Tmp for allocator.

Cargo.toml

@@ -61,7 +61,10 @@ tracing-subscriber = "0.3.7"
 wav = "1.0.0"
 yoke = { version = "0.7.2", features = ["derive"] }
 zip = { version = "0.6.6", default-features = false }
-metal = { git = "https://github.com/ivarflakstad/metal-rs.git", features = ["mps"] }
+#metal = { git = "https://github.com/ivarflakstad/metal-rs.git", features = ["mps"] }
+metal = { path = "../metal-rs", features = ["mps"] }
+dispatch = "0.2.0"
+rustc-hash = "1.1"
 
 [profile.release-with-debug]
 inherits = "release"

candle-core/Cargo.toml

@@ -30,6 +30,8 @@ safetensors = { workspace = true }
 thiserror = { workspace = true }
 yoke = { workspace = true }
 zip = { workspace = true }
+dispatch = { workspace = true, optional = true }
+rustc-hash = { workspace = true }
 
 [dev-dependencies]
 anyhow = { workspace = true }
@@ -41,4 +43,4 @@ cuda = ["cudarc", "dep:candle-kernels"]
 cudnn = ["cuda", "cudarc/cudnn"]
 mkl = ["dep:libc", "dep:intel-mkl-src"]
 accelerate = ["dep:libc", "dep:accelerate-src"]
-metal = ["dep:metal", "dep:candle-metal-kernels"]
+metal = ["dep:metal", "dep:candle-metal-kernels", "dep:dispatch"]

candle-core/src/metal_backend.rs

@@ -7,9 +7,10 @@ use candle_metal_kernels::Kernels;
 use half::f16;
 use metal;
 use metal::{Buffer, CommandBuffer, CommandQueue, MTLResourceOptions, NSUInteger};
-use metal::mps::matrix::{Matrix, MatrixDescriptor, MatrixMultiplication};
 use std::sync::{Arc, RwLock};
 use std::collections::HashMap;
+use rustc_hash::FxHashMap;
+use dispatch::{Queue, QueueAttribute};
 
 /// Metal related errors
 #[derive(thiserror::Error, Debug)]
@@ -38,8 +39,9 @@ pub struct MetalDevice {
     device: metal::Device,
     command_queue: metal::CommandQueue,
     command_buffer: Arc<RwLock<metal::CommandBuffer>>,
+    buffers: Arc<RwLock<FxHashMap<usize, Vec<Buffer>>>>,
+    queue : Queue,
     kernels: Arc<candle_metal_kernels::Kernels>,
-    buffers: Arc<RwLock<HashMap<(NSUInteger, MTLResourceOptions), Vec<Arc<Buffer>>>>>,
 }
 
 impl std::fmt::Debug for MetalDevice {
@@ -61,10 +63,6 @@ impl MetalDevice {
         self.registry_id()
     }
 
-    pub fn metal_device(&self) -> &metal::Device {
-        &self.device
-    }
-
     pub fn command_queue(&self) -> &CommandQueue {
         &self.command_queue
     }
@@ -73,28 +71,10 @@ impl MetalDevice {
         self.command_buffer.try_read().unwrap()
     }
 
-    pub fn commit(&self) {
-        let mut old = self.command_buffer.try_write().unwrap();
-        match old.status(){
-            metal::MTLCommandBufferStatus::NotEnqueued | metal::MTLCommandBufferStatus::Enqueued => {
-                old.commit();
-            let command_buffer = self.command_queue.new_command_buffer().to_owned();
-            *old = command_buffer;
-            }
-            _ => {}
-        }
-        // self.command_buffer.replace_with(|_| command_buffer)
-    }
-
     pub fn wait_until_completed(&self) {
         let mut old = self.command_buffer.try_write().unwrap();
-        match old.status(){
-            metal::MTLCommandBufferStatus::NotEnqueued | metal::MTLCommandBufferStatus::Enqueued => {
-                old.commit();
-                old.wait_until_completed();
-            }
-            _ => {}
-        }
+        old.commit();
+        old.wait_until_completed();
         let command_buffer = self.command_queue.new_command_buffer().to_owned();
         *old = command_buffer;
         // self.command_buffer.replace_with(|_| command_buffer)
@@ -108,72 +88,41 @@ impl MetalDevice {
         &self.device
     }
 
-    pub fn new_buffer(&self, element_count: usize, dtype: DType) -> Arc<Buffer >{
-        let size = (element_count * dtype.size_in_bytes()) as NSUInteger;
-        self._new_buffer(size, MTLResourceOptions::StorageModePrivate)
-    }
-
-    fn _new_buffer(&self, size: NSUInteger, option: MTLResourceOptions) -> Arc<Buffer >{
+    pub fn new_buffer(&self, element_count: usize, dtype: DType) -> Buffer {
+        let size = element_count * dtype.size_in_bytes();
         let mut buffers = self.buffers.try_write().unwrap();
-        let subbuffers = buffers.entry((size, option)).or_insert(vec![]);
+        let subbuffers = buffers.entry(size).or_insert(vec![]);
 
         for sub in &mut *subbuffers{
-            if Arc::strong_count(sub) == 1{
+            if sub.retain_count() == 1{
                 return sub.clone();
+                // println!("{size } {:?}", sub.retain_count());
             }
         }
         let new_buffer = self.device
-            .new_buffer(size as NSUInteger, option);
-        let new_buffer = Arc::new(new_buffer);
+            .new_buffer(size as NSUInteger, MTLResourceOptions::StorageModePrivate);
         subbuffers.push(new_buffer.clone());
         new_buffer
     }
 
