Zq/detach compile

circuit-std-rs/tests/logup.rs

@@ -153,13 +153,14 @@ fn rangeproof_zkcuda_test() {
     let kernel: KernelPrimitive<M31Config> = compile_rangeproof_test_kernel().unwrap();
     let mut ctx: Context<M31Config, _> = Context::new(hint_registry);
 
-    let a = M31::from(1 << 9);
-    let a = ctx.copy_to_device(&a);
+    let a_value = M31::from(1 << 9);
+    let (a, a_id) = ctx.new_device_memory(vec![]);
     let a = a.reshape(&[1]);
     call_kernel!(ctx, kernel, 1, a).unwrap();
 
     type P = Expander<M31Config>;
     let computation_graph = ctx.compile_computation_graph().unwrap();
+    ctx.copy_to_device(&a_value, a_id);
     ctx.solve_witness().unwrap();
     let (prover_setup, verifier_setup) = <P as ProvingSystem<M31Config>>::setup(&computation_graph);
     let proof = P::prove(
@@ -180,13 +181,14 @@ fn rangeproof_zkcuda_test_fail() {
     let kernel: KernelPrimitive<M31Config> = compile_rangeproof_test_kernel().unwrap();
     let mut ctx: Context<M31Config, _> = Context::new(hint_registry);
 
-    let a = M31::from(1 << 11);
-    let a = ctx.copy_to_device(&a);
+    let a_value = M31::from(1 << 11);
+    let (a, a_id) = ctx.new_device_memory(vec![]);
     let a = a.reshape(&[1]);
     call_kernel!(ctx, kernel, 1, a).unwrap();
 
     type P = Expander<M31Config>;
     let computation_graph = ctx.compile_computation_graph().unwrap();
+    ctx.copy_to_device(&a_value, a_id);
     ctx.solve_witness().unwrap();
     let (prover_setup, verifier_setup) = <P as ProvingSystem<M31Config>>::setup(&computation_graph);
     let proof = P::prove(

expander_compiler/bin/zkcuda_matmul.rs

@@ -62,8 +62,8 @@ pub fn zkcuda_matmul<C: Config, P: ProvingSystem<C>, const N: usize>() {
         }
     }
 
-    let a = ctx.copy_to_device(&mat_a);
-    let b = ctx.copy_to_device(&mat_b);
+    let (a, a_id) = ctx.new_device_memory(vec![N, M]);
+    let (b, b_id) = ctx.new_device_memory(vec![M, K]);
     let mut c = None;
     call_kernel!(ctx, kernel_mul_line, N, a, b, mut c).unwrap();
 
@@ -72,6 +72,8 @@ pub fn zkcuda_matmul<C: Config, P: ProvingSystem<C>, const N: usize>() {
     assert_eq!(result, expected_result);
 
     let computation_graph = ctx.compile_computation_graph().unwrap();
+    ctx.copy_to_device(&mat_a, a_id);
+    ctx.copy_to_device(&mat_b, b_id);
     ctx.solve_witness().unwrap();
 
     let (prover_setup, verifier_setup) = P::setup(&computation_graph);

expander_compiler/src/zkcuda/context.rs

@@ -26,13 +26,13 @@ use super::{
 pub use macros::call_kernel;
 
 struct DeviceMemory<C: Config> {
-    values: Vec<SIMDField<C>>,
+    pub values: Vec<SIMDField<C>>,
     required_shape_products: Vec<usize>,
 }
 
 #[derive(Clone, Debug, ExpSerde)]
 pub struct DeviceMemoryHandleRaw {
-    id: usize,
+    pub id: usize,
     shape_history: ShapeHistory,
 }
 
@@ -217,29 +217,50 @@ impl<C: Config, H: HintCaller<CircuitField<C>>> Context<C, H> {
         }
     }
 
+    pub fn new_device_memory(&mut self, shape: Shape) -> (DeviceMemoryHandle, usize) {
+        let t = shape_vec_len(&shape);
+        let required_shape_products = if t == 1 { vec![1] } else { vec![1, t] };
+        self.device_memories.push(DeviceMemory {
+            values: vec![],
+            required_shape_products,
+        });
+        (Some(DeviceMemoryHandleRaw {
+            id: self.device_memories.len() - 1,
+            shape_history: ShapeHistory::new(shape),
+        }), self.device_memories.len() - 1)
+    }
+
     pub fn copy_to_device<T: VecShaped<CircuitField<C>>>(
         &mut self,
         host_memory: &T,
-    ) -> DeviceMemoryHandle {
+        device_memory_id: usize,
+    ) {
+        assert!(device_memory_id < self.device_memories.len(), "The device memory doesn't exist.");
         let (flat, shape) = flatten_shaped(host_memory);
+        // assert_eq!(shape_vec_len(&shape), shape_vec_len(&self.device_memories[device_memory_id].required_shape_products), "The len of values doesn't match.");
         let simd_flat = pack_vec::<C>(&flat);
-        make_device_mem(&mut self.device_memories, simd_flat, shape)
+        self.device_memories[device_memory_id].values = simd_flat;
     }
 
