> R
671    where
672        F: FnOnce(&GpuCompiler) -> R,
673    {
674        let compiler = GpuCompiler::new(self.inner.create_compiler());
675        f(&compiler)
676    }
677
678    /// Get a kernel from the registry
679    pub fn get_kernel(&self, name: &str) -> Result<GpuKernelHandle, GpuError> {
680        let kernel = self
681            .kernel_registry
682            .get(name)
683            .ok_or_else(|| GpuError::KernelNotFound(name.to_string()))?;
684
685        let kernel_source = kernel.source_for_backend(self.backend)?;
686        let metadata = kernel.metadata();
687
688        let handle = self.compile_kernel_with_metadata(&kernel_source, &metadata)?;
689        Ok(handle)
690    }
691
692    /// Get a specialized kernel from the registry
693    pub fn get_specialized_kernel(
694        &self,
695        name: &str,
696        params: &kernels::KernelParams,
697    ) -> Result<GpuKernelHandle, GpuError> {
698        let specialized = self.kernel_registry.get_specialized(name, params)?;
699        let kernel_source = specialized.source_for_backend(self.backend)?;
700        let metadata = specialized.metadata();
701
702        let handle = self.compile_kernel_with_metadata(&kernel_source, &metadata)?;
703        Ok(handle)
704    }
705
706    /// Compile a kernel with metadata
707    fn compile_kernel_with_metadata(
708        &self,
709        source: &str,
710        _metadata: &kernels::KernelMetadata,
711    ) -> Result<GpuKernelHandle, GpuError> {
712        self.execute(|compiler| compiler.compile(source))
713    }
714
715    /// Get available memory on the device
716    pub fn get_available_memory(&self) -> Option<usize> {
717        // In a real implementation, this would query the device
718        // For now, return a placeholder value
719        Some(1024 * 1024 * 1024) // 1GB
720    }
721
722    /// Get total memory on the device
723    pub fn get_total_memory(&self) -> Option<usize> {
724        // In a real implementation, this would query the device
725        // For now, return a placeholder value
726        Some(4 * 1024 * 1024 * 1024) // 4GB
727    }
728
729    /// Launch a kernel with the given parameters
730    pub fn launch_kernel(
731        &self,
732        kernel_name: &str,
733        grid_size: (usize, usize, usize),
734        block_size: (usize, usize, usize),
735        args: &[DynamicKernelArg],
736    ) -> Result<(), GpuError> {
737        // Placeholder implementation
738        let _ = (kernel_name, grid_size, block_size, args);
739        Ok(())
740    }
741
742    /// Transfer data from host to device asynchronously
743    pub fn transfer_async_host_to_device<T: GpuDataType>(
744        &self,
745        ptr: &GpuPtr<T>,
746        data: &[T],
747    ) -> Result<(), GpuError> {
748        // Placeholder implementation
749        let _ = (ptr, data);
750        Ok(())
751    }
752
753    /// Transfer data from host to device synchronously
754    pub fn transfer_host_to_device<T: GpuDataType>(
755        &self,
756        ptr: &GpuPtr<T>,
757        data: &[T],
758    ) -> Result<(), GpuError> {
759        // Placeholder implementation
760        let _ = (ptr, data);
761        Ok(())
762    }
763
764    /// Transfer data from device to host asynchronously
765    pub fn transfer_async_device_to_host<T: GpuDataType>(
766        &self,
767        ptr: &GpuPtr<T>,
768        data: &mut [T],
769    ) -> Result<(), GpuError> {
770        // Placeholder implementation
771        let _ = (ptr, data);
772        Ok(())
773    }
774
775    /// Transfer data from device to host synchronously
776    pub fn transfer_device_to_host<T: GpuDataType>(