-    pub fn new_buffer_managed(&self, size: NSUInteger) -> Arc<Buffer> {
-        self._new_buffer(size, MTLResourceOptions::StorageModeManaged)
+    pub fn new_buffer_managed(&self, size: NSUInteger) -> Buffer {
+        self.device
+            .new_buffer(size, MTLResourceOptions::StorageModeManaged)
     }
 
-    pub fn new_buffer_with_data<T>(&self, data: &[T]) -> Arc<Buffer> {
-        let tmp = self.device.new_buffer_with_data(
+    pub fn new_buffer_with_data<T>(&self, data: &[T]) -> Buffer {
+        let option = metal::MTLResourceOptions::StorageModeManaged;
+        self.device.new_buffer_with_data(
             data.as_ptr() as *const core::ffi::c_void,
             core::mem::size_of_val(data) as NSUInteger,
-            metal::MTLResourceOptions::StorageModeManaged
-        );
-        let real = self._new_buffer(
-            core::mem::size_of_val(data) as NSUInteger,
-            metal::MTLResourceOptions::StorageModePrivate
-        );
-        {
-            let command = self.command_buffer();
-            let blit = command.new_blit_command_encoder();
-            blit.copy_from_buffer(&tmp, 0, &real, 0, tmp.length());
-            blit.end_encoding();
-
-        }
-        real
-    }
-
-    pub fn new_matrix(&self, (b, m, n): (NSUInteger, NSUInteger, NSUInteger), size: NSUInteger, type_id: u32, dtype:DType) -> Result<(Matrix, Arc<Buffer>)>{
-        let elem_count = (b * m * n ) as usize;
-        let out_buffer = self.new_buffer(elem_count, dtype);
-
-        let result_descriptor = MatrixDescriptor::init_multiple(m, n, b, n * size, m * n * size, type_id);
-        let result_matrix = Matrix::init_with_buffer_descriptor(
-            &out_buffer,
-            0,
-            &result_descriptor,
+            option,
         )
-        .ok_or_else(|| {
-            MetalError::from("Failed to create matrix multiplication kernel".to_string())
-        })?;
-        Ok((result_matrix, out_buffer))
     }
 }
 
 #[derive(Debug, Clone)]
 pub struct MetalStorage {
-    buffer: Arc<metal::Buffer>,
-    matrices: Arc<RwLock<HashMap<(NSUInteger, NSUInteger, NSUInteger, bool, NSUInteger, NSUInteger, u32), Matrix>>>,
+    buffer: metal::Buffer,
     device: MetalDevice,
     dtype: DType,
 }
@@ -195,11 +144,15 @@ impl BackendStorage for MetalStorage {
 
     fn to_cpu_storage(&self) -> Result<CpuStorage> {
         let buffer = self.device.new_buffer_managed(self.buffer.length());
-        let command_buffer = self.device.command_buffer();
-        let blit = command_buffer.new_blit_command_encoder();
+        {
+        let command = self.device.command_buffer();
+        let blit = command.new_blit_command_encoder();
         blit.copy_from_buffer(&self.buffer, 0, &buffer, 0, self.buffer.length());
         blit.end_encoding();
-        drop(command_buffer);
+
+        }
+
+
         self.device.wait_until_completed();
 
         match self.dtype {
@@ -234,7 +187,7 @@ impl BackendStorage for MetalStorage {
         let el = shape.elem_count();
         let dtype = self.dtype;
 
-        let buffer = device.new_buffer(el, self.dtype);
+        let mut buffer = device.new_buffer(el, self.dtype);
         let command_buffer = self.device.command_buffer();
         if layout.is_contiguous() && layout.start_offset() == 0 {
             let name = match self.dtype {
@@ -249,7 +202,7 @@ impl BackendStorage for MetalStorage {
                 name,
                 el,
                 &self.buffer,
-                &buffer,
+                &mut buffer,
                 mul as f32,
                 add as f32,
             )
@@ -269,17 +222,17 @@ impl BackendStorage for MetalStorage {
                 &self.buffer,
                 layout.stride(),
                 layout.start_offset() * dtype.size_in_bytes(),
-                &buffer,
+                &mut buffer,
                 mul as f32,
                 add as f32,
             )
             .unwrap();
         }
-        Ok(Self::new(
+        Ok(Self {
             buffer,
-            device.clone(),
+            device: device.clone(),
             dtype,
-        ))
+        })
     }
 