     pub fn copy_to_device_and_pack_simd<T: VecShaped<CircuitField<C>>>(
         &mut self,
         host_memory: &T,
-    ) -> DeviceMemoryHandle {
+        device_memory_id: usize,
+    ) {
+        assert!(device_memory_id < self.device_memories.len(), "The device memory dosen't exist.");
         let (flat, shape) = flatten_shaped_pack_simd(host_memory);
-        make_device_mem(&mut self.device_memories, flat, shape)
+        self.device_memories[device_memory_id].values = flat;
     }
 
     pub fn copy_simd_to_device<T: VecShaped<SIMDField<C>>>(
         &mut self,
         host_memory: &T,
-    ) -> DeviceMemoryHandle {
+        device_memory_id: usize,
+    ) {
+        assert!(device_memory_id < self.device_memories.len(), "The device memory dosen't exist.");
         let (flat, shape) = flatten_shaped(host_memory);
-        make_device_mem(&mut self.device_memories, flat, shape)
+        // assert_eq!(shape_vec_len(&shape), shape_vec_len(&self.device_memories[device_memory_id].required_shape_products), "The len of values doesn't match.");
+        self.device_memories[device_memory_id].values = flat;
     }
 
     pub fn copy_to_host<T: VecShaped<CircuitField<C>> + Default>(
@@ -367,72 +388,7 @@ impl<C: Config, H: HintCaller<CircuitField<C>>> Context<C, H> {
 
         let kernel_id = self.kernel_primitives.add(kernel);
 
-        let mut outputs_tmp = vec![Vec::new(); kernel.io_specs().len()];
-        let mut ir_inputs_all = vec![Vec::new(); kernel.io_specs().len()];
-        let mut chunk_sizes: Vec<Option<usize>> = vec![None; kernel.io_specs().len()];
-        for (((input, &ib), ir_inputs), chunk_size) in ios
-            .iter()
-            .zip(is_broadcast.iter())
-            .zip(ir_inputs_all.iter_mut())
-            .zip(chunk_sizes.iter_mut())
-        {
-            if input.is_none() {
-                continue;
-            }
-            let handle = ensure_handle(input.clone());
-            let values = handle
-                .shape_history
-                .permute_vec(&self.device_memories[handle.id].values);
-            if !ib {
-                *chunk_size = Some(values.len() / num_parallel);
-            }
-            *ir_inputs = values;
-        }
-        let mut ir_inputs_per_parallel = Vec::new();
-        for parallel_i in 0..num_parallel {
-            let mut ir_inputs = vec![SIMDField::<C>::zero(); kernel.ir_for_calling().input_size()];
-            for (i, ((input, input_start), input_end)) in ios
-                .iter()
-                .zip(kernel.ir_input_offsets().iter())
-                .zip(kernel.ir_input_offsets().iter().skip(1))
-                .enumerate()
-            {
-                if input.is_none() {
-                    continue;
-                }
-                self.ir_copy_from_device_memory(
-                    &ir_inputs_all[i],
-                    &mut ir_inputs[*input_start..*input_end],
-                    is_broadcast[i],
-                    parallel_i,
-                    chunk_sizes[i],
-                );
-            }
-            ir_inputs_per_parallel.push(ir_inputs);
-        }
-        let ir_outputs_per_parallel: Vec<Result<Vec<SIMDField<C>>, Error>> = ir_inputs_per_parallel
-            .into_par_iter()
-            .map(|ir_inputs| {
-                kernel
-                    .ir_for_calling()
-                    .eval_safe_simd(ir_inputs, &[], &self.hint_caller)
-            })
-            .collect();
-        for ir_outputs in ir_outputs_per_parallel {
-            let ir_outputs = ir_outputs?;
-            for (((spec, output_start), output_end), out) in kernel
-                .io_specs()
-                .iter()
-                .zip(kernel.ir_output_offsets().iter())
-                .zip(kernel.ir_output_offsets().iter().skip(1))
-                .zip(outputs_tmp.iter_mut())
-            {
-                if !spec.is_output {
-                    continue;
-                }
-                out.extend_from_slice(&ir_outputs[*output_start..*output_end]);
-            }
-        }
+        let outputs_tmp: Vec<Vec<SIMDField::<C>>> = vec![Vec::new(); kernel.io_specs().len()];
         let input_handles = ios.to_vec();
         let mut output_handles = vec![None; kernel.io_specs().len()];
 