777        &self,
778        ptr: &GpuPtr<T>,
779        data: &mut [T],
780    ) -> Result<(), GpuError> {
781        // Placeholder implementation
782        let _ = (ptr, data);
783        Ok(())
784    }
785
786    /// Execute a kernel with dynamic compilation and parameter passing
787    /// This method is expected by scirs2-vision for GPU operations
788    pub fn execute_kernel(
789        &self,
790        source: &str,
791        buffers: &[GpuBuffer<f32>],
792        work_groups: (u32, u32, u32),
793        int_params: &[u32],
794        float_params: &[f32],
795    ) -> Result<(), GpuError> {
796        // For now, provide a basic implementation that logs the execution
797        // In a real implementation, this would compile and execute the kernel
798        eprintln!(
799            "GPU kernel execution (source length: {}, buffers: {}, workgroups: {:?})",
800            source.len(),
801            buffers.len(),
802            work_groups
803        );
804        eprintln!("Int params: {int_params:?}");
805        eprintln!("Float params: {float_params:?}");
806        Ok(())
807    }
808
809    /// Read data from a GPU buffer
810    /// This method is expected by scirs2-vision for reading GPU results
811    pub fn read_buffer<T: GpuDataType>(&self, buffer: &GpuBuffer<T>) -> Result<Vec<T>, GpuError> {
812        Ok(buffer.to_vec())
813    }
814}
815
816// The following trait definitions would be implemented by backend-specific
817// code in a real implementation
818
819/// GPU buffer implementation trait
820pub(crate) trait GpuBufferImpl: Send + Sync {
821    /// Copy data from host to device
822    unsafe fn copy_from_host(&self, data: *const u8, size: usize);
823
824    /// Copy data from device to host
825    unsafe fn copy_to_host(&self, data: *mut u8, size: usize);
826
827    /// Get a reference to self as Any for downcasting
828    #[allow(dead_code)]
829    fn as_any(&self) -> &dyn std::any::Any;
830
831    /// Get the size of the buffer in bytes
832    #[allow(dead_code)]
833    fn size(&self) -> usize {
834        0 // Default implementation for backward compatibility
835    }
836
837    /// Get the device pointer (for backends that use device pointers)
838    #[allow(dead_code)]
839    fn device_ptr(&self) -> u64 {
840        0 // Default implementation for backward compatibility
841    }
842}
843
844/// GPU kernel implementation trait
845pub(crate) trait GpuKernelImpl: Send + Sync {
846    /// Set a buffer parameter
847    fn set_buffer(&self, name: &str, buffer: &Arc<dyn GpuBufferImpl>);
848
849    /// Set a u32 parameter
850    fn set_u32(&self, name: &str, value: u32);
851
852    /// Set an i32 parameter
853    fn set_i32(&self, name: &str, value: i32);
854
855    /// Set an f32 parameter
856    fn set_f32(&self, name: &str, value: f32);
857
858    /// Set an f64 parameter
859    fn set_f64(&self, name: &str, value: f64);
860
861    /// Dispatch the kernel
862    fn dispatch(&self, workgroups: [u32; 3]);
863}
864
865/// GPU compiler implementation trait
866pub(crate) trait GpuCompilerImpl: Send + Sync {
867    /// Compile a kernel from source
868    fn compile(&self, source: &str) -> Result<Arc<dyn GpuKernelImpl>, GpuError>;
869
870    /// Compile a typed kernel
871    fn compile_typed(
872        &self,
873        name: &str,
874        input_type: std::any::TypeId,
875        output_type: std::any::TypeId,
876    ) -> Arc<dyn GpuKernelImpl>;
877}
878
879/// GPU context implementation trait
880pub(crate) trait GpuContextImpl: Send + Sync {
881    /// Create a buffer
882    fn create_buffer(&self, size: usize) -> Arc<dyn GpuBufferImpl>;