     fn powf(&self, _: &Layout, _: f64) -> Result<Self> {
@@ -293,9 +246,8 @@ impl BackendStorage for MetalStorage {
     fn reduce_op(&self, op: ReduceOp, layout: &Layout, sum_dims: &[usize]) -> Result<Self> {
         assert!(sum_dims.len() == 1);
         assert!(sum_dims[0] == layout.shape().rank() - 1);
-        assert!(layout.stride()[sum_dims[0]] == 1);
-        // assert!(layout.is_contiguous());
-        // assert!(layout.start_offset() == 0);
+        assert!(layout.is_contiguous());
+        assert!(layout.start_offset() == 0);
         let device = self.device.clone();
         let src_stride = layout.stride();
         let src_dims = layout.shape().dims();
@@ -330,10 +282,7 @@ impl BackendStorage for MetalStorage {
             Err(crate::Error::EmptyTensor { op: "reduce" }.bt())?
         }
         let dtype = if return_index { DType::U32 } else { self.dtype };
-        if dtype == DType::U32{
-            todo!("Implement this");
-        }
-        let buffer = device.new_buffer(dst_el, dtype);
+        let mut buffer = device.new_buffer(dst_el, dtype);
         let command_buffer = self.device.command_buffer();
         candle_metal_kernels::call_reduce_contiguous(
             &device.device,
@@ -343,16 +292,15 @@ impl BackendStorage for MetalStorage {
             src_el,
             dst_el,
             &self.buffer,
-            layout.start_offset() * self.dtype.size_in_bytes(),
-            &buffer,
+            &mut buffer,
         )
         .map_err(MetalError::from)?;
 
-        Ok(Self::new(
+        Ok(Self {
             buffer,
             device,
             dtype,
-        ))
+        })
     }
 
     fn cmp(&self, _: CmpOp, _: &Self, _: &Layout, _: &Layout) -> Result<Self> {
@@ -363,7 +311,7 @@ impl BackendStorage for MetalStorage {
         let device = self.device();
         let shape = layout.shape();
         let el_count = shape.elem_count();
-        let buffer = device.new_buffer(el_count, dtype);
+        let mut buffer = device.new_buffer(el_count, dtype);
         let command_buffer = device.command_buffer();
         if layout.is_contiguous() {
             let kernel_name = match (self.dtype, dtype) {
@@ -379,7 +327,7 @@ impl BackendStorage for MetalStorage {
                 kernel_name,
                 el_count,
                 &self.buffer,
-                &buffer,
+                &mut buffer,
             )
             .map_err(MetalError::from)?;
         } else {
@@ -398,26 +346,36 @@ impl BackendStorage for MetalStorage {
                 &self.buffer,
                 layout.stride(),
                 layout.start_offset() * self.dtype.size_in_bytes(),
-                &buffer,
+                &mut buffer,
             )
             .map_err(MetalError::from)?;
         }
 
-        Ok(Self::new(
+        Ok(Self {
             buffer,
-            device.clone(),
+            device: device.clone(),
             dtype,
-        ))
+        })
     }
 
     fn unary_impl<B: UnaryOpT>(&self, layout: &Layout) -> Result<Self> {
+
+
         let device = self.device();
         let dtype = self.dtype;
         let shape = layout.shape();
         let el_count = shape.elem_count();
         let buffer = device.new_buffer(el_count, dtype);
-        let command_buffer = device.command_buffer();
+        let metal = self.device.clone();
+        let mut cloned = buffer.clone();
+        let inbuffer = self.buffer.clone();
+        let ldims = layout.dims().to_owned();
+        let lstride = layout.stride().to_owned();
+        let loffset = layout.start_offset() * dtype.size_in_bytes();
         if layout.is_contiguous() && layout.start_offset() == 0 {
+        // self.device.queue.exec_async(move || {
+            let device = metal;
+        let command_buffer = device.command_buffer();
             use candle_metal_kernels::unary::contiguous;
 
             let kernel_name = match (B::KERNEL, dtype) {
@@ -455,11 +413,16 @@ impl BackendStorage for MetalStorage {
                 &device.kernels,
                 kernel_name,
                 el_count,
-                &self.buffer,
-                &buffer,
+                &inbuffer,
+                &mut cloned,
             )
-            .map_err(MetalError::from)?;
+            .unwrap();
+        // });
+
         } else {
+        // self.device.queue.exec_async(move || {
+            let device = metal;
+        let command_buffer = device.command_buffer();
             use candle_metal_kernels::unary::strided;
             let kernel_name = match (B::KERNEL, dtype) {
                 ("ucos", DType::F32) => strided::cos::FLOAT,
@@ -495,23 +458,22 @@ impl BackendStorage for MetalStorage {
                 &command_buffer,
                 &device.kernels,
                 kernel_name,
-                layout.dims(),
-                &self.buffer,
-                layout.stride(),
-                layout.start_offset() * self.dtype.size_in_bytes(),
-                &buffer,
+                &ldims,
+                &inbuffer,
+                &lstride,
+                loffset,
+                &mut cloned,
                 0,
             )
-            .map_err(MetalError::from)?;
+            .unwrap();
+        // });
         }
-        command_buffer.set_label("unary");
-        drop(command_buffer);
-        self.device.commit();
-        Ok(Self::new(
+
+        Ok(Self {
             buffer,
-            device.clone(),
+            device: device.clone(),
             dtype,
-        ))
+        })
     }
 
