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12_Matmul_with_diagonal_matrices_ • shared_mem_diag_matmul_base_base

Level 1 • Task 12
import torch
import torch.nn as nn
import torch.nn.functional as F


def module_fn(A, B):
    """
    Performs a matrix multiplication of a diagonal matrix with another matrix.

    Args:
        A (torch.Tensor): A 1D tensor representing the diagonal of the diagonal matrix. Shape: (N,).
        B (torch.Tensor): A 2D tensor representing the second matrix. Shape: (N, M).

    Returns:
        torch.Tensor: The result of the matrix multiplication. Shape: (N, M).
    """
    return torch.diag(A) @ B


class Model(nn.Module):
    """
    Simple model that performs a matrix multiplication of a diagonal matrix with another matrix.
    C = diag(A) * B
    """

    def __init__(self):
        super(Model, self).__init__()

    def forward(self, A, B, fn=module_fn):
        return fn(A, B)


M = 4096
N = 4096


def get_inputs():
    A = torch.randn(N)
    B = torch.randn(N, M)
    return [A, B]


def get_init_inputs():
    return []  # No special initialization inputs needed

import torch
import torch.nn as nn

class Model(nn.Module):
    """
    Simple model that performs a matrix multiplication of a diagonal matrix with another matrix.
    C = diag(A) * B
    """
    def __init__(self):
        super(Model, self).__init__()
    
    def forward(self, A, B):
        """
        Performs the matrix multiplication.

        Args:
            A (torch.Tensor): A 1D tensor representing the diagonal of the diagonal matrix. Shape: (N,).
            B (torch.Tensor): A 2D tensor representing the second matrix. Shape: (N, M).

        Returns:
            torch.Tensor: The result of the matrix multiplication. Shape: (N, M).
        """
        return torch.diag(A) @ B

M = 4096
N = 4096

def get_inputs():
    A = torch.randn(N)
    B = torch.randn(N, M)
    return [A, B]

def get_init_inputs():
    return []  # No special initialization inputs needed
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Kernel Information

Operation Name 12_Matmul_with_diagonal_matrices_
Level ID 1
Task ID 12
Kernel Name shared_mem_diag_matmul_base_base
CUDA Speedup (Native) 54.400x
CUDA Speedup (Compile) 55.456x
CUDA Runtime 0.051 ms
PyTorch Runtime (Native) 2.774 ms
PyTorch Runtime (Compile) 2.828 ms
Correct True
Max Diff (vs. Reference) 0.000000
Model bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0
Temperature 0.00
View Experiment Progress Details

Related Kernels (Level 1, Task 12 • 12_Matmul_with_diagonal_matrices_)

Rank Kernel Name Runtime (ms) Speedup Native Speedup Compile
🥇 flat_no_atomic_diag_matmul_base 0.05 54.40 55.46
🥇 shared_mem_diag_matmul_base_base 0.05 54.40 55.46
🥇 hybrid_diag_matmul_base 0.05 54.40 55.46
🥇 adaptive_diag_matmul_base 0.05 54.40 55.46
🥇 optimized_block_size_diag_matmul_base 0.05 54.40 55.46
🥇 hybrid_diag_matmul_base 0.05 54.40 55.46
🥇 adaptive_diag_matmul_base 0.05 54.40 55.46
🥇 diag_matmul_modular_edit_1 0.05 54.40 55.46
🥇 diag_matmul_warp_sync_base 0.05 54.40 55.46
🥇 diag_matmul_shared_min_sync_edit_1 0.05 54.40 55.46
🥇 diag_matmul_readonly_base 0.05 54.40 55.46
🥇 diag_matmul_modular_base 0.05 54.40 55.46
🥇 diag_matmul_shared_min_sync_base 0.05 54.40 55.46
🥇 stride_loop_diag_matmul_base 0.05 54.40 55.46
🥇 shared_memory_optimized_diag_matmul_base 0.05 54.40 55.46
🥇 unified_diag_matmul_base 0.05 54.40 55.46
🥇 diag_matmul_modular_base 0.05 54.40 55.46
🥇 adaptive_diag_matmul_edit_1 0.05 54.40 55.46
19 coalesced_diag_matmul_base 0.05 53.35 54.39
19 diag_matmul_readonly_edit_1 0.05 53.35 54.39 
#include <torch/extension.h>
#include <cuda.h>
#include <cuda_runtime.h>

template<bool UseVector>
__global__ void shared_diag_matmul_kernel(
    const float* __restrict__ A,
    const float* __restrict__ B,
    float* __restrict__ C,
    const int64_t N,
    const int64_t M,
    const int64_t elements_per_thread
) {
    __shared__ float shared_diag;  // Cache diagonal value in shared memory
    
    const int tid = threadIdx.x;
    const int bid = blockIdx.x;
    const int num_threads = blockDim.x;
    const int global_idx = bid * num_threads + tid;
    
    if (UseVector) {
        // Vectorized version
        const float4* B_vec = reinterpret_cast<const float4*>(B);
        float4* C_vec = reinterpret_cast<float4*>(C);
        const int vec_M = M >> 2;  // M/4
        
        for (int i = global_idx; i < N * vec_M; i += gridDim.x * num_threads) {
            const int row = i / vec_M;
            
