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1 change: 1 addition & 0 deletions cpp/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -349,6 +349,7 @@ add_library(
src/ast/expressions.cpp
src/ast/operators.cpp
src/binaryop/binaryop.cpp
src/binaryop/decimal_ops.cu
src/binaryop/compiled/ATan2.cu
src/binaryop/compiled/Add.cu
src/binaryop/compiled/BitwiseAnd.cu
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103 changes: 103 additions & 0 deletions cpp/include/cudf/decimal/decimal_ops.hpp

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We should probably rename "decimal" to "fixed point" for consistency with the rest of libcudf. The code paths we have don't force the base to be 10 (could be binary).

That would put this in cudf/fixed_point/fixed_point_operators.hpp or similar.

Original file line number Diff line number Diff line change
@@ -0,0 +1,103 @@
/*
* Copyright (c) 2025, NVIDIA CORPORATION.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

#pragma once

#include <cudf/column/column.hpp>
#include <cudf/fixed_point/fixed_point.hpp>
#include <cudf/scalar/scalar.hpp>
#include <cudf/utilities/export.hpp>
#include <cudf/utilities/memory_resource.hpp>

#include <memory>

namespace CUDF_EXPORT cudf {

/**
* @addtogroup transformation_decimalops
* @{
* @file
* @brief Column APIs for decimal operations with scale preservation
*/

/**
* @brief Performs decimal division between two columns with scale preservation.
*
* The output contains the result of `divide_decimal(lhs[i], rhs[i])` for all `0 <= i < lhs.size()`
* The scale of the output is preserved to match the scale of the left operand.
*
* @param lhs The left operand column
* @param rhs The right operand column
* @param rounding_mode The rounding mode to use
* @param stream CUDA stream used for device memory operations and kernel launches
* @param mr Device memory resource used to allocate the returned column's device memory
* @return Output column containing the result of the decimal division
* @throw cudf::logic_error if @p lhs and @p rhs are different sizes
* @throw cudf::logic_error if @p lhs and @p rhs are not decimal types
*/
std::unique_ptr<column> divide_decimal(
column_view const& lhs,
column_view const& rhs,
numeric::decimal_rounding_mode rounding_mode = numeric::decimal_rounding_mode::HALF_UP,
rmm::cuda_stream_view stream = cudf::get_default_stream(),
rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());

/**
* @brief Performs decimal division between a column and a scalar with scale preservation.
*
* The output contains the result of `divide_decimal(lhs[i], rhs)` for all `0 <= i < lhs.size()`
* The scale of the output is preserved to match the scale of the left operand.
*
* @param lhs The left operand column
* @param rhs The right operand scalar
* @param rounding_mode The rounding mode to use
* @param stream CUDA stream used for device memory operations and kernel launches
* @param mr Device memory resource used to allocate the returned column's device memory
* @return Output column containing the result of the decimal division
* @throw cudf::logic_error if @p lhs is not a decimal type
* @throw cudf::logic_error if @p rhs is not a decimal scalar
*/
std::unique_ptr<column> divide_decimal(
column_view const& lhs,
scalar const& rhs,
numeric::decimal_rounding_mode rounding_mode = numeric::decimal_rounding_mode::HALF_UP,
rmm::cuda_stream_view stream = cudf::get_default_stream(),
rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());

/**
* @brief Performs decimal division between a scalar and a column with scale preservation.
*
* The output contains the result of `divide_decimal(lhs, rhs[i])` for all `0 <= i < rhs.size()`
* The scale of the output is preserved to match the scale of the left operand.
*
* @param lhs The left operand scalar
* @param rhs The right operand column
* @param rounding_mode The rounding mode to use
* @param stream CUDA stream used for device memory operations and kernel launches
* @param mr Device memory resource used to allocate the returned column's device memory
* @return Output column containing the result of the decimal division
* @throw cudf::logic_error if @p lhs is not a decimal scalar
* @throw cudf::logic_error if @p rhs is not a decimal type
*/
std::unique_ptr<column> divide_decimal(
scalar const& lhs,
column_view const& rhs,
numeric::decimal_rounding_mode rounding_mode = numeric::decimal_rounding_mode::HALF_UP,
rmm::cuda_stream_view stream = cudf::get_default_stream(),
rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());

/** @} */ // end of group
} // namespace CUDF_EXPORT cudf
140 changes: 140 additions & 0 deletions cpp/include/cudf/fixed_point/fixed_point.hpp
Original file line number Diff line number Diff line change
Expand Up @@ -716,6 +716,21 @@ CUDF_HOST_DEVICE inline fixed_point<Rep1, Rad1> operator*(fixed_point<Rep1, Rad1
scaled_integer<Rep1>(lhs._value * rhs._value, scale_type{lhs._scale + rhs._scale})};
}

namespace detail {

} // namespace detail

/**
* @brief Rounding modes for decimal division operations
*
* Specifies how to round the result when performing decimal division
* with scale preservation.
*/
enum class decimal_rounding_mode : int32_t {

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HALF_UP = 0, ///< Round half away from zero
HALF_EVEN = 1 ///< Round half to even (banker's rounding)
};

// DIVISION Operation
template <typename Rep1, Radix Rad1>
CUDF_HOST_DEVICE inline fixed_point<Rep1, Rad1> operator/(fixed_point<Rep1, Rad1> const& lhs,
Expand All @@ -731,6 +746,131 @@ CUDF_HOST_DEVICE inline fixed_point<Rep1, Rad1> operator/(fixed_point<Rep1, Rad1
scaled_integer<Rep1>(lhs._value / rhs._value, scale_type{lhs._scale - rhs._scale})};
}

/**
* @brief Performs decimal division with scale preservation
*
* This function divides two fixed-point numbers while preserving the scale
* of the dividend (left-hand side). This behavior is similar to Java's
* BigDecimal.divide(divisor, roundingMode) which maintains the dividend's scale.
*
* @tparam Rep1 The representation type of the fixed-point numbers
* @tparam Rad1 The radix of the fixed-point numbers
* @param lhs The dividend (left-hand side of division)
* @param rhs The divisor (right-hand side of division)
* @param rounding_mode The rounding mode to use (default: HALF_UP)
* @return A fixed-point number with the same scale as the dividend
*/
template <typename Rep1, Radix Rad1>

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If this is specialized for decimals, we might need to require that the radix is 10. But if this logic is generic, we should call it "fixed point" rather than "decimal."

CUDF_HOST_DEVICE inline fixed_point<Rep1, Rad1> divide_decimal(
fixed_point<Rep1, Rad1> const& lhs,
fixed_point<Rep1, Rad1> const& rhs,
decimal_rounding_mode rounding_mode = decimal_rounding_mode::HALF_UP)
{
// Check for division by zero
// In CUDA device code, we cannot throw exceptions, so we assert
// In host code, this will cause undefined behavior (same as standard division)
#if defined(__CUDACC_DEBUG__)
assert(rhs.value() != 0 && "division by zero");
assert(!detail::division_overflow<Rep1>(lhs.value(), rhs.value()) && "fixed_point overflow");
#endif

// Scale up the dividend to maintain precision
// Result will have scale = lhs.scale()
// We need to compensate for the scale difference to preserve the dividend's scale
// Standard division would give us scale = lhs.scale() - rhs.scale()
// To preserve lhs.scale(), we need to scale up by 10^(-rhs.scale())
auto const scale_factor = detail::ipow<Rep1, Rad1>(-static_cast<int>(rhs.scale()));

// Check for potential overflow when