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[NVIDIA] CUDA 13 Support #1735

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0fe5c1d
Update CMakeLists.txt
johnnynunez Aug 23, 2025
6f93e19
Update CMakeLists.txt
johnnynunez Aug 23, 2025
9e31022
Update CMakeLists.txt
johnnynunez Aug 23, 2025
44caa8f
Update CMakeLists.txt
johnnynunez Aug 23, 2025
b5517e1
Update CMakeLists.txt
johnnynunez Aug 23, 2025
7a732d8
Update CMakeLists.txt
johnnynunez Aug 23, 2025
b3221c6
Update pythonInterface.cpp
johnnynunez Aug 23, 2025
3e9dedb
Update CMakeLists.txt
johnnynunez Aug 23, 2025
12a0d43
Update CMakeLists.txt
johnnynunez Aug 23, 2025
02188cc
Update CMakeLists.txt
johnnynunez Aug 23, 2025
c6f7d27
Update CMakeLists.txt
johnnynunez Aug 23, 2025
51885c9
Replace cub::Max() with cuda::maximum<> in kernel reductions
johnnynunez Aug 23, 2025
6dc9b51
Replace cub::Max() with cuda::maximum<> in kernel reductions
johnnynunez Aug 23, 2025
1c7f0e8
Replace cub::Max() with cuda::maximum<> in kernel reductions
johnnynunez Aug 23, 2025
528299d
Replace cub::Max() with cuda::maximum<> in kernel reductions
johnnynunez Aug 23, 2025
555c6df
Replace cub::Max() with cuda::maximum<> in kernel reductions
johnnynunez Aug 23, 2025
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9 changes: 7 additions & 2 deletions CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -115,8 +115,13 @@ if(BUILD_CUDA)
message(STATUS "CMake < 3.23.0; determining CUDA architectures supported...")

# 11.4+ supports these at a minimum.
set(CMAKE_CUDA_ARCHITECTURES_ALL 50 52 53 60 61 62 70 72 75 80 86 87)
set(CMAKE_CUDA_ARCHITECTURES_ALL_MAJOR 50 60 70 80)
if (CMAKE_CUDA_COMPILER_VERSION VERSION_LESS "13.0")
set(CMAKE_CUDA_ARCHITECTURES_ALL 50 52 53 60 61 62 70 72 75 80 86 87)
set(CMAKE_CUDA_ARCHITECTURES_ALL_MAJOR 50 60 70 80)
else()
set(CMAKE_CUDA_ARCHITECTURES_ALL 75 80 86 87)
set(CMAKE_CUDA_ARCHITECTURES_ALL_MAJOR 70 80)
endif()

# CUDA 11.8 adds support for Ada and Hopper.
if (CMAKE_CUDA_COMPILER_VERSION VERSION_GREATER_EQUAL "11.8")
Expand Down
25 changes: 13 additions & 12 deletions csrc/kernels.cu
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Expand Up @@ -11,6 +11,7 @@
#include <cub/block/block_reduce.cuh>
#include <cub/block/block_store.cuh>
#include <cub/cub.cuh>
#include <cuda/std/functional>
#include <cub/warp/warp_reduce.cuh>
#include <cuda_fp16.h>
#include <math_constants.h>
Expand Down Expand Up @@ -416,7 +417,7 @@ __global__ void kQuantizeBlockwise(
for (int j = 0; j < NUM_PER_TH; j++)
local_abs_max = fmaxf(local_abs_max, fabsf((float)vals[j]));

local_abs_max = BlockReduce(reduce).Reduce(local_abs_max, cub::Max(), valid_items);
local_abs_max = BlockReduce(reduce).Reduce(local_abs_max, cuda::maximum<>{}, valid_items);

if (threadIdx.x == 0) {
smem_absmax_value[0] = 1.0f / local_abs_max;
Expand Down Expand Up @@ -1002,12 +1003,12 @@ __global__ void __launch_bounds__(NUM_THREADS, 2) kPreconditionOptimizerStatic8b
}

__syncthreads();
local_max_s1 = BlockReduce(temp_storage.reduce).Reduce(local_max_s1, cub::Max(), valid_items);
local_max_s1 = BlockReduce(temp_storage.reduce).Reduce(local_max_s1, cuda::maximum<>{}, valid_items);
__syncthreads();
local_max_s2 = BlockReduce(temp_storage.reduce).Reduce(local_max_s2, cub::Max(), valid_items);
local_max_s2 = BlockReduce(temp_storage.reduce).Reduce(local_max_s2, cuda::maximum<>{}, valid_items);
if (unorm != NULL) {
__syncthreads();
local_unorm = BlockReduce(temp_storage.reduce).Reduce(local_unorm, cub::Sum(), valid_items);
local_unorm = BlockReduce(temp_storage.reduce).Reduce(local_unorm, cuda::std::plus<>{}, valid_items);
}

if (threadIdx.x == 0) {
Expand Down Expand Up @@ -1213,13 +1214,13 @@ __global__ void __launch_bounds__(NUM_THREADS, 2) kPreconditionOptimizerStatic8b
}