            // First thread in block loads diagonal value
            if (tid == 0) {
                shared_diag = A[row];
            }
            __syncthreads();
            
            float4 b_val = B_vec[i];
            float4 c_val;
            c_val.x = shared_diag * b_val.x;
            c_val.y = shared_diag * b_val.y;
            c_val.z = shared_diag * b_val.z;
            c_val.w = shared_diag * b_val.w;
            C_vec[i] = c_val;
            
            __syncthreads();
        }
    } else {
        // Scalar version
        for (int base = global_idx; base < N * M; base += gridDim.x * num_threads) {
            const int row = base / M;
            
            // First thread in block loads diagonal value
            if (tid == 0) {
                shared_diag = A[row];
            }
            __syncthreads();
            
            // Process elements_per_thread elements per thread
            #pragma unroll 4
            for (int offset = 0; offset < elements_per_thread && (base + offset) < N * M; offset++) {
                const int idx = base + offset;
                if (idx < N * M) {
                    C[idx] = shared_diag * B[idx];
                }
            }
            
            __syncthreads();
        }
    }
}

at::Tensor forward(at::Tensor A, at::Tensor B) {
    TORCH_CHECK(A.dim() == 1, "A must be a 1D tensor");
    TORCH_CHECK(B.dim() == 2, "B must be a 2D tensor");
    TORCH_CHECK(A.size(0) == B.size(0), "Dimension mismatch");

    A = A.contiguous();
    B = B.contiguous();

    const int64_t N = A.size(0);
    const int64_t M = B.size(1);
    auto C = torch::empty({N, M}, B.options());

    const int threads = 256;
    const int elements_per_thread = 4;
    
    if (M % 4 == 0) {
        // Use vectorized version for aligned data
        const int blocks = min(65535, (int)((N * M + threads * 4 - 1) / (threads * 4)));
        shared_diag_matmul_kernel<true><<<blocks, threads>>>(
            A.data_ptr<float>(),
            B.data_ptr<float>(),
            C.data_ptr<float>(),
            N, M,
            elements_per_thread
        );
    } else {
        // Use scalar version for unaligned data
        const int blocks = min(65535, (int)((N * M + threads * elements_per_thread - 1) / (threads * elements_per_thread)));
        shared_diag_matmul_kernel<false><<<blocks, threads>>>(
            A.data_ptr<float>(),
            B.data_ptr<float>(),
            C.data_ptr<float>(),
            N, M,
            elements_per_thread
        );
    }