883
884    /// Create a compiler
885    fn create_compiler(&self) -> Arc<dyn GpuCompilerImpl>;
886
887    /// Support dynamic downcasting of concrete context implementations
888    fn as_any(&self) -> &dyn std::any::Any
889    where
890        Self: 'static + Sized,
891    {
892        self
893    }
894}
895
896// CPU fallback implementation
897
898/// CPU context implementation
899struct CpuContext;
900
901impl CpuContext {
902    /// Create a new CPU context
903    fn new() -> Self {
904        Self
905    }
906}
907
908impl GpuContextImpl for CpuContext {
909    fn create_buffer(&self, size: usize) -> Arc<dyn GpuBufferImpl> {
910        Arc::new(CpuBuffer::new(size))
911    }
912
913    fn create_compiler(&self) -> Arc<dyn GpuCompilerImpl> {
914        Arc::new(CpuCompiler)
915    }
916}
917
918/// CPU buffer implementation
919struct CpuBuffer {
920    data: Vec<u8>,
921}
922
923impl CpuBuffer {
924    /// Create a new CPU buffer
925    fn new(size: usize) -> Self {
926        Self {
927            data: vec![0; size],
928        }
929    }
930}
931
932impl GpuBufferImpl for CpuBuffer {
933    unsafe fn copy_from_host(&self, data: *const u8, size: usize) {
934        let mut_self = self as *const Self as *mut Self;
935        let data_ptr = (*mut_self).data.as_mut_ptr();
936        std::ptr::copy_nonoverlapping(data, data_ptr, size);
937    }
938
939    unsafe fn copy_to_host(&self, data: *mut u8, size: usize) {
940        let data_ptr = self.data.as_ptr();
941        std::ptr::copy_nonoverlapping(data_ptr, data, size);
942    }
943
944    fn as_any(&self) -> &dyn std::any::Any {
945        self
946    }
947
948    fn size(&self) -> usize {
949        self.data.len()
950    }
951
952    fn device_ptr(&self) -> u64 {
953        self.data.as_ptr() as u64
954    }
955}
956
957/// CPU compiler implementation
958struct CpuCompiler;
959
960impl GpuCompilerImpl for CpuCompiler {
961    fn compile(&self, source: &str) -> Result<Arc<dyn GpuKernelImpl>, GpuError> {
962        // In a real implementation, we would parse and execute the kernel
963        // For now, just return a dummy implementation
964        Ok(Arc::new(CpuKernel))
965    }
966
967    fn compile_typed(
968        &self,
969        _name: &str,
970        _input_type: std::any::TypeId,
971        _output_type: std::any::TypeId,
972    ) -> Arc<dyn GpuKernelImpl> {
973        // In a real implementation, we would select an appropriate implementation
974        // For now, just return a dummy implementation
975        Arc::new(CpuKernel)
976    }
977}
978
979/// CPU kernel implementation
980struct CpuKernel;
981
982impl GpuKernelImpl for CpuKernel {
983    fn set_buffer(&self, _name: &str, buffer: &Arc<dyn GpuBufferImpl>) {
984        // In a real implementation, we would store the buffer
985    }
986
987    fn set_u32(&self, _name: &str, value: u32) {
988        // In a real implementation, we would store the value
989    }
990
991    fn set_i32(&self, _name: &str, value: i32) {
992        // In a real implementation, we would store the value
993    }
994
995    fn set_f32(&self, _name: &str, value: f32) {
996        // In a real implementation, we would store the value
997    }
998
999    fn set_f64(&self, _name: &str, value: f64) {
1000        // In a real implementation, we would store the value
1001    }
1002
1003    fn dispatch(&self, workgroups: [u32; 3]) {
1004        // In a real implementation, we would execute the kernel
1005    }
1006}
1007
1008// In a real implementation, we would have implementations for other backends
1009// such as CUDA, WebGPU, Metal, and OpenCL.
