Skip to main content

jay/device/
mod.rs

1//! Where a compiled expression runs.
2//!
3//! Placement is deliberately not part of binding. A kernel bound to data is
4//! the same kernel wherever it executes; a [`Device`] says which processor
5//! executes it, and the CPU is one of the answers. `Program::run_on` takes
6//! the device explicitly, and everything a device cannot do falls back to
7//! the CPU path with a reason a caller can read.
8//!
9//! What runs on a GPU this phase is the fused elementwise kernel and nothing
10//! else. [`crate::fuse`] already compiles a chain of scalar verbs into a
11//! postfix program over blocks, with an optional reduction folded in — that
12//! is a kernel description, and `codegen` turns it into WGSL at run time.
13//! Anything outside a fused node, and any fused node the generator declines,
14//! runs where it always ran.
15//!
16//! # Precision
17//!
18//! libjay computes floats in f64. WGSL can express f64, but almost no
19//! adapter implements it: Metal has no double at all, and on Vulkan it is a
20//! feature (`SHADER_F64`) that many drivers leave off. A device that cannot
21//! run f64 therefore **declines** by default rather than quietly computing
22//! in f32 — losing precision is not a performance decision libjay may take
23//! on the caller's behalf. `Precision::F32` is the caller saying, in so many
24//! words, that they want it.
25//!
26//! # Residency
27//!
28//! [`Device::upload`] returns an array that carries its own location: the
29//! buffer it hands back keeps the device allocation alive inside its owner
30//! handle, so passing it to a later run uploads nothing. The array is an
31//! ordinary [`Array`] otherwise, which is what lets a fallback to the CPU
32//! read it without asking anyone.
33
34mod codegen;
35mod gpu;
36
37use std::any::Any;
38use std::sync::Arc;
39
40use crate::array::{Array, Buf, Data, Owner};
41use crate::dtype::DType;
42use crate::fuse::{FusedKernel, Yield};
43
44pub use codegen::Precision;
45
46/// One adapter, as the machine reports it.
47#[derive(Clone, Debug, PartialEq, Eq)]
48pub struct DeviceInfo {
49    /// The adapter's own name, e.g. "AMD Radeon Pro 560".
50    pub name: String,
51    /// The API behind it: Metal, Vulkan, DX12.
52    pub backend: String,
53    /// discrete GPU, integrated GPU, virtual GPU, CPU, or other.
54    pub kind: String,
55    /// Whether shaders on this adapter can compute in f64. Where this is
56    /// false, only an explicit `Precision::F32` reaches the device.
57    pub f64: bool,
58}
59
60/// Every adapter this machine offers, in the order the backend ranks them.
61/// Empty on a machine with no GPU, which is not an error.
62pub fn available() -> Vec<DeviceInfo> {
63    gpu::enumerate()
64}
65
66/// Where a program runs.
67///
68/// Cloning is cheap: the GPU handle is shared, so two clones name the same
69/// adapter and the same uploaded buffers.
70#[derive(Clone)]
71pub struct Device {
72    at: Where,
73    precision: Precision,
74}
75
76#[derive(Clone)]
77enum Where {
78    Cpu,
79    Gpu(Arc<dyn Backend>),
80}
81
82impl std::fmt::Debug for Device {
83    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
84        match &self.at {
85            Where::Cpu => write!(f, "Device(cpu)"),
86            Where::Gpu(g) => {
87                write!(f, "Device({}, {:?})", g.info().name, self.precision)
88            }
89        }
90    }
91}
92
93impl Device {
94    /// The processor everything already ran on.
95    pub fn cpu() -> Device {
96        Device { at: Where::Cpu, precision: Precision::F64 }
97    }
98
99    /// The machine's preferred adapter, or None where there is none.
100    ///
101    /// The adapter is opened once per process and shared; asking twice
102    /// costs nothing and hands back the same device.