    return C;
}

PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
    m.def("forward", &forward, "Shared memory diagonal matrix multiplication");
}
Performance Metrics
Metric Value Unit Variance Samples
Executed Ipc Active 0.932 inst/cycle 0.000 5
Executed Ipc Elapsed 0.854 inst/cycle 0.000 5
Issue Slots Busy 23.376 % 0.015 5
Issued Ipc Active 0.936 inst/cycle 0.000 5
SM Busy 23.376 % 0.015 5
Memory Throughput 2687383159678.094 byte/second 330721879857935548416.000 5
Mem Busy 46.976 % 0.087 5
Max Bandwidth 80.242 % 0.305 5
L1/TEX Hit Rate 0.030 % 0.000 5
L2 Hit Rate 49.996 % 0.023 5
Mem Pipes Busy 21.084 % 0.018 5
Warp Cycles Per Issued Instruction 62.646 cycle 0.572 5
Warp Cycles Per Executed Instruction 62.888 cycle 0.578 5
Avg. Active Threads Per Warp 29.860 0.000 5
Avg. Not Predicated Off Threads Per Warp 28.750 0.000 5
Max Active Clusters 0.000 cluster 0.000 5
Max Cluster Size 8.000 block 0.000 5
Overall GPU Occupancy 0.000 % 0.000 5
Cluster Occupancy 0.000 % 0.000 5
Block Limit SM 32.000 block 0.000 5
Block Limit Registers 10.000 block 0.000 5
Block Limit Shared Mem 28.000 block 0.000 5
Block Limit Warps 8.000 block 0.000 5
Theoretical Active Warps per SM 64.000 warp 0.000 5
Theoretical Occupancy 100.000 % 0.000 5
Achieved Occupancy 91.742 % 0.006 5
Achieved Active Warps Per SM 58.714 warp 0.003 5
Analysis Rules
Rule Description
WRN HighPipeUtilization All compute pipelines are under-utilized. Either this kernel is very small or it doesn't issue enough warps per scheduler. Check the Launch Statistics and Scheduler Statistics sections for further details.
INF CPIStall Check the Warp Stall Sampling (All Cycles) table for the top stall locations in your source based on sampling data. The Kernel Profiling Guide (https://docs.nvidia.com/nsight-compute/ProfilingGuide/index.html#metrics-reference) provides more details on each stall reason.
INF Occupancy This kernel's theoretical occupancy is not impacted by any block limit.
Operation / Metric Value Unit
aten::to
CPU Time 751396.70 μs
Device Time 6766.57 μs
Self CPU Time 55.53 μs
Self Device Time 0.00 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
aten::_to_copy
CPU Time 751341.17 μs
Device Time 6766.57 μs
Self CPU Time 134.96 μs
Self Device Time 0.00 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
aten::empty_strided
CPU Time 744165.16 μs
Device Time 0.00 μs
Self CPU Time 143.77 μs
Self Device Time 0.00 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
cudaDeviceGetStreamPriorityRange
CPU Time 723196.61 μs
Device Time 0.00 μs
Self CPU Time 723196.61 μs
Self Device Time 0.00 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
cudaLaunchKernel
CPU Time 559334.90 μs
Device Time 14337.21 μs
Self CPU Time 559334.90 μs
Self Device Time 14337.21 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
void shared_diag_matmul_kernel<true>(float const*, float const*, float*, long, long, long)
CPU Time 0.00 μs
Device Time 259656.92 μs
Self CPU Time 0.00 μs
Self Device Time 259656.92 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
cudaEventRecord
CPU Time 14883.69 μs
Device Time 28275.67 μs
Self CPU Time 14883.69 μs
Self Device Time 28275.67 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
aten::zero_
CPU Time 229229.61 μs
Device Time 429540.68 μs
Self CPU Time 10800.43 μs
Self Device Time 0.00 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
aten::fill_
CPU Time 218431.31 μs
Device Time 429540.68 μs
Self CPU Time 11291.50 μs
Self Device Time 429540.68 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)
CPU Time 0.00 μs
Device Time 429540.68 μs
Self CPU Time 0.00 μs
Self Device Time 429540.68 μs
CPU Memory Usage 0 B
Device Memory Usage 0 B
Self CPU Memory Usage 0 B
Self Device Memory Usage 0 B
Status: Failed 
45252 warnings and 2 errors generated when compiling for host.
Error while processing /home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu.
Suppressed 45287 warnings (45240 in non-user code, 47 NOLINT).
Use -header-filter=.* to display errors from all non-system headers. Use -system-headers to display errors from system headers as well.
Found compiler error(s).
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:7:5 bugprone-easily-swappable-parameters
7 | const float* __restrict__ A,
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
8 | const float* __restrict__ B,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:7:31: note: the first parameter in the range is 'A'
7 | const float* __restrict__ A,
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:8:31: note: the last parameter in the range is 'B'
8 | const float* __restrict__ B,
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:16:21: warning: narrowing conversion from 'unsigned int' to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]
16 | const int tid = threadIdx.x;
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:17:21: warning: narrowing conversion from 'unsigned int' to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]
17 | const int bid = blockIdx.x;
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:18:29: warning: narrowing conversion from 'unsigned int' to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]
18 | const int num_threads = blockDim.x;
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:25:27: warning: narrowing conversion from 'int64_t' (aka 'long') to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]
25 | const int vec_M = M >> 2; // M/4
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:27:54: warning: narrowing conversion from 'unsigned int' to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]
27 | for (int i = global_idx; i < N * vec_M; i += gridDim.x * num_threads) {
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:48:59: warning: narrowing conversion from 'unsigned int' to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]
48 | for (int base = global_idx; base < N * M; base += gridDim.x * num_threads) {