1010
1011#[cfg(test)]
1012mod tests {
1013    use super::*;
1014
1015    #[test]
1016    fn test_gpu_backend_preferred() {
1017        let backend = GpuBackend::preferred();
1018        // Should return a valid backend
1019        match backend {
1020            GpuBackend::Cuda
1021            | GpuBackend::Rocm
1022            | GpuBackend::Wgpu
1023            | GpuBackend::Metal
1024            | GpuBackend::OpenCL
1025            | GpuBackend::Cpu => {}
1026        }
1027    }
1028
1029    #[test]
1030    fn test_gpu_backend_default() {
1031        let backend = GpuBackend::default();
1032        assert_eq!(backend, GpuBackend::preferred());
1033    }
1034
1035    #[test]
1036    fn test_gpu_backend_is_available() {
1037        let backend = GpuBackend::Cpu;
1038        assert!(backend.is_available());
1039
1040        // Test other backends - availability depends on runtime, not just feature flags
1041        #[cfg(feature = "cuda")]
1042        {
1043            // CUDA feature enabled doesn't guarantee runtime availability
1044            let _ = GpuBackend::Cuda.is_available(); // Just check without asserting
1045        }
1046        #[cfg(not(feature = "cuda"))]
1047        assert!(!GpuBackend::Cuda.is_available());
1048
1049        #[cfg(feature = "rocm")]
1050        {
1051            // ROCm feature enabled doesn't guarantee runtime availability
1052            let _ = GpuBackend::Rocm.is_available(); // Just check without asserting
1053        }
1054        #[cfg(not(feature = "rocm"))]
1055        assert!(!GpuBackend::Rocm.is_available());
1056
1057        #[cfg(all(feature = "metal", target_os = "macos"))]
1058        assert!(GpuBackend::Metal.is_available());
1059        #[cfg(not(all(feature = "metal", target_os = "macos")))]
1060        assert!(!GpuBackend::Metal.is_available());
1061    }
1062
1063    #[test]
1064    fn test_gpu_backend_display() {
1065        assert_eq!(GpuBackend::Cuda.to_string(), "CUDA");
1066        assert_eq!(GpuBackend::Rocm.to_string(), "ROCm");
1067        assert_eq!(GpuBackend::Wgpu.to_string(), "WebGPU");
1068        assert_eq!(GpuBackend::Metal.to_string(), "Metal");
1069        assert_eq!(GpuBackend::OpenCL.to_string(), "OpenCL");
1070        assert_eq!(GpuBackend::Cpu.to_string(), "CPU");
1071    }
1072
1073    #[test]
1074    fn test_gpuerror_from_conversion() {
1075        let gpuerror = GpuError::BackendNotAvailable("CUDA".to_string());
1076        let coreerror: CoreError = gpuerror.into();
1077        match coreerror {
1078            CoreError::ComputationError(_) => {}
1079            _ => panic!("Expected ComputationError"),
1080        }
1081
1082        let gpuerror = GpuError::OutOfMemory("8GB required".to_string());
1083        let coreerror: CoreError = gpuerror.into();
1084        match coreerror {
1085            CoreError::MemoryError(_) => {}
1086            _ => panic!("Expected MemoryError"),
1087        }
1088
1089        let gpuerror = GpuError::InvalidParameter("batch_size must be > 0".to_string());
1090        let coreerror: CoreError = gpuerror.into();
1091        match coreerror {
1092            CoreError::InvalidArgument(_) => {}
1093            _ => panic!("Expected InvalidArgument"),
1094        }
1095
1096        let gpuerror = GpuError::UnsupportedDataType(kernels::DataType::Float16);
1097        let coreerror: CoreError = gpuerror.into();
1098        match coreerror {
1099            CoreError::TypeError(_) => {}
1100            _ => panic!("Expected TypeError"),
1101        }
1102    }
1103
1104    #[test]
1105    fn test_gpu_datatype_trait() {
1106        // Test that various types implement GpuDataType
1107        fn assert_gpu_datatype<T: GpuDataType>() {}
1108
1109        assert_gpu_datatype::<f32>();
1110        assert_gpu_datatype::<f64>();
1111        assert_gpu_datatype::<i32>();
1112        assert_gpu_datatype::<u32>();
1113        assert_gpu_datatype::<u8>();
1114        assert_gpu_datatype::<i8>();
1115        assert_gpu_datatype::<u16>();
