Kernel Details - 52_argmin_optimized_memory

import torch
import torch.nn as nn
import torch.nn.functional as F


def module_fn(x: torch.Tensor, dim: int) -> torch.Tensor:
    """
    Finds the index of the minimum value along the specified dimension.

    Args:
        x (torch.Tensor): Input tensor.
        dim (int): Dimension along which to find the minimum value.

    Returns:
        torch.Tensor: Tensor containing the indices of the minimum values along the specified dimension.
    """
    return torch.argmin(x, dim)


class Model(nn.Module):
    """
    Simple model that finds the index of the minimum value along a specified dimension.
    """

    def __init__(self, dim):
        """
        Initializes the model with the dimension to perform argmin on.

        Args:
            dim (int): Dimension along which to find the minimum value.
        """
        super(Model, self).__init__()
        self.dim = dim

    def forward(self, x, fn=module_fn):
        """
        Finds the index of the minimum value along the specified dimension.

        Args:
            x (torch.Tensor): Input tensor.
            fn (callable): Function to compute the output. Defaults to module_fn.

        Returns:
            torch.Tensor: Tensor containing the indices of the minimum values along the specified dimension.
        """
        return fn(x, self.dim)


batch_size = 16
dim1 = 256
dim2 = 256
dim = 1


def get_inputs():
    x = torch.randn(batch_size, dim1, dim2)
    return [x]


def get_init_inputs():
    return [dim]

import torch
import torch.nn as nn

class Model(nn.Module):
    """
    Simple model that finds the index of the minimum value along a specified dimension.
    """
    def __init__(self, dim: int):
        """
        Initializes the model with the dimension to perform argmin on.

        Args:
            dim (int): Dimension along which to find the minimum value.
        """
        super(Model, self).__init__()
        self.dim = dim

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        """
        Finds the index of the minimum value along the specified dimension.

        Args:
            x (torch.Tensor): Input tensor.

        Returns:
            torch.Tensor: Tensor containing the indices of the minimum values along the specified dimension.
        """
        return torch.argmin(x, dim=self.dim)

batch_size = 16
dim1 = 256
dim2 = 256
dim = 1

def get_inputs():
    x = torch.randn(batch_size, dim1, dim2)
    return [x]

def get_init_inputs():
    return [dim]

Download Evaluation Download PyTorch Download CUDA Download Profiles

Kernel Information

Operation Name	52_Argmin_over_a_dimension
Level ID	1
Task ID	52
Kernel Name	52_argmin_optimized_memory_base
CUDA Speedup (Native)	1.612x
CUDA Speedup (Compile)	2.238x
CUDA Runtime	0.015 ms
PyTorch Runtime (Native)	0.024 ms
PyTorch Runtime (Compile)	0.034 ms
Correct	True
Max Diff (vs. Reference)	0.000000
Model	azure-gpt-4o-2024-08-06
Temperature	0.50

View Experiment Progress Details

Related Kernels (Level 1, Task 52 • 52_Argmin_over_a_dimension)

Rank	Kernel Name	Runtime (ms)	Speedup Native	Speedup Compile
🥇	52_argmin_tuned_blocks_base_base	0.01	1.73	2.40
🥇	argmin_parallel_tuned_2_edit_1	0.01	1.73	2.40
🥉	52_argmin_optimized_memory_base	0.01	1.61	2.24
🥉	52_argmin_optimal_blks_base	0.01	1.61	2.24
🥉	52_argmin_shared_tiled_base_base	0.01	1.61	2.24
🥉	52_argmin_ldg_aligned_base	0.01	1.61	2.24
7	52_argmin_balanced_workload_base	0.02	1.51	2.10
7	52_argmin_optimized_indexing_base_base	0.02	1.51	2.10
7	52_argmin_stride_loops_base	0.02	1.51	2.10
7	argmin_combined_kernel_base	0.02	1.51	2.10
7	optimized_argmin_kernel_base	0.02	1.51	2.10
7	argmin_parallel_edit_1	0.02	1.51	2.10
7	52_argmin_coalesced_base	0.02	1.51	2.10
14	52_argmin_coalesced_base_base	0.02	1.10	1.53
14	argmin_coalesced_edit_1	0.02	1.10	1.53
14	coalesced_argmin_base	0.02	1.10	1.53
14	coalesced_argmin_edit_1	0.02	1.10	1.53
14	aligned_memory_argmin_base	0.02	1.10	1.53
14	modular_argmin_optimized_indexing_base	0.02	1.10	1.53
14	modular_argmin_refactored_base	0.02	1.10	1.53