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:49:29: warning: narrowing conversion from 'int64_t' (aka 'long') to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]
49 | const int row = base / M;
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:88:28: error: no matching function for call to 'min' [clang-diagnostic-error]
88 | const int blocks = min(65535, (int)((N * M + threads * 4 - 1) / (threads * 4)));
| ^~~
/home/common_modules/clang-tidy/20.0.0git/lib/clang/20/include/__clang_cuda_math.h:201:16: note: candidate function not viable: call to __device__ function from __host__ function
201 | __DEVICE__ int min(int __a, int __b) { return __nv_min(__a, __b); }
| ^
/usr/local/cuda/include/crt/math_functions.hpp:868:38: note: candidate function not viable: call to __device__ function from __host__ function
868 | __MATH_FUNCTIONS_DECL__ unsigned int min(const unsigned int a, const unsigned int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:873:38: note: candidate function not viable: call to __device__ function from __host__ function
873 | __MATH_FUNCTIONS_DECL__ unsigned int min(const int a, const unsigned int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:878:38: note: candidate function not viable: call to __device__ function from __host__ function
878 | __MATH_FUNCTIONS_DECL__ unsigned int min(const unsigned int a, const int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:883:34: note: candidate function not viable: call to __device__ function from __host__ function
883 | __MATH_FUNCTIONS_DECL__ long int min(const long int a, const long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:902:43: note: candidate function not viable: call to __device__ function from __host__ function
902 | __MATH_FUNCTIONS_DECL__ unsigned long int min(const unsigned long int a, const unsigned long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:919:43: note: candidate function not viable: call to __device__ function from __host__ function
919 | __MATH_FUNCTIONS_DECL__ unsigned long int min(const long int a, const unsigned long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:936:43: note: candidate function not viable: call to __device__ function from __host__ function
936 | __MATH_FUNCTIONS_DECL__ unsigned long int min(const unsigned long int a, const long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:953:39: note: candidate function not viable: call to __device__ function from __host__ function
953 | __MATH_FUNCTIONS_DECL__ long long int min(const long long int a, const long long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:958:48: note: candidate function not viable: call to __device__ function from __host__ function
958 | __MATH_FUNCTIONS_DECL__ unsigned long long int min(const unsigned long long int a, const unsigned long long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:963:48: note: candidate function not viable: call to __device__ function from __host__ function
963 | __MATH_FUNCTIONS_DECL__ unsigned long long int min(const long long int a, const unsigned long long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:968:48: note: candidate function not viable: call to __device__ function from __host__ function
968 | __MATH_FUNCTIONS_DECL__ unsigned long long int min(const unsigned long long int a, const long long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:973:31: note: candidate function not viable: call to __device__ function from __host__ function
973 | __MATH_FUNCTIONS_DECL__ float min(const float a, const float b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:978:32: note: candidate function not viable: call to __device__ function from __host__ function
978 | __MATH_FUNCTIONS_DECL__ double min(const double a, const double b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:983:32: note: candidate function not viable: call to __device__ function from __host__ function
983 | __MATH_FUNCTIONS_DECL__ double min(const float a, const double b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:988:32: note: candidate function not viable: call to __device__ function from __host__ function
988 | __MATH_FUNCTIONS_DECL__ double min(const double a, const float b)
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:88:54: warning: performing an implicit widening conversion to type 'int64_t' (aka 'long') of a multiplication performed in type 'int' [bugprone-implicit-widening-of-multiplication-result]
88 | const int blocks = min(65535, (int)((N * M + threads * 4 - 1) / (threads * 4)));
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:88:54: note: make conversion explicit to silence this warning
88 | const int blocks = min(65535, (int)((N * M + threads * 4 - 1) / (threads * 4)));
| ^~~~~~~~~~~
| static_cast<int64_t>( )
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:88:54: note: perform multiplication in a wider type
88 | const int blocks = min(65535, (int)((N * M + threads * 4 - 1) / (threads * 4)));
| ^~~~~~~
| static_cast<int64_t>( )
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:88:74: warning: performing an implicit widening conversion to type 'int64_t' (aka 'long') of a multiplication performed in type 'int' [bugprone-implicit-widening-of-multiplication-result]
88 | const int blocks = min(65535, (int)((N * M + threads * 4 - 1) / (threads * 4)));
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:88:74: note: make conversion explicit to silence this warning
4 | const int blocks = min(65535, (int)((N * M + threads * 4 - 1) / (threads * 4)));
| ^~~~~~~~~~~
| static_cast<int64_t>( )
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:88:74: note: perform multiplication in a wider type
88 | const int blocks = min(65535, (int)((N * M + threads * 4 - 1) / (threads * 4)));
| ^~~~~~~
| static_cast<int64_t>( )
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:98:28: error: no matching function for call to 'min' [clang-diagnostic-error]