     fn binary_impl<B: BinaryOpT>(
@@ -524,7 +486,7 @@ impl BackendStorage for MetalStorage {
         let dtype = self.dtype;
         let shape = lhs_l.shape();
         let el_count = shape.elem_count();
-        let buffer = device.new_buffer(el_count, dtype);
+        let mut buffer = device.new_buffer(el_count, dtype);
         let command_buffer = device.command_buffer();
         if (lhs_l.is_contiguous() && lhs_l.start_offset() == 0)
             && (rhs_l.is_contiguous() && rhs_l.start_offset() == 0)
@@ -558,7 +520,7 @@ impl BackendStorage for MetalStorage {
                 el_count,
                 &self.buffer,
                 &rhs.buffer,
-                &buffer,
+                &mut buffer,
             )
             .map_err(MetalError::from)?;
         } else {
@@ -587,18 +549,15 @@ impl BackendStorage for MetalStorage {
                 &rhs.buffer,
                 rhs_l.stride(),
                 rhs_l.start_offset() * rhs.dtype.size_in_bytes(),
-                &buffer,
+                &mut buffer,
             )
             .map_err(MetalError::from)?;
         }
-        command_buffer.set_label("binary");
-        drop(command_buffer);
-        self.device.commit();
-        Ok(Self::new(
+        Ok(Self {
             buffer,
-            device.clone(),
+            device: device.clone(),
             dtype,
-        ))
+        })
     }
 
     fn where_cond(
@@ -614,7 +573,7 @@ impl BackendStorage for MetalStorage {
         let dims = shape.dims();
         let el = shape.elem_count();
         let dtype = t.dtype;
-        let buffer = self.device.new_buffer(el, dtype);
+        let mut buffer = self.device.new_buffer(el, dtype);
         let command_buffer = self.device.command_buffer();
         candle_metal_kernels::call_where_cond_strided(
             &device.device,
@@ -631,14 +590,14 @@ impl BackendStorage for MetalStorage {
             (&t_l.stride(), t_l.start_offset() * t.dtype.size_in_bytes()),
             &f.buffer,
             (&f_l.stride(), f_l.start_offset() * f.dtype.size_in_bytes()),
-            &buffer,
+            &mut buffer,
         )
         .map_err(MetalError::from)?;
-        Ok(Self::new(
+        Ok(Self {
             buffer,
             device,
             dtype,
-        ))
+        })
     }
 
     fn conv1d(
@@ -724,7 +683,7 @@ impl BackendStorage for MetalStorage {
         let dst_el = ids_el * left_size * right_size;
         let dtype = self.dtype;
         let device = self.device();
-        let buffer = device.new_buffer(dst_el, dtype);
+        let mut buffer = device.new_buffer(dst_el, dtype);
         let name = match (ids.dtype, self.dtype) {
             (DType::U32, DType::F32) => "is_u32_f32",
             (DType::U32, DType::F16) => "is_u32_f16",
@@ -741,14 +700,14 @@ impl BackendStorage for MetalStorage {
             dim,
             &self.buffer,
             &ids.buffer,
-            &buffer,
+            &mut buffer,
         )
         .map_err(MetalError::from)?;
-        Ok(Self::new(
+        Ok(Self {
             buffer,
-            device.clone(),
+            device: device.clone(),
             dtype,
-        ))
+        })
     }
 
     fn index_add(
@@ -771,8 +730,7 @@ impl BackendStorage for MetalStorage {
         rhs_l: &Layout,
     ) -> Result<Self> {
         // Create descriptors
-
-        // let start = std::time::Instant::now();
+        use metal::mps::matrix::*;
 
         let (type_id, size) = match self.dtype {
             DType::F32 => (
@@ -786,6 +744,7 @@ impl BackendStorage for MetalStorage {
             dtype => todo!("Dtype for matmul {dtype:?} is not supported"),
         };
 
+        let elem_count = b * m * n;
 
         let lhs_stride = lhs_l.stride();
         let rhs_stride = rhs_l.stride();
@@ -816,73 +775,115 @@ impl BackendStorage for MetalStorage {
                 mnk: (m, n, k),
             })?
         };
+        let stride_left: u64 = match lhs_stride[..lhs_stride.len() - 2] {
+            [s1, stride] if s1 == stride * lhs_l.dims()[1] => stride,
+            [stride] => stride,
+            [] => m * k,
+            _ => Err(MetalError::MatMulNonContiguous {
+                lhs_stride: lhs_stride.to_vec(),
+                rhs_stride: rhs_stride.to_vec(),
+                mnk: (m, n, k),
+            })?,
+        } as u64;
+        let stride_right: u64 = match rhs_stride[..rhs_stride.len() - 2] {
+            [s1, stride] if s1 == stride * rhs_l.dims()[1] => stride,
+            [stride] => stride,
+            [] => n * k,
+            _ => Err(MetalError::MatMulNonContiguous {
+                lhs_stride: lhs_stride.to_vec(),
+                rhs_stride: rhs_stride.to_vec(),
+                mnk: (m, n, k),
+            })?,
+        } as u64;
+
         let b = b as NSUInteger;
         let m = m as NSUInteger;
         let n = n as NSUInteger;
         let k = k as NSUInteger;
 