103    pub fn default_gpu() -> Option<Device> {
104        Some(Device { at: Where::Gpu(gpu::shared()?), precision: Precision::F64 })
105    }
106
107    /// The same device, computing in `p`.
108    ///
109    /// `Precision::F32` is an explicit request to compute a f64 program in
110    /// single precision. It is the only way a machine whose shaders have no
111    /// f64 runs anything at all on its GPU.
112    pub fn with_precision(&self, p: Precision) -> Device {
113        Device { at: self.at.clone(), precision: p }
114    }
115
116    pub fn precision(&self) -> Precision {
117        self.precision
118    }
119
120    pub fn is_gpu(&self) -> bool {
121        matches!(self.at, Where::Gpu(_))
122    }
123
124    /// What this device is, or None for the CPU.
125    pub fn info(&self) -> Option<&DeviceInfo> {
126        match &self.at {
127            Where::Cpu => None,
128            Where::Gpu(g) => Some(g.info()),
129        }
130    }
131
132    fn backend(&self) -> Option<&Arc<dyn Backend>> {
133        match &self.at {
134            Where::Cpu => None,
135            Where::Gpu(g) => Some(g),
136        }
137    }
138
139    /// `y` with its elements resident on this device.
140    ///
141    /// The result is an ordinary array — same shape, same values, readable
142    /// by anything — that additionally holds the device allocation, so a
143    /// run that reaches the device with it uploads nothing. Uploading to
144    /// the CPU is the identity.
145    pub fn upload(&self, y: &Array) -> Result<Array, DeviceError> {
146        let Some(backend) = self.backend() else { return Ok(y.clone()) };
147        // What goes to the device is the elements in row-major order; a
148        // column-major argument is laid out once before it leaves.
149        let laid_out;
150        let y = if y.is_row_major() {
151            y
152        } else {
153            laid_out = y.to_row_major();
154            &laid_out
155        };
156        // A float array is uploaded from its own buffer; anything else is
157        // converted once, and the conversion becomes the host mirror.
158        let host = match &y.data {
159            Data::F64(_) => Host::Same(y.data.clone()),
160            Data::I64(v) => Host::Made(v.iter().map(|&x| x as f64).collect()),
161            Data::Bool(v) => Host::Made(v.iter().map(|&x| x as f64).collect()),
162            _ => {
163                return Err(DeviceError(
164                    "only boolean, integer and float arrays can be uploaded".into(),
165                ))
166            }
167        };
168        let handle = backend.upload(host.values(), self.precision)?;
169        let resident = Arc::new(Resident {
170            device: Arc::as_ptr(backend) as *const () as usize,
171            precision: self.precision,
172            elems: host.values().len(),
173            handle,
174            host,
175        });
176        let values = resident.host.values();
177        let (ptr, len) = (values.as_ptr(), values.len());
178        // SAFETY: the elements live inside the `Arc` this owner holds — in
179        // the array's own refcounted buffer or in the vector made for the
180        // upload — so they stay valid and unmutated for as long as the
181        // buffer that borrows them does.
182        let owner: Owner = resident;
183        Ok(Array::new(y.shape.clone(), Data::F64(unsafe { Buf::foreign(ptr, len, owner) })))
184    }
185
186    /// Is this array already resident on this device, at this precision?
187    pub fn holds(&self, y: &Array) -> bool {
188        self.backend().is_some_and(|b| resident_on(y, b, self.precision).is_some())
189    }
190}
191
192/// The elements an uploaded array's buffer borrows: the array's own, when
193/// it was already f64, or the conversion the upload had to make anyway.
194enum Host {
195    Same(Data),
196    Made(Vec<f64>),
197}
198
199impl Host {
200    fn values(&self) -> &[f64] {
201        match self {
202            Host::Same(Data::F64(v)) => v.as_slice(),
203            Host::Same(_) => &[],
204            Host::Made(v) => v,
205        }
206    }
207}
208
209/// A device allocation, and the host mirror an ordinary array reads.