98 | const int blocks = min(65535, (int)((N * M + threads * elements_per_thread - 1) / (threads * elements_per_thread)));
| ^~~
/home/common_modules/clang-tidy/20.0.0git/lib/clang/20/include/__clang_cuda_math.h:201:16: note: candidate function not viable: call to __device__ function from __host__ function
201 | __DEVICE__ int min(int __a, int __b) { return __nv_min(__a, __b); }
| ^
/usr/local/cuda/include/crt/math_functions.hpp:868:38: note: candidate function not viable: call to __device__ function from __host__ function
868 | __MATH_FUNCTIONS_DECL__ unsigned int min(const unsigned int a, const unsigned int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:873:38: note: candidate function not viable: call to __device__ function from __host__ function
873 | __MATH_FUNCTIONS_DECL__ unsigned int min(const int a, const unsigned int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:878:38: note: candidate function not viable: call to __device__ function from __host__ function
878 | __MATH_FUNCTIONS_DECL__ unsigned int min(const unsigned int a, const int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:883:34: note: candidate function not viable: call to __device__ function from __host__ function
883 | __MATH_FUNCTIONS_DECL__ long int min(const long int a, const long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:902:43: note: candidate function not viable: call to __device__ function from __host__ function
902 | __MATH_FUNCTIONS_DECL__ unsigned long int min(const unsigned long int a, const unsigned long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:919:43: note: candidate function not viable: call to __device__ function from __host__ function
919 | __MATH_FUNCTIONS_DECL__ unsigned long int min(const long int a, const unsigned long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:936:43: note: candidate function not viable: call to __device__ function from __host__ function
936 | __MATH_FUNCTIONS_DECL__ unsigned long int min(const unsigned long int a, const long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:953:39: note: candidate function not viable: call to __device__ function from __host__ function
953 | __MATH_FUNCTIONS_DECL__ long long int min(const long long int a, const long long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:958:48: note: candidate function not viable: call to __device__ function from __host__ function
958 | __MATH_FUNCTIONS_DECL__ unsigned long long int min(const unsigned long long int a, const unsigned long long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:963:48: note: candidate function not viable: call to __device__ function from __host__ function
963 | __MATH_FUNCTIONS_DECL__ unsigned long long int min(const long long int a, const unsigned long long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:968:48: note: candidate function not viable: call to __device__ function from __host__ function
968 | __MATH_FUNCTIONS_DECL__ unsigned long long int min(const unsigned long long int a, const long long int b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:973:31: note: candidate function not viable: call to __device__ function from __host__ function
973 | __MATH_FUNCTIONS_DECL__ float min(const float a, const float b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:978:32: note: candidate function not viable: call to __device__ function from __host__ function
978 | __MATH_FUNCTIONS_DECL__ double min(const double a, const double b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:983:32: note: candidate function not viable: call to __device__ function from __host__ function
983 | __MATH_FUNCTIONS_DECL__ double min(const float a, const double b)
| ^
/usr/local/cuda/include/crt/math_functions.hpp:988:32: note: candidate function not viable: call to __device__ function from __host__ function
988 | __MATH_FUNCTIONS_DECL__ double min(const double a, const float b)
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:98:54: warning: performing an implicit widening conversion to type 'int64_t' (aka 'long') of a multiplication performed in type 'int' [bugprone-implicit-widening-of-multiplication-result]
98 | const int blocks = min(65535, (int)((N * M + threads * elements_per_thread - 1) / (threads * elements_per_thread)));
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:98:54: note: make conversion explicit to silence this warning
98 | const int blocks = min(65535, (int)((N * M + threads * elements_per_thread - 1) / (threads * elements_per_thread)));
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
| static_cast<int64_t>( )
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:98:54: note: perform multiplication in a wider type
98 | const int blocks = min(65535, (int)((N * M + threads * elements_per_thread - 1) / (threads * elements_per_thread)));
| ^~~~~~~
| static_cast<int64_t>( )
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:98:92: warning: performing an implicit widening conversion to type 'int64_t' (aka 'long') of a multiplication performed in type 'int' [bugprone-implicit-widening-of-multiplication-result]
98 | const int blocks = min(65535, (int)((N * M + threads * elements_per_thread - 1) / (threads * elements_per_thread)));
| ^
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:98:92: note: make conversion explicit to silence this warning
98 | const int blocks = min(65535, (int)((N * M + threads * elements_per_thread - 1) / (threads * elements_per_thread)));
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
| static_cast<int64_t>( )
/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_12/b7_s2_shared_mem_diag_matmul_base/base/base.cu:98:92: note: perform multiplication in a wider type
98 | const int blocks = min(65535, (int)((N * M + threads * elements_per_thread - 1) / (threads * elements_per_thread)));
| ^~~~~~~
| static_cast<int64_t>( )