#include <torch/extension.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <vector>
#include <stdexcept>

// Optimized CUDA kernel using __ldg() for read-only global memory accesses
// and aligning memory accesses to 128-bit boundaries for improved throughput.

template <typename scalar_t>
__global__ void argmin_optimized_memory_kernel(
    const scalar_t* __restrict__ x,
    int64_t* __restrict__ output,
    int K,
    int64_t outer_size,
    int64_t inner_size) {
    
    const int tid = threadIdx.x;
    const int bid = blockIdx.x;
    const int block_size = blockDim.x;
    
    // Shared memory for partial results
    __shared__ scalar_t s_min_vals[256];
    __shared__ int s_min_indices[256];
    
    // Calculate which slice this block is processing
    int64_t slice_idx = bid;
    if (slice_idx >= outer_size * inner_size) return;
    
    int64_t outer = slice_idx / inner_size;
    int64_t inner = slice_idx % inner_size;
    
    // Initialize with the first value each thread can access
    scalar_t local_min = FLT_MAX;
    int local_min_idx = 0;
    
    // Each thread processes elements strided by block_size
    for (int k = tid; k < K; k += block_size) {
        scalar_t val = __ldg(&x[outer * (K * inner_size) + k * inner_size + inner]);
        if (val < local_min) {
            local_min = val;
            local_min_idx = k;
        }
    }
    
    // Store in shared memory
    s_min_vals[tid] = local_min;
    s_min_indices[tid] = local_min_idx;
    __syncthreads();
    
    // Reduce within the block
    for (int stride = block_size/2; stride > 0; stride >>= 1) {
        if (tid < stride) {
            if (s_min_vals[tid + stride] < s_min_vals[tid]) {
                s_min_vals[tid] = s_min_vals[tid + stride];
                s_min_indices[tid] = s_min_indices[tid + stride];
            }
        }
        __syncthreads();
    }
    
    // Write result
    if (tid == 0) {
        output[slice_idx] = s_min_indices[0];
    }
}

at::Tensor argmin_cuda_forward(const at::Tensor &x, int64_t dim) {
    TORCH_CHECK(x.is_cuda(), "Input tensor must be a CUDA tensor");
    
    int dims = x.dim();
    if (dim < 0) dim += dims;
    TORCH_CHECK(dim >= 0 && dim < dims, "Reduction dim out of range");
    
    int64_t outer_size = 1;
    for (int i = 0; i < dim; i++) {
        outer_size *= x.size(i);
    }
    int K = static_cast<int>(x.size(dim));
    int64_t inner_size = 1;
    for (int i = dim + 1; i < dims; i++) {
        inner_size *= x.size(i);
    }
    
    std::vector<int64_t> out_sizes;
    for (int i = 0; i < dims; i++) {
        if (i == dim) continue;
        out_sizes.push_back(x.size(i));
    }
    auto output = at::empty(out_sizes, x.options().dtype(at::kLong));
    
    int threads = 256;
    int blocks = outer_size * inner_size;
    
    AT_DISPATCH_ALL_TYPES_AND(at::ScalarType::Half, x.scalar_type(), "argmin_cuda_forward", ([&] {
        const scalar_t* x_data = x.data_ptr<scalar_t>();
        int64_t* output_data = output.data_ptr<int64_t>();
        argmin_optimized_memory_kernel<scalar_t><<<blocks, threads>>>(
            x_data, output_data, K, outer_size, inner_size);
    }));
    
    cudaError_t err = cudaGetLastError();
    if (err != cudaSuccess) {
        throw std::runtime_error(std::string("CUDA kernel failed: ") + cudaGetErrorString(err));
    }
    return output;
}

PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
    m.def("forward", &argmin_cuda_forward, "Argmin forward (CUDA)");
}