-        let left_matrix = self.matrix((b, m, k), transpose_left, size,
-            lhs_l.start_offset() as NSUInteger * size, type_id)?;
-        let right_matrix = rhs.matrix((b, k, n), transpose_right, size,
-            rhs_l.start_offset() as NSUInteger * size, type_id)?;
-        let (result_matrix, out_buffer) = self.device.new_matrix((b, m, n), size, type_id, self.dtype)?;
+        let left_descriptor = if transpose_left {
+            MatrixDescriptor::init_single(k, m, m * size, type_id)
+        } else {
+            MatrixDescriptor::init_single(m, k, k * size, type_id)
+        };
+        let right_descriptor = if transpose_right {
+            MatrixDescriptor::init_single(n, k, k * size, type_id)
+        } else {
+            MatrixDescriptor::init_single(k, n, n * size, type_id)
+        };
+        let result_descriptor = MatrixDescriptor::init_single(m, n, n * size, type_id);
+
+        let out_buffer = self.device.new_buffer(elem_count, self.dtype);
 
         let command_buffer = self.device.command_buffer();
+        for bi in 0..b {
+            // Create matrix objects
+            let left_matrix = Matrix::init_with_buffer_descriptor(
+                &self.buffer,
+                (bi * stride_left + lhs_l.start_offset() as u64) * size,
+                &left_descriptor,
+            )
+            .ok_or_else(|| {
+                MetalError::from("Failed to create matrix multiplication kernel".to_string())
+            })?;
+            let right_matrix = Matrix::init_with_buffer_descriptor(
+                &rhs.buffer,
+                (bi * stride_right + rhs_l.start_offset() as u64) * size,
+                &right_descriptor,
+            )
+            .ok_or_else(|| {
+                MetalError::from("Failed to create matrix multiplication kernel".to_string())
+            })?;
 
+            let result_matrix = Matrix::init_with_buffer_descriptor(
+                &out_buffer,
+                bi * m * n * size,
+                &result_descriptor,
+            )
+            .ok_or_else(|| {
+                MetalError::from("Failed to create matrix multiplication kernel".to_string())
+            })?;
 
-        let alpha = 1.0f64;
-        let beta = 0.0f64;
-        // Create kernel
-        let matrix_multiplication = MatrixMultiplication::init(
-            &self.device,
-            transpose_left,
-            transpose_right,
-            m,
-            n,
-            k,
-            alpha,
-            beta,
-        )
-        .ok_or_else(|| {
-            MetalError::from("Failed to create matrix multiplication kernel".to_string())
-        })?;
+            let alpha = 1.0f64;
+            let beta = 0.0f64;
+            // Create kernel
+            let matrix_multiplication = MatrixMultiplication::init(
+                &self.device,
+                transpose_left,
+                transpose_right,
+                m,
+                n,
+                k,
+                alpha,
+                beta,
+            )
+            .ok_or_else(|| {
+                MetalError::from("Failed to create matrix multiplication kernel".to_string())
+            })?;
 
-        // matrix_multiplication.set_batch_size(b);
+            // Encode kernel to command buffer
+            matrix_multiplication.encode_to_command_buffer(
+                &command_buffer,
+                &left_matrix,
+                &right_matrix,
+                &result_matrix,
+            );
+        }
 
-        // Encode kernel to command buffer
-        matrix_multiplication.encode_to_command_buffer(
-            &command_buffer,
-            &left_matrix,
-            &right_matrix,
-            &result_matrix,
-        );
-        command_buffer.set_label("matmul");
-        drop(command_buffer);
-        self.device.commit();
-
-        Ok(Self::new(
-            out_buffer,
-            self.device.clone(),
-            self.dtype(),
-        ))
+        Ok(Self {
+            buffer: out_buffer,
+            device: self.device.clone(),
+            dtype: self.dtype(),
+        })
     }
 