1116        assert_gpu_datatype::<i16>();
1117        assert_gpu_datatype::<u64>();
1118        assert_gpu_datatype::<i64>();
1119    }
1120
1121    #[test]
1122    fn test_gpu_buffer_creation() {
1123        let inner = Arc::new(CpuBuffer::new(100));
1124        let buffer = GpuBuffer::<f32>::new(inner, 25);
1125
1126        assert_eq!(buffer.len(), 25);
1127        assert!(!buffer.is_empty());
1128    }
1129
1130    #[test]
1131    fn test_gpu_buffer_empty() {
1132        let inner = Arc::new(CpuBuffer::new(0));
1133        let buffer = GpuBuffer::<f32>::new(inner, 0);
1134
1135        assert_eq!(buffer.len(), 0);
1136        assert!(buffer.is_empty());
1137    }
1138
1139    #[test]
1140    fn test_gpu_buffer_copy_operations() {
1141        let inner = Arc::new(CpuBuffer::new(16));
1142        let buffer = GpuBuffer::<f32>::new(inner, 4);
1143
1144        let data = vec![1.0f32, 2.0, 3.0, 4.0];
1145        let _ = buffer.copy_from_host(&data);
1146
1147        let mut result = vec![0.0f32; 4];
1148        let _ = buffer.copy_to_host(&mut result);
1149
1150        assert_eq!(result, data);
1151    }
1152
1153    #[test]
1154    fn test_gpu_buffer_to_vec() {
1155        let inner = Arc::new(CpuBuffer::new(12));
1156        let buffer = GpuBuffer::<f32>::new(inner, 3);
1157
1158        let data = vec![5.0f32, 6.0, 7.0];
1159        let _ = buffer.copy_from_host(&data);
1160
1161        let result = buffer.to_vec();
1162        assert_eq!(result, data);
1163    }
1164
1165    #[test]
1166    #[should_panic(expected = "Data size exceeds buffer size")]
1167    fn test_gpu_buffer_copy_from_host_overflow() {
1168        let inner = Arc::new(CpuBuffer::new(8));
1169        let buffer = GpuBuffer::<f32>::new(inner, 2);
1170
1171        let data = vec![1.0f32, 2.0, 3.0]; // 3 elements > 2 buffer size
1172        buffer.copy_from_host(&data).expect("Operation failed");
1173    }
1174
1175    #[test]
1176    #[should_panic(expected = "Data size exceeds buffer size")]
1177    fn test_gpu_buffer_copy_to_host_overflow() {
1178        let inner = Arc::new(CpuBuffer::new(8));
1179        let buffer = GpuBuffer::<f32>::new(inner, 2);
1180
1181        let mut data = vec![0.0f32; 3]; // 3 elements > 2 buffer size
1182        buffer.copy_to_host(&mut data).expect("Operation failed");
1183    }
1184
1185    #[test]
1186    fn test_gpu_kernel_handle() {
1187        let kernel = Arc::new(CpuKernel);
1188        let handle = GpuKernelHandle::new(kernel);
1189
1190        // Test setting various parameter types
1191        let buffer = GpuBuffer::<f32>::new(Arc::new(CpuBuffer::new(16)), 4);
1192        handle.set_buffer("input", &buffer);
1193        handle.set_u32("size", 100);
1194        handle.set_i32("offset", -5);
1195        handle.set_f32("scale", 2.5);
1196        handle.set_f64("precision", 0.0001);
1197
1198        // Test dispatch
1199        handle.dispatch([16, 8, 1]);
1200    }
1201
1202    #[test]
1203    fn test_gpu_context_cpu_backend() {
1204        let context = GpuContext::new(GpuBackend::Cpu).expect("Operation failed");
1205        assert_eq!(context.backend(), GpuBackend::Cpu);
1206        assert_eq!(context.backend_name(), "CPU");
1207
1208        // Test memory query methods
1209        assert_eq!(context.get_available_memory(), Some(1024 * 1024 * 1024));
1210        assert_eq!(context.get_total_memory(), Some(4 * 1024 * 1024 * 1024));
1211    }
1212
1213    #[test]
1214    fn test_gpu_context_buffer_creation() {
1215        let context = GpuContext::new(GpuBackend::Cpu).expect("Operation failed");
1216
1217        let buffer = context.create_buffer::<f32>(100);
1218        assert_eq!(buffer.len(), 100);
1219
1220        let data = vec![1.0f32; 50];
1221        let buffer_from_slice = context.create_buffer_from_slice(&data);
1222        assert_eq!(buffer_from_slice.len(), 50);
1223
1224        let result = buffer_from_slice.to_vec();
1225        assert_eq!(result, data);
1226    }
1227
1228    #[test]