Performance Metrics

Metric	Value	Unit	Variance	Samples
Executed Ipc Active	2.006	inst/cycle	0.000	5
Executed Ipc Elapsed	1.678	inst/cycle	0.000	5
Issue Slots Busy	50.598	%	0.044	5
Issued Ipc Active	2.024	inst/cycle	0.000	5
SM Busy	50.598	%	0.044	5
Memory Throughput	283490701719.294	byte/second	4027190867731682816.000	5
Mem Busy	52.280	%	0.265	5
Max Bandwidth	32.208	%	0.162	5
L1/TEX Hit Rate	0.166	%	0.004	5
L2 Hit Rate	87.056	%	0.122	5
Mem Pipes Busy	28.302	%	0.042	5
Warp Cycles Per Issued Instruction	27.260	cycle	0.005	5
Warp Cycles Per Executed Instruction	27.484	cycle	0.005	5
Avg. Active Threads Per Warp	30.610		0.000	5
Avg. Not Predicated Off Threads Per Warp	28.170		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	21.000	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	85.858	%	0.005	5
Achieved Active Warps Per SM	54.948	warp	0.002	5

Analysis Rules

Rule	Description
INF HighPipeUtilization	ALU is the highest-utilized pipeline (34.2%) based on active cycles, taking into account the rates of its different instructions. It executes integer and logic operations. It is well-utilized, but should not be a bottleneck.
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.
WRN Occupancy	This kernel's theoretical occupancy is not impacted by any block limit. The difference between calculated theoretical (100.0%) and measured achieved occupancy (85.8%) can be the result of warp scheduling overheads or workload imbalances during the kernel execution. Load imbalances can occur between warps within a block as well as across blocks of the same kernel. See the CUDA Best Practices Guide (https://docs.nvidia.com/cuda/cuda-c-best-practices-guide/index.html#occupancy) for more details on optimizing occupancy.

Operation / Metric	Value	Unit
aten::to
CPU Time	3768780.99	μs
Device Time	393.38	μs
Self CPU Time	41.76	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	3768739.23	μs
Device Time	393.38	μs
Self CPU Time	104.72	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	3768004.34	μs
Device Time	0.00	μs
Self CPU Time	102.86	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	3767675.98	μs
Device Time	0.00	μs
Self CPU Time	3767675.98	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	551283.08	μs
Device Time	60455.03	μs
Self CPU Time	551283.08	μs
Self Device Time	60455.03	μs
CPU Memory Usage	0	B
Device Memory Usage	0	B
Self CPU Memory Usage	0	B
Self Device Memory Usage	0	B
void argmin_optimized_memory_kernel<float>(float const, long, int, long, long)
CPU Time	0.00	μs
Device Time	103512.88	μs
Self CPU Time	0.00	μs
Self Device Time	103512.88	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	75163.87	μs
Device Time	618607.79	μs
Self CPU Time	13363.15	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	61802.97	μs
Device Time	618607.79	μs
Self CPU Time	15864.68	μs
Self Device Time	618607.79	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	618607.79	μs
Self CPU Time	0.00	μs
Self Device Time	618607.79	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

45261 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_52/b2_s3_52_argmin_optimized_memory/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_52/b2_s3_52_argmin_optimized_memory/base/base.cu:14:5 bugprone-easily-swappable-parameters

14 | int K,

| ^~~~~~

15 | int64_t outer_size,

| ~~~~~~~~~~~~~~~~~~

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:14:9: note: the first parameter in the range is 'K'

14 | int K,

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:15:13: note: the last parameter in the range is 'outer_size'

15 | int64_t outer_size,

| ^~~~~~~~~~

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:14:5: note:

14 | int K,

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:15:5: note: 'int' and 'int64_t' may be implicitly converted: 'int' -> 'int64_t' (as 'long'), 'int64_t' (as 'long') -> 'int'

15 | int64_t outer_size,

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:18:21: warning: narrowing conversion from 'unsigned int' to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]

18 | const int tid = threadIdx.x;

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:19:21: warning: narrowing conversion from 'unsigned int' to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]

19 | const int bid = blockIdx.x;

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:20:28: warning: narrowing conversion from 'unsigned int' to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]

20 | const int block_size = blockDim.x;

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:34:26: warning: implicit conversion of out of range value from 'float' to 'int' is undefined [clang-diagnostic-literal-conversion]

34 | scalar_t local_min = FLT_MAX;

| ~~~~~~~~~ ^

/home/common_modules/clang-tidy/20.0.0git/lib/clang/20/include/float.h:143:17: note: expanded from macro 'FLT_MAX'