210struct Resident {
211    /// Identifies the backend the allocation belongs to. Two devices that
212    /// share a backend share their uploads; a buffer from another one is
213    /// not usable and is re-uploaded.
214    device: usize,
215    precision: Precision,
216    elems: usize,
217    handle: Handle,
218    host: Host,
219}
220
221/// The device allocation behind this array's buffer, when it has one that
222/// belongs to `backend` at `precision`.
223fn resident_on<'a>(
224    y: &'a Array,
225    backend: &Arc<dyn Backend>,
226    precision: Precision,
227) -> Option<&'a Handle> {
228    let owner = y.data.owner()?;
229    let r: &Resident = owner.downcast_ref()?;
230    let same = r.device == Arc::as_ptr(backend) as *const () as usize
231        && r.precision == precision
232        && r.elems == y.data.len();
233    same.then_some(&r.handle)
234}
235
236/// A device operation that could not be carried out. These are host-side
237/// failures — no adapter, an allocation refused, a shader the driver would
238/// not compile — not language errors, and they never reach a program's
239/// diagnostics: the caller sees them from [`Device::upload`], and a run
240/// turns them into a fallback to the CPU.
241#[derive(Clone, Debug)]
242pub struct DeviceError(pub String);
243
244impl std::fmt::Display for DeviceError {
245    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
246        f.write_str(&self.0)
247    }
248}
249
250impl std::error::Error for DeviceError {}
251
252/// An allocation on a device, opaque to everything but the backend that
253/// made it.
254pub(crate) struct Handle(pub Arc<dyn Any + Send + Sync>);
255
256/// One dispatch: a generated shader, the buffers it reads, and the grid.
257pub(crate) struct Plan<'a> {
258    pub source: &'a str,
259    pub entry: &'a str,
260    pub inputs: &'a [&'a Handle],
261    /// Elements the shader writes.
262    pub out_elems: usize,
263    pub elem_size: usize,
264    /// Elements the kernel maps over.
265    pub n: u32,
266    /// Threads in the grid, for the grid-stride loop a reduction runs.
267    pub stride: u32,
268    pub groups: u32,
269}
270
271/// What a device backend must provide for the fused-kernel path.
272///
273/// One implementation, [`gpu`], covers Metal, Vulkan and DX12 through wgpu.
274/// A second — CUDA, say — is another implementation of this trait and
275/// nothing else: the kernel description, the code generator and the
276/// placement rules above it are backend-agnostic.
277pub(crate) trait Backend: Send + Sync + 'static {
278    fn info(&self) -> &DeviceInfo;
279    /// Copy elements into a device buffer, in the device's element type.
280    fn upload(&self, values: &[f64], p: Precision) -> Result<Handle, DeviceError>;
281    /// Compile (or reuse) the plan's shader and run it, returning what it
282    /// wrote.
283    fn dispatch(&self, plan: &Plan<'_>) -> Result<Vec<u8>, DeviceError>;
284}
285
286// --------------------------------------------------------------- placement
287
288/// Why a fused node ran on the CPU although a device was asked for.
289///
290/// Every one of these is a statement about the kernel or its data, decided
291/// before any work happens, except [`Failed`](Refusal::Failed), which is the
292/// device itself refusing at run time. A fallback is always correct and only
293/// ever slower.
294#[derive(Clone, Debug, PartialEq, Eq)]
295pub enum Refusal {
296    /// The kernel's working type is i64. WGSL has no 64-bit integer
297    /// arithmetic on most adapters, so integer chains stay on the CPU.
298    Integer,
299    /// The chain's result is not f64 — a comparison at the root, a tally.
300    /// Narrowing a device result is not worth the risk this phase.
301    NotFloat,
302    /// The adapter has no f64 in shaders and the caller did not ask for
303    /// f32. See the module note on precision.
304    NoF64,
305    /// The generator does not cover one of the chain's operations at this
306    /// precision.