     fn copy_strided_src(&self, dst: &mut Self, dst_offset: usize, src_l: &Layout) -> Result<()> {
-        let command_buffer = self.device.command_buffer();
-        if src_l.is_contiguous(){
-            command_buffer.set_label("copy_contiguous");
-            let blit = command_buffer.new_blit_command_encoder();
-            let src_offset = (src_l.start_offset() * self.dtype.size_in_bytes()) as NSUInteger;
-            let dst_offset = (dst_offset * dst.dtype().size_in_bytes()) as NSUInteger;
-            blit.copy_from_buffer(&self.buffer, src_offset, dst.buffer(), dst_offset, self.buffer.length() - src_offset);
-            blit.end_encoding();
-
-        }else{
         let src_shape = src_l.shape();
         let el_count = src_shape.elem_count();
         if el_count == 0 {
             return Ok(());
         }
+        let command_buffer = self.device.command_buffer();
         let kernel_name = match self.dtype {
             DType::F32 => candle_metal_kernels::unary::strided::copy::FLOAT,
             DType::F16 => candle_metal_kernels::unary::strided::copy::HALF,
@@ -899,58 +900,26 @@ impl BackendStorage for MetalStorage {
             &self.buffer,
             src_l.stride(),
             src_l.start_offset() * self.dtype.size_in_bytes(),
-            &dst.buffer,
+            &mut dst.buffer,
             dst_offset * dst.dtype.size_in_bytes(),
         )
         .map_err(MetalError::from)?;
-        command_buffer.set_label("copy_strided");
-        }
-        drop(command_buffer);
-        self.device.commit();
         Ok(())
     }
 }
 
 impl MetalStorage {
-    pub fn new(buffer: Arc<Buffer>, device: MetalDevice, dtype: DType) -> Self {
-        let matrices = Arc::new(RwLock::new(HashMap::new()));
+    pub fn new(buffer: Buffer, device: MetalDevice, dtype: DType) -> Self {
         Self {
             buffer,
             device,
             dtype,
-            matrices
         }
     }
 
     pub fn buffer(&self) -> &Buffer {
         &self.buffer
     }
-
-    fn matrix(&self, (b, m, n): (NSUInteger, NSUInteger, NSUInteger), transpose: bool, size: NSUInteger, offset: NSUInteger, type_id: u32) -> Result<Matrix>{
-
-        let key = (b, m, n, transpose, size, offset, type_id);
-
-        let mut matrices = self.matrices.try_write().unwrap();
-        if let Some(matrix) = matrices.get(&key){
-            Ok(matrix.clone())
-        }else{
-        let descriptor = if transpose{
-            MatrixDescriptor::init_multiple(n, m, b, m * size, m * n * size, type_id)
-        } else {
-            MatrixDescriptor::init_multiple(m, n, b, n * size, m * n * size, type_id)
-        };
-        let matrix = Matrix::init_with_buffer_descriptor(
-            &self.buffer,
-            offset,
-            &descriptor,
-        )
-        .ok_or_else(|| {
-            MetalError::from("Failed to create matrix multiplication kernel".to_string())
-        })?;
-        matrices.insert(key, matrix.clone());
-        Ok(matrix)
-        }
-    }
 }
 
 impl BackendDevice for MetalDevice {
@@ -975,12 +944,14 @@ impl BackendDevice for MetalDevice {
         let command_queue = device.new_command_queue();
         let command_buffer = Arc::new(RwLock::new(command_queue.new_command_buffer().to_owned()));
         let kernels = Arc::new(Kernels::new());
-        let buffers = Arc::new(RwLock::new(HashMap::new()));
+        let queue = Queue::create("co.huggingface.candle", QueueAttribute::Serial);
+        let buffers = Arc::new(RwLock::new(FxHashMap::default()));
         Ok(Self {
             device,
             command_queue,
             command_buffer,
             buffers,
+            queue,
             kernels,
         })
     }
@@ -1001,7 +972,11 @@ impl BackendDevice for MetalDevice {
 
     fn zeros_impl(&self, shape: &Shape, dtype: DType) -> Result<MetalStorage> {
         let buffer = self.new_buffer(shape.elem_count(), dtype);
-        Ok(MetalStorage::new(buffer, self.clone(), dtype))
+        Ok(MetalStorage {
+            buffer,
+            device: self.clone(),
+            dtype,
+        })
     }
 
     fn ones_impl(&self, shape: &Shape, dtype: DType) -> Result<Self::Storage> {
@@ -1020,11 +995,11 @@ impl BackendDevice for MetalDevice {
             CpuStorage::F32(storage) => self.new_buffer_with_data(storage),
             CpuStorage::F64(storage) => self.new_buffer_with_data(storage),
         };
-        Ok(Self::Storage::new(
-            buffer.into(),
-            self.clone(),
-            storage.dtype(),
-        ))
+        Ok(Self::Storage {
+            buffer,
+            device: self.clone(),
+            dtype: storage.dtype(),
+        })
     }
 
     fn rand_uniform(

candle-examples/Cargo.toml

@@ -57,7 +57,6 @@ flash-attn = ["cuda", "candle-transformers/flash-attn", "dep:candle-flash-attn"]
 mkl = ["dep:intel-mkl-src", "candle/mkl", "candle-nn/mkl", "candle-transformers/mkl"]
 nccl = ["cuda", "cudarc/nccl", "dep:half"]
 onnx = ["candle-onnx"]
-metal = ["candle/metal", "candle-nn/metal"]
 