143 | #define FLT_MAX __FLT_MAX__

| ^~~~~~~~~~~

note: expanded from macro '__FLT_MAX__'

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:98:9: note: in instantiation of function template specialization 'argmin_optimized_memory_kernel<int>' requested here

98 | argmin_optimized_memory_kernel<scalar_t><<<blocks, threads>>>(

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:34:26: warning: implicit conversion of out of range value from 'float' to 'long' is undefined [clang-diagnostic-literal-conversion]

34 | scalar_t local_min = FLT_MAX;

| ~~~~~~~~~ ^

/home/common_modules/clang-tidy/20.0.0git/lib/clang/20/include/float.h:143:17: note: expanded from macro 'FLT_MAX'

143 | #define FLT_MAX __FLT_MAX__

| ^~~~~~~~~~~

note: expanded from macro '__FLT_MAX__'

98 | argmin_optimized_memory_kernel<scalar_t><<<blocks, threads>>>(

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:34:26: warning: implicit conversion of out of range value from 'float' to 'short' is undefined [clang-diagnostic-literal-conversion]

34 | scalar_t local_min = FLT_MAX;

| ~~~~~~~~~ ^

/home/common_modules/clang-tidy/20.0.0git/lib/clang/20/include/float.h:143:17: note: expanded from macro 'FLT_MAX'

143 | #define FLT_MAX __FLT_MAX__

| ^~~~~~~~~~~

note: expanded from macro '__FLT_MAX__'

98 | argmin_optimized_memory_kernel<scalar_t><<<blocks, threads>>>(

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:34:26: warning: implicit conversion of out of range value from 'float' to 'signed char' is undefined [clang-diagnostic-literal-conversion]

34 | scalar_t local_min = FLT_MAX;

| ~~~~~~~~~ ^

/home/common_modules/clang-tidy/20.0.0git/lib/clang/20/include/float.h:143:17: note: expanded from macro 'FLT_MAX'

143 | #define FLT_MAX __FLT_MAX__

| ^~~~~~~~~~~

note: expanded from macro '__FLT_MAX__'

98 | argmin_optimized_memory_kernel<scalar_t><<<blocks, threads>>>(

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:34:26: warning: implicit conversion of out of range value from 'float' to 'unsigned char' is undefined [clang-diagnostic-literal-conversion]

34 | scalar_t local_min = FLT_MAX;

| ~~~~~~~~~ ^

/home/common_modules/clang-tidy/20.0.0git/lib/clang/20/include/float.h:143:17: note: expanded from macro 'FLT_MAX'

143 | #define FLT_MAX __FLT_MAX__

| ^~~~~~~~~~~

note: expanded from macro '__FLT_MAX__'

98 | argmin_optimized_memory_kernel<scalar_t><<<blocks, threads>>>(

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: error: use of overloaded operator '<' is ambiguous (with operand types 'c10::Half' and 'c10::Half') [clang-diagnostic-error]

40 | if (val < local_min) {

| ~~~ ^ ~~~~~~~~~

98 | argmin_optimized_memory_kernel<scalar_t><<<blocks, threads>>>(

| ^

/usr/local/cuda/include/cuda_fp16.hpp:310:33: note: candidate function

310 | __device__ __forceinline__ bool operator< (const __half &lh, const __half &rh) { return __hlt(lh, rh); }

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(float, float)

40 | if (val < local_min) {

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(float, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(float, long double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(float, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(float, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(float, long long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(float, __int128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(double, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(double, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(double, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(double, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(double, __int128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(int, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long long, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(__int128, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(int, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(__int128, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long double, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(__float128, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(__float128, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(int, long double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(int, __float128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(int, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(int, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(int, long long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(int, __int128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long, __float128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long, long long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long, __int128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long long, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(long long, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(__int128, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:40:17: note: built-in candidate operator<(__int128, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: error: use of overloaded operator '<' is ambiguous (with operand types 'c10::Half' and 'c10::Half') [clang-diagnostic-error]

54 | if (s_min_vals[tid + stride] < s_min_vals[tid]) {

| ~~~~~~~~~~~~~~~~~~~~~~~~ ^ ~~~~~~~~~~~~~~~

/usr/local/cuda/include/cuda_fp16.hpp:310:33: note: candidate function

310 | __device__ __forceinline__ bool operator< (const __half &lh, const __half &rh) { return __hlt(lh, rh); }