307    Unsupported(&'static str),
308    /// The kernel itself would decline these inputs, device or no device.
309    Declined,
310    /// Too little data to pay for a dispatch.
311    TooSmall,
312    /// The device refused: an allocation, a shader, a queue submission.
313    Failed(String),
314}
315
316impl Refusal {
317    pub fn reason(&self) -> String {
318        match self {
319            Refusal::Integer => "the chain computes in 64-bit integers".into(),
320            Refusal::NotFloat => "the chain's result is not a float array".into(),
321            Refusal::NoF64 => {
322                "this adapter has no f64 in shaders; pass precision=\"f32\" to run anyway".into()
323            }
324            Refusal::Unsupported(op) => format!("`{op}` has no shader form here"),
325            Refusal::Declined => "the fused kernel declined these inputs".into(),
326            Refusal::TooSmall => "there is too little data to pay for a dispatch".into(),
327            Refusal::Failed(e) => format!("the device refused: {e}"),
328        }
329    }
330}
331
332/// Where a fused node's arithmetic happened.
333#[derive(Clone, Debug, PartialEq, Eq)]
334pub enum Placement {
335    /// No device was asked for, so the question did not arise.
336    Default,
337    Gpu,
338    /// The device would not take it, for this reason.
339    Cpu(Refusal),
340}
341
342impl std::fmt::Display for Placement {
343    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
344        match self {
345            Placement::Default => Ok(()),
346            Placement::Gpu => write!(f, "device: gpu"),
347            Placement::Cpu(why) => write!(f, "device: cpu ({})", why.reason()),
348        }
349    }
350}
351
352/// Least elements worth a dispatch.
353///
354/// Below this the round trip — two submissions, a queue wait, a readback —
355/// costs more than the whole pass does on the CPU, whatever the arithmetic
356/// per element is. Measured on a Radeon Pro 560 against the 8-thread CPU
357/// path, the crossover for the simplest chain (`+/ w * x`) is around a
358/// million elements; the threshold is set an octave below that so that a
359/// heavier chain, which crosses over sooner, is not kept off the device.
360pub const MIN_ELEMS: usize = 1 << 19;
361
362/// Run a fused kernel on `device`, or say why it will not.
363pub(crate) fn try_run(
364    device: &Device,
365    k: &FusedKernel,
366    inputs: &[Array],
367) -> Result<Array, Refusal> {
368    let backend = device.backend().ok_or(Refusal::Declined)?;
369    let precision = device.precision;
370    if precision == Precision::F64 && !backend.info().f64 {
371        return Err(Refusal::NoF64);
372    }
373    // A tally never touches values, and a reduction over one item is the
374    // item itself: both are the fused path's own answers, exactly.
375    if k.yields() == Yield::Tally {
376        return Err(Refusal::Declined);
377    }
378    let Some(Some(shape)) = crate::fuse::common_shape(inputs) else {
379        return Err(Refusal::Declined);
380    };
381    let n: usize = shape.iter().product();
382    if n < MIN_ELEMS {
383        return Err(Refusal::TooSmall);
384    }
385    let reducing = k.reduce().is_some();
386    if reducing && shape.len() != 1 {
387        return Err(Refusal::Declined);
388    }
389    let (working, root) = crate::fuse::working_type(k, inputs).ok_or(Refusal::Declined)?;
390    if working != DType::F64 {
391        return Err(Refusal::Integer);
392    }
393    if root != DType::F64 {
394        return Err(Refusal::NotFloat);
395    }
396
397    // Every input either lies on the device already or goes up now. A
398    // rank-0 input becomes a one-element buffer the shader reads at 0.