 [[example]]
 name = "llama_multiprocess"

candle-metal-kernels/Cargo.toml

@@ -10,7 +10,8 @@ categories = ["science"]
 license = "MIT OR Apache-2.0"
 
 [dependencies]
-metal = { git = "https://github.com/ivarflakstad/metal-rs.git", features = ["mps"] }
+# metal = { git = "https://github.com/ivarflakstad/metal-rs.git", features = ["mps"] }
+metal = { path = "../../metal-rs", features = ["mps"] }
 once_cell = "1.18.0"
 thiserror = "1"
 tracing = "0.1.37"

candle-metal-kernels/src/lib.rs

@@ -298,8 +298,11 @@ pub fn call_unary_contiguous(
     kernel_name: unary::contiguous::Kernel,
     length: usize,
     input: &Buffer,
-    output: &Buffer,
+    output: &mut Buffer,
 ) -> Result<(), MetalKernelError> {
+    // println!("Kernel {:?}", kernel_name.0);
+    // assert_eq!(input.length(), output.length());
+
     let pipeline = kernels.load_pipeline(device, Source::Unary, kernel_name.0)?;
     let encoder = command_buffer.new_compute_command_encoder();
     encoder.set_compute_pipeline_state(&pipeline);
@@ -320,7 +323,7 @@ pub fn call_unary_strided(
     input: &Buffer,
     strides: &[usize],
     offset: usize,
-    output: &Buffer,
+    output: &mut Buffer,
     output_offset: usize,
 ) -> Result<(), MetalKernelError> {
     let pipeline = kernels.load_pipeline(device, Source::Unary, name.0)?;
@@ -358,7 +361,7 @@ pub fn call_binary_contiguous(
     length: usize,
     left: &Buffer,
     right: &Buffer,
-    output: &Buffer,
+    output: &mut Buffer,
 ) -> Result<(), MetalKernelError> {
     let pipeline = kernels.load_pipeline(device, Source::Binary, kernel_name.0)?;
 
@@ -386,7 +389,7 @@ pub fn call_binary_strided(
     right_input: &Buffer,
     right_strides: &[usize],
     right_offset: usize,
-    output: &Buffer,
+    output: &mut Buffer,
 ) -> Result<(), MetalKernelError> {
     let pipeline = kernels.load_pipeline(device, Source::Binary, name.0)?;
 
@@ -425,7 +428,7 @@ pub fn call_cast_contiguous(
     kernel_name: &'static str,
     length: usize,
     input: &Buffer,
-    output: &Buffer,
+    output: &mut Buffer,
 ) -> Result<(), MetalKernelError> {
     let pipeline = kernels.load_pipeline(device, Source::Cast, kernel_name)?;
 
@@ -450,7 +453,7 @@ pub fn call_cast_strided(
     input: &Buffer,
     input_strides: &[usize],
     input_offset: usize,
-    output: &Buffer,
+    output: &mut Buffer,
 ) -> Result<(), MetalKernelError> {
     // println!("Kernel {:?}", kernel_name.0);
     // assert_eq!(input.length(), output.length());
@@ -481,8 +484,7 @@ pub fn call_reduce_contiguous(
     length: usize,
     out_length: usize,
     input: &Buffer,
-    input_offset: usize, 
-    output: &Buffer,
+    output: &mut Buffer,
 ) -> Result<(), MetalKernelError> {
     let pipeline = kernels.load_pipeline(device, Source::Reduce, kernel_name)?;
     let elements_to_sum = length / out_length;
@@ -490,7 +492,7 @@ pub fn call_reduce_contiguous(
     let encoder = command_buffer.new_compute_command_encoder();
     encoder.set_compute_pipeline_state(&pipeline);
 
-    set_params!(encoder, (length, elements_to_sum, (input,input_offset), output));
+    set_params!(encoder, (length, elements_to_sum, input, output));
 
     let thread_group_count = MTLSize {
         width: out_length as u64,
@@ -523,7 +525,7 @@ pub fn call_last_softmax(
     length: usize,
     elements_to_sum: usize,
     input: &Buffer,
-    output: &Buffer,
+    output: &mut Buffer,
 ) -> Result<(), MetalKernelError> {
     let pipeline = kernels.load_pipeline(device, Source::Reduce, kernel_name)?;
     let encoder = command_buffer.new_compute_command_encoder();
@@ -564,7 +566,7 @@ pub fn call_affine(
     name: &'static str,
     size: usize,
     input: &Buffer,
-    output: &Buffer,
+    output: &mut Buffer,
     mul: f32,
     add: f32,
 ) -> Result<(), MetalKernelError> {
@@ -590,7 +592,7 @@ pub fn call_affine_strided(
     input: &Buffer,
     input_stride: &[usize],
     input_offset: usize,
-    output: &Buffer,
+    output: &mut Buffer,
     mul: f32,
     add: f32,
 ) -> Result<(), MetalKernelError> {
@@ -632,7 +634,7 @@ pub fn call_where_cond_strided(
     (left_stride, left_offset): (&[usize], usize),
     right: &Buffer,
     (right_stride, right_offset): (&[usize], usize),
-    output: &Buffer,
+    output: &mut Buffer,
 ) -> Result<(), MetalKernelError> {
     let pipeline = kernels.load_pipeline(device, Source::Ternary, name)?;
 