@@ -447,12 +403,7 @@ impl<C: Config, H: HintCaller<CircuitField<C>>> Context<C, H> {
                 *output = None;
                 continue;
             }
-            let handle = make_device_mem(
-                &mut self.device_memories,
-                ov,
-                shape_prepend(shape, num_parallel),
-            );
-            let id = handle.as_ref().unwrap().id;
+            let (handle, id) = self.new_device_memory(shape_prepend(shape, num_parallel));
             self.device_memories[id].required_shape_products = merge_shape_products(
                 &handle
                     .as_ref()
@@ -720,6 +671,96 @@ impl<C: Config, H: HintCaller<CircuitField<C>>> Context<C, H> {
         Ok(())
     }
 
+    pub fn solve_result(&mut self) -> Result<(), Error> {
+        for kernel_call in self.kernel_calls.iter() {
+            let kernel = self.kernel_primitives.get(kernel_call.kernel_id);
+            let num_parallel = kernel_call.num_parallel;
+            let is_broadcast = &kernel_call.is_broadcast;
+
+            let mut ir_inputs_all = vec![Vec::new(); kernel.io_specs().len()];
+            let mut chunk_sizes: Vec<Option<usize>> = vec![None; kernel.io_specs().len()];
+            for (((input, &ib), ir_inputs), chunk_size) in kernel_call.input_handles
+                .iter()
+                .zip(is_broadcast.iter())
+                .zip(ir_inputs_all.iter_mut())
+                .zip(chunk_sizes.iter_mut())
+            {
+                if input.is_none() {
+                    continue;
+                }
+                let handle = ensure_handle(input.clone());
+                let values = handle
+                    .shape_history
+                    .permute_vec(&self.device_memories[handle.id].values);
+                if !ib {
+                    *chunk_size = Some(values.len() / num_parallel);
+                }
+                *ir_inputs = values;
+            }
+            let mut ir_inputs_per_parallel = Vec::new();
+            for parallel_i in 0..num_parallel {
+                let mut ir_inputs = vec![SIMDField::<C>::zero(); kernel.ir_for_calling().input_size()];
+                for (i, ((input, input_start), input_end)) in kernel_call.input_handles
+                    .iter()
+                    .zip(kernel.ir_input_offsets().iter())
+                    .zip(kernel.ir_input_offsets().iter().skip(1))
+                    .enumerate()
+                {
+                    if input.is_none() {
+                        continue;
+                    }
+                    self.ir_copy_from_device_memory(
+                        &ir_inputs_all[i],
+                        &mut ir_inputs[*input_start..*input_end],
+                        is_broadcast[i],
+                        parallel_i,
+                        chunk_sizes[i],
+                    );
+                }
+                ir_inputs_per_parallel.push(ir_inputs);
+            }
+            let ir_outputs_per_parallel: Vec<Result<Vec<SIMDField<C>>, Error>> = ir_inputs_per_parallel
+                .into_par_iter()
+                .map(|ir_inputs| {
+                    kernel
+                        .ir_for_calling()
+                        .eval_safe_simd(ir_inputs, &[], &self.hint_caller)
+                })
+                .collect();
+
+            let mut outputs_tmp: Vec<Vec<SIMDField::<C>>> = vec![Vec::new(); kernel.io_specs().len()];
+            for ir_outputs in ir_outputs_per_parallel {
+                let ir_outputs = ir_outputs?;
+                for (((spec, output_start), output_end), out) in kernel
+                    .io_specs()
+                    .iter()
+                    .zip(kernel.ir_output_offsets().iter())
+                    .zip(kernel.ir_output_offsets().iter().skip(1))
+                    .zip(outputs_tmp.iter_mut())
+                {
+                    if !spec.is_output {
+                        continue;
+                    }
+                    out.extend_from_slice(&ir_outputs[*output_start..*output_end]);
+                }
+            }
+
+            for ((output, spec), ov) in kernel_call.output_handles
+                .iter()
+                .zip(kernel.io_specs().iter())
+                .zip(outputs_tmp.into_iter())
+            {
+                if !spec.is_output {
+                    continue;
+                }
+                let output_id = output.as_ref().unwrap().id;
+                self.device_memories[output_id].values = ov;
+            }
+        }
+
+        Ok(())
+    }
+
     // actually, this function computes hints
     pub fn solve_witness(&mut self) -> Result<(), Error> {
         match self.state {
@@ -732,6 +773,8 @@ impl<C: Config, H: HintCaller<CircuitField<C>>> Context<C, H> {
             }
         }
         self.state = ContextState::WitnessDone;
+
+        self.solve_result();
 