1229    fn test_gpu_context_unsupported_backend() {
1230        // Test a backend that's not available
1231        #[cfg(not(feature = "cuda"))]
1232        {
1233            let result = GpuContext::new(GpuBackend::Cuda);
1234            assert!(result.is_err());
1235            match result {
1236                Err(GpuError::UnsupportedBackend(_)) => {}
1237                Err(GpuError::BackendNotAvailable(_)) => {} // Also accept this error
1238                Err(e) => panic!(
1239                    "Expected UnsupportedBackend or BackendNotAvailable error, got: {:?}",
1240                    e
1241                ),
1242                Ok(_) => panic!("Expected error, got Ok"),
1243            }
1244        }
1245    }
1246
1247    #[test]
1248    fn test_gpu_compiler() {
1249        let compiler_impl = Arc::new(CpuCompiler);
1250        let compiler = GpuCompiler::new(compiler_impl);
1251
1252        // Test compiling from source
1253        let kernel = compiler
1254            .compile("dummy kernel source")
1255            .expect("Operation failed");
1256        kernel.dispatch([1, 1, 1]);
1257
1258        // Test typed compilation
1259        let typed_kernel = compiler.compile_kernel::<f32, f32>("vector_add");
1260        typed_kernel.dispatch([32, 1, 1]);
1261    }
1262
1263    #[test]
1264    fn test_gpu_context_execute() {
1265        let context = GpuContext::new(GpuBackend::Cpu).expect("Operation failed");
1266
1267        let result = context.execute(|compiler| compiler.compile("test kernel").is_ok());
1268
1269        assert!(result);
1270    }
1271
1272    #[test]
1273    fn test_gpu_context_kernel_registry() {
1274        let context = GpuContext::new(GpuBackend::Cpu).expect("Operation failed");
1275
1276        // Test getting a non-existent kernel
1277        let result = context.get_kernel("non_existent_kernel");
1278        assert!(result.is_err());
1279        match result {
1280            Err(GpuError::KernelNotFound(_)) => {}
1281            _ => panic!("Expected KernelNotFound error"),
1282        }
1283    }
1284
1285    #[test]
1286    fn test_cpu_buffer_implementation() {
1287        let buffer = CpuBuffer::new(256);
1288        assert_eq!(buffer.data.len(), 256);
1289
1290        // Test that initial data is zeroed
1291        assert!(buffer.data.iter().all(|&b| b == 0));
1292    }
1293
1294    #[test]
1295    fn test_gpuerror_display() {
1296        let error = GpuError::BackendNotAvailable("CUDA".to_string());
1297        assert_eq!(error.to_string(), "GPU backend CUDA is not available");
1298
1299        let error = GpuError::OutOfMemory("allocation failed".to_string());
1300        assert_eq!(error.to_string(), "GPU out of memory: allocation failed");
1301
1302        let error = GpuError::KernelCompilationError("syntax error".to_string());
1303        assert_eq!(error.to_string(), "Kernel compilation error: syntax error");
1304
1305        let error = GpuError::KernelNotFound("gemm".to_string());
1306        assert_eq!(error.to_string(), "Kernel not found: gemm");
1307    }
1308
1309    #[test]
1310    fn test_backend_equality() {
1311        assert_eq!(GpuBackend::Cuda, GpuBackend::Cuda);
1312        assert_ne!(GpuBackend::Cuda, GpuBackend::Rocm);
1313
1314        // Test Clone and Copy
1315        let backend = GpuBackend::Metal;
1316        let cloned = backend;
1317        let copied = backend;
1318        assert_eq!(backend, cloned);
1319        assert_eq!(backend, copied);
1320    }
1321
1322    #[test]
1323    fn test_backend_hash() {
1324        use std::collections::HashSet;
1325
1326        let mut set = HashSet::new();
1327        set.insert(GpuBackend::Cuda);
1328        set.insert(GpuBackend::Rocm);
1329        set.insert(GpuBackend::Cuda); // Duplicate
1330
1331        assert_eq!(set.len(), 2); // Should only have 2 unique entries
1332        assert!(set.contains(&GpuBackend::Cuda));
1333        assert!(set.contains(&GpuBackend::Rocm));
1334    }
1335}
scirs2_core/gpu/mod.rs

scirs2_core/gpu/
mod.rs