@@ -675,7 +677,7 @@ pub fn call_index_select(
     dim: usize,
     input: &Buffer,
     ids: &Buffer,
-    output: &Buffer,
+    output: &mut Buffer,
 ) -> Result<(), MetalKernelError> {
     let left_size: usize = shape[..dim].iter().product();
     let right_size: usize = shape[dim + 1..].iter().product();
@@ -750,7 +752,7 @@ mod tests {
             name,
             v.len(),
             &input,
-            &output,
+            &mut output,
         )
         .unwrap();
         command_buffer.commit();
@@ -775,7 +777,7 @@ mod tests {
             x.len(),
             &left,
             &right,
-            &output,
+            &mut output,
         )
         .unwrap();
         command_buffer.commit();
@@ -805,7 +807,7 @@ mod tests {
             &input,
             strides,
             offset,
-            &output,
+            &mut output,
             0,
         )
         .unwrap();
@@ -943,7 +945,7 @@ mod tests {
             name,
             v.len(),
             &input,
-            &output,
+            &mut output,
         )
         .unwrap();
         command_buffer.commit();
@@ -984,7 +986,7 @@ mod tests {
             "affine_float",
             size,
             &input,
-            &output,
+            &mut output,
             mul as f32,
             add as f32,
         )
@@ -1021,7 +1023,7 @@ mod tests {
             &input,
             strides,
             0,
-            &output,
+            &mut output,
             mul as f32,
             add as f32,
         )
@@ -1119,7 +1121,7 @@ mod tests {
             dim,
             &embeddings_buffer,
             &ids_buffer,
-            &dst_buffer,
+            &mut dst_buffer,
         )
         .unwrap();
 
@@ -1226,8 +1228,7 @@ mod tests {
             v.len(),
             out_length,
             &input,
-            0, 
-            &output,
+            &mut output,
         )
         .unwrap();
         command_buffer.commit();
@@ -1255,7 +1256,7 @@ mod tests {
             v.len(),
             last_dim,
             &input,
-            &output,
+            &mut output,
         )
         .unwrap();
         command_buffer.commit();
@@ -1355,7 +1356,7 @@ mod tests {
             (&left_stride, left_offset),
             &right,
             (&cond_stride, cond_offset),
-            &output,
+            &mut output,
         )
         .unwrap();
         command_buffer.commit();

candle-metal-kernels/src/reduce.metal

@@ -16,7 +16,7 @@ METAL_FUNC uint get_strided_index(
     return strided_i;
 }
 
-constant int THREADGROUP_SIZE = 1024;
+constant int THREADGROUP_SIZE = 256;
 
 # define REDUCE(FN, NAME, TYPENAME) \
 kernel void NAME( \

candle-nn/Cargo.toml

@@ -19,7 +19,6 @@ num-traits = { workspace = true }
 rayon = { workspace = true }
 safetensors = { workspace = true }
 serde = { workspace = true }
-candle-metal-kernels = { path = "../candle-metal-kernels", version = "0.3.0", optional = true }
 
 [dev-dependencies]
 anyhow = { workspace = true }
@@ -30,4 +29,3 @@ default = []
 accelerate = ["dep:accelerate-src", "candle/accelerate"]
 cuda = ["candle/cuda"]
 mkl = ["dep:intel-mkl-src", "candle/mkl"]
-metal = ["candle/metal", "dep:candle-metal-kernels"]

candle-nn/src/ops.rs

@@ -201,37 +201,6 @@ impl candle::CustomOp1 for SoftmaxLastDim {
         };
         Ok((dst, layout.shape().clone()))
     }
-
-    #[cfg(feature = "metal")]
-    fn metal_fwd(
-        &self,
-        storage: &candle::MetalStorage,
-        layout: &Layout,
-    ) -> Result<(candle::MetalStorage, Shape)> {
-        use candle::backend::{BackendStorage};
-        let device  = storage.device();
-        let command_buffer = device.command_buffer();
-        let kernels = device.kernels();
-        let name = "softmax_float";
-        assert!(layout.is_contiguous());
-        assert!(layout.start_offset() == 0);
-        let last_dim = layout.dims()[layout.shape().rank() - 1];
-        let elem_count = layout.shape().elem_count();
-        let mut output = device.new_buffer(elem_count, storage.dtype());
-        candle_metal_kernels::call_last_softmax(
-            device.metal_device(),
-            &command_buffer,
-            &kernels,
-            name,
-            elem_count,
-            last_dim,
-            storage.buffer(),
-            &mut output,
-        )
-        .unwrap();
-        let newstorage = candle::MetalStorage::new(output, device.clone(), storage.dtype());
-        Ok((newstorage, layout.shape().clone()))
-    }
 }
 
 pub fn softmax_last_dim(xs: &Tensor) -> Result<Tensor> {