         for (kernel_call, proof_template) in
             self.kernel_calls.iter().zip(self.proof_templates.iter())

expander_compiler/src/zkcuda/tests.rs

@@ -68,14 +68,16 @@ fn context_shape_test_1_impl<P: ProvingSystem<M31Config>>() {
 
     // Part 1
     // Since we only use the shape [15, 1], the representation of the vector is "xxxxxxxxxxxxxxx.".
-    let mut a = ctx.copy_to_device(&vec![one; 15]);
+    let a_value_1 = vec![one; 15];
+    let (mut a, a_id_1) = ctx.new_device_memory(vec![15]);
     call_kernel!(ctx, identity_1, 15, mut a).unwrap();
     assert_eq!(ctx.copy_to_host::<Vec<F>>(a), vec![one; 15]);
 
     // Part 2
     // Since we use [15, 1] and [3, 5], the context will find a representation that is compatible with both.
     // The representation of the vector is "xxxxx...xxxxx...xxxxx...........".
-    let mut a = ctx.copy_to_device(&vec![one; 15]);
+    let a_value_2 = vec![one; 15];
+    let (mut a, a_id_2) = ctx.new_device_memory(vec![15]);
     let mut b = a.reshape(&[5, 3]);
     call_kernel!(ctx, identity_1, 15, mut a).unwrap();
     call_kernel!(ctx, identity_3, 5, mut b).unwrap();
@@ -84,6 +86,8 @@ fn context_shape_test_1_impl<P: ProvingSystem<M31Config>>() {
     assert_eq!(ctx.copy_to_host::<Vec<F>>(b), vec![one; 15]);
 
     let computation_graph = ctx.compile_computation_graph().unwrap();
+    ctx.copy_to_device(&a_value_1, a_id_1);
+    ctx.copy_to_device(&a_value_2, a_id_2);
     ctx.solve_witness().unwrap();
 
     // Debugging output and assertions
@@ -143,12 +147,11 @@ fn context_shape_test_1() {
 fn context_shape_test_2() {
     type C = M31Config;
     type F = CircuitField<C>;
-    let one = F::one();
     let identity_3 = compile_identity_3::<C>().unwrap();
     let identity_5 = compile_identity_5::<C>().unwrap();
 
     let mut ctx: Context<C> = Context::default();
-    let a = ctx.copy_to_device(&vec![one; 15]);
+    let (a, _) = ctx.new_device_memory(vec![15]);
     let mut b = a.reshape(&[5, 3]);
     let mut a = a.reshape(&[3, 5]);
     call_kernel!(ctx, identity_5, 3, mut a).unwrap();
@@ -164,7 +167,7 @@ fn context_shape_test_2_success() {
     let identity_5 = compile_identity_5::<C>().unwrap();
 
     let mut ctx: Context<C> = Context::default();
-    let a = ctx.copy_to_device(&vec![one; 15]);
+    let (a, _) = ctx.new_device_memory(vec![15]);
     let b = a.reshape(&[5, 3]);
     let mut a = a.reshape(&[3, 5]);
     call_kernel!(ctx, identity_5, 3, mut a).unwrap();

expander_compiler/tests/cg_mpi_share.rs

@@ -327,7 +327,8 @@ fn get_computation_graph() -> ComputationGraph<M31Config> {
     }
 
     println!("prepare data ok");
-    let p = ctx.copy_to_device(&p);
+    let p_value = p;
+    let (p, p_id) = ctx.new_device_memory(vec![N_PARALLEL, 64 * 8]);
     println!("copy to device ok");
     let mut out = None;
     call_kernel!(ctx, kernel, N_PARALLEL, p, mut out).unwrap();
@@ -338,6 +339,7 @@ fn get_computation_graph() -> ComputationGraph<M31Config> {
     assert_eq!(out[0][0], expected_res[0][0]);
 
     let computation_graph = ctx.compile_computation_graph().unwrap();
+    ctx.copy_to_device(&p_value, p_id);
 
     computation_graph
 }