__syncthreads();
local_max_s1 = BlockReduce(temp_storage.reduce).Reduce(local_max_s1, cub::Max(), valid_items);
local_max_s1 = BlockReduce(temp_storage.reduce).Reduce(local_max_s1, cuda::maximum<>{}, valid_items);
if (threadIdx.x == 0) {
atomicMax(&new_max1[0], local_max_s1);
}
if (unorm != NULL) {
__syncthreads();
local_unorm = BlockReduce(temp_storage.reduce).Reduce(local_unorm, cub::Sum(), valid_items);
local_unorm = BlockReduce(temp_storage.reduce).Reduce(local_unorm, cuda::std::plus<>{}, valid_items);
if (threadIdx.x == 0) {
atomicAdd(&unorm[0], local_unorm);
}
Expand Down Expand Up @@ -1524,11 +1525,11 @@ __launch_bounds__(256, 3) __global__ void kOptimizerStatic8bit2StateBlockwise(
}

// reduce: 2.51/1.60 -> 2.67/1.69
new_local_abs_max1 = BlockReduce1(reduce1).Reduce(new_local_abs_max1, cub::Max());
new_local_abs_max2 = BlockReduce2(reduce2).Reduce(new_local_abs_max2, cub::Max());
new_local_abs_max1 = BlockReduce1(reduce1).Reduce(new_local_abs_max1, cuda::maximum<>{});
new_local_abs_max2 = BlockReduce2(reduce2).Reduce(new_local_abs_max2, cuda::maximum<>{});

if (OPTIMIZER == ADEMAMIX) {
new_local_abs_max3 = BlockReduce3(reduce3).Reduce(new_local_abs_max3, cub::Max());
new_local_abs_max3 = BlockReduce3(reduce3).Reduce(new_local_abs_max3, cuda::maximum<>{});
}

if (threadIdx.x == 0) {
Expand Down Expand Up @@ -1737,7 +1738,7 @@ __launch_bounds__(256, 3) __global__ void kOptimizerStatic8bit1StateBlockwise(
}

// reduce: 2.51/1.60 -> 2.67/1.69
new_local_abs_max1 = BlockReduce1(reduce1).Reduce(new_local_abs_max1, cub::Max());
new_local_abs_max1 = BlockReduce1(reduce1).Reduce(new_local_abs_max1, cuda::maximum<>{});

if (threadIdx.x == 0)
smem_exchange1[0] = new_local_abs_max1;
Expand Down Expand Up @@ -1843,7 +1844,7 @@ __launch_bounds__(1024, BNB_MAX_THREADS_PER_SM / 1024) __global__
}

// Reduce thread-local absmax across the block.
const TReduction row_absmax = BlockReduceT(temp_storage).Reduce(row_local_absmax, cub::Max(), cols);
const TReduction row_absmax = BlockReduceT(temp_storage).Reduce(row_local_absmax, cuda::maximum<>{}, cols);
if (threadIdx.x == 0) {
// Save our block's absmax to shared memory for the quantization step.
rowStats[row_id] = smem_row_absmax = row_absmax;
Expand Down Expand Up @@ -1898,7 +1899,7 @@ __launch_bounds__(1024, BNB_MAX_THREADS_PER_SM / 1024) __global__

// Reduce thread-local absmax across the block.
// TODO: Consider algorithm BLOCK_REDUCE_RAKING_COMMUTATIVE_ONLY
const float row_absmax = BlockReduceT(temp_storage).Reduce(row_local_absmax, cub::Max(), cols);
const float row_absmax = BlockReduceT(temp_storage).Reduce(row_local_absmax, cuda::maximum<>{}, cols);
if (threadIdx.x == 0) {
// Save our block's absmax to shared memory for the quantization step.
rowStats[row_id] = row_absmax;
Expand Down
23 changes: 22 additions & 1 deletion csrc/pythonInterface.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,27 @@

#if BUILD_CUDA
#include <ops.cuh>
#include <cuda_runtime_api.h>

#if CUDART_VERSION >= 13000
static inline cudaError_t bnb_cudaMemPrefetchAsync(const void* ptr,
size_t bytes,
int device,
cudaStream_t stream) {
cudaMemLocation loc{};
loc.type = cudaMemLocationTypeDevice;
loc.id = device;
// flags = 0
return cudaMemPrefetchAsync(ptr, bytes, loc, 0u, stream);
}
#else
static inline cudaError_t bnb_cudaMemPrefetchAsync(const void* ptr,
size_t bytes,
int device,
cudaStream_t stream) {
return cudaMemPrefetchAsync(ptr, bytes, device, stream);
}
#endif
#endif
#if BUILD_HIP
#include <ops_hip.cuh>
Expand Down Expand Up @@ -623,7 +644,7 @@ void cprefetch(void* ptr, size_t bytes, int device) {
if (hasPrefetch == 0)
return;

CUDA_CHECK_RETURN(cudaMemPrefetchAsync(ptr, bytes, device, 0));
CUDA_CHECK_RETURN(bnb_cudaMemPrefetchAsync(ptr, bytes, device, 0));
CUDA_CHECK_RETURN(cudaPeekAtLastError());
}

Expand Down
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