399    let splat: Vec<bool> = inputs.iter().map(|a| a.rank() == 0).collect();
400    let source = codegen::wgsl(k, &splat, precision).map_err(Refusal::Unsupported)?;
401
402    let mut temporaries: Vec<Handle> = Vec::new();
403    let mut slots: Vec<Option<&Handle>> = Vec::with_capacity(inputs.len());
404    for a in inputs {
405        match resident_on(a, backend, precision) {
406            Some(h) => slots.push(Some(h)),
407            None => {
408                // A float argument goes up from its own buffer; only a
409                // boolean or integer one is converted, and copying tens of
410                // megabytes for nothing is exactly what that would be.
411                let h = match &a.data {
412                    Data::F64(v) => backend.upload(v.as_slice(), precision),
413                    _ => backend.upload(&as_f64_vec(a), precision),
414                }
415                .map_err(|e| Refusal::Failed(e.0))?;
416                temporaries.push(h);
417                slots.push(None);
418            }
419        }
420    }
421    let mut next = 0usize;
422    let buffers: Vec<&Handle> = slots
423        .iter()
424        .map(|s| match s {
425            Some(h) => *h,
426            None => {
427                let h = &temporaries[next];
428                next += 1;
429                h
430            }
431        })
432        .collect();
433
434    let elem_size = precision.size();
435    let out = if reducing {
436        let groups = codegen::groups_for(n);
437        let plan = Plan {
438            source: &source,
439            entry: codegen::REDUCE,
440            inputs: &buffers,
441            out_elems: groups,
442            elem_size,
443            n: n as u32,
444            stride: (groups * codegen::WORKGROUP) as u32,
445            groups: groups as u32,
446        };
447        let bytes = backend.dispatch(&plan).map_err(|e| Refusal::Failed(e.0))?;
448        let partials = codegen::from_bytes(&bytes, precision, groups);
449        // The partials combine right to left, as the CPU path's chunks do.
450        // Only associative operations are absorbed, so this is the same
451        // regrouping the float contract (§5.9) already allows.
452        let op = k.reduce().expect("reducing");
453        let mut acc = *partials.last().ok_or(Refusal::Declined)?;
454        for &v in partials[..partials.len() - 1].iter().rev() {
455            acc = crate::fuse::step(op, v, acc).ok_or(Refusal::Declined)?;
456        }
457        Array::scalar_f64(acc)
458    } else {
459        let plan = Plan {
460            source: &source,
461            entry: codegen::MAP,
462            inputs: &buffers,
463            out_elems: n,
464            elem_size,
465            n: n as u32,
466            stride: 0,
467            groups: n.div_ceil(codegen::WORKGROUP) as u32,
468        };
469        let bytes = backend.dispatch(&plan).map_err(|e| Refusal::Failed(e.0))?;
470        let values = codegen::from_bytes(&bytes, precision, n);
471        Array::new(shape, Data::F64(values.into()))
472    };
473    Ok(out)
474}
475
476fn as_f64_vec(a: &Array) -> Vec<f64> {
477    match &a.data {
478        Data::F64(v) => v.as_slice().to_vec(),
479        Data::I64(v) => v.iter().map(|&x| x as f64).collect(),
480        Data::Bool(v) => v.iter().map(|&x| x as f64).collect(),
481        _ => Vec::new(),
482    }
483}
484
485#[cfg(test)]
486mod tests {
487    use super::*;
488
489    #[test]
490    fn the_cpu_is_always_a_device() {
491        let d = Device::cpu();
492        assert!(!d.is_gpu());
493        assert!(d.info().is_none());
494        let a = Array::from_f64(vec![1.0, 2.0]);
495        assert_eq!(d.upload(&a).expect("cpu upload"), a);
496    }
497
498    #[test]
499    fn every_refusal_says_something() {
500        for r in [
501            Refusal::Integer,
502            Refusal::NotFloat,
503            Refusal::NoF64,
504            Refusal::Unsupported("^"),
505            Refusal::Declined,
506            Refusal::TooSmall,
507            Refusal::Failed("no adapter".into()),
508        ] {
509            assert!(!r.reason().is_empty());
510        }
511    }
512}