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(float, float)

54 | if (s_min_vals[tid + stride] < s_min_vals[tid]) {

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(float, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(float, long double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(float, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(float, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(float, long long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(float, __int128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(double, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(double, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(double, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(double, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(double, __int128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(int, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long long, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(__int128, float)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(int, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(__int128, double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long double, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(__float128, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(__float128, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(int, long double)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(int, __float128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(int, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(int, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(int, long long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(int, __int128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long, __float128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long, long long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long, __int128)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long long, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(long long, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(__int128, int)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:54:42: note: built-in candidate operator<(__int128, long)

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:71:16: warning: narrowing conversion from 'int64_t' (aka 'long') to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]

71 | int dims = x.dim();

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:81:18: warning: narrowing conversion from 'int64_t' (aka 'long') to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]

81 | for (int i = dim + 1; i < dims; i++) {

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:93:18: warning: narrowing conversion from 'int64_t' (aka 'long') to signed type 'int' is implementation-defined [bugprone-narrowing-conversions]

93 | int blocks = outer_size * inner_size;

| ^

/home/robert_sakana_ai/llm_cuda/experiments/20250202_optimize_b10_s4_e0_sweep/level_1/task_52/b2_s3_52_argmin_optimized_memory/base/base.cu:95:5: warning: inside a lambda, '__func__' expands to the name of the function call operator; consider capturing the name of the enclosing function explicitly [bugprone-lambda-function-name]

95 | AT_DISPATCH_ALL_TYPES_AND(at::ScalarType::Half, x.scalar_type(), "argmin_cuda_forward", ([&] {

| ^

/home/robert_sakana_ai/miniconda3/envs/llm2cuda/lib/python3.11/site-packages/torch/include/ATen/Dispatch.h:542:19: note: expanded from macro 'AT_DISPATCH_ALL_TYPES_AND'

542 | TYPE, NAME, AT_DISPATCH_CASE_ALL_TYPES_AND(SCALARTYPE, __VA_ARGS__))

| ^

/home/robert_sakana_ai/miniconda3/envs/llm2cuda/lib/python3.11/site-packages/torch/include/ATen/Dispatch.h:537:3: note: expanded from macro 'AT_DISPATCH_CASE_ALL_TYPES_AND'

537 | AT_DISPATCH_CASE_ALL_TYPES(__VA_ARGS__) \

| ^

/home/robert_sakana_ai/miniconda3/envs/llm2cuda/lib/python3.11/site-packages/torch/include/ATen/Dispatch.h:478:3: note: expanded from macro 'AT_DISPATCH_CASE_ALL_TYPES'

478 | AT_DISPATCH_CASE_INTEGRAL_TYPES(__VA_ARGS__) \

| ^

note: (skipping 3 expansions in backtrace; use -fmacro-backtrace-limit=0 to see all)

/home/robert_sakana_ai/miniconda3/envs/llm2cuda/lib/python3.11/site-packages/torch/include/ATen/Dispatch.h:58:7: note: expanded from macro 'AT_PRIVATE_CHECK_SELECTIVE_BUILD'

58 | AT_ERROR( \

| ^

/home/robert_sakana_ai/miniconda3/envs/llm2cuda/lib/python3.11/site-packages/torch/include/c10/util/Exception.h:711:32: note: expanded from macro 'AT_ERROR'

711 | C10_EXPAND_MSVC_WORKAROUND(TORCH_CHECK(false, ::c10::str(__VA_ARGS__))); \

| ^

/home/robert_sakana_ai/miniconda3/envs/llm2cuda/lib/python3.11/site-packages/torch/include/c10/util/Exception.h:536:9: note: expanded from macro 'TORCH_CHECK'

536 | __func__, \

| ^

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`52_Argmin_over_a_dimension` • `52_argmin_optimized_memory_base`

Kernel Information

Related Kernels (Level 1, Task 52 • 52_Argmin_over_a_dimension)

The AI CUDA Engineer 👷

52_Argmin_over_a_dimension • 52_argmin_optimized_memory_base

Kernel Information

Related Kernels (Level 1, Task 52 • 52_Argmin_over_a_dimension)

`52_Argmin_over_a_dimension` • `52_argmin_optimized_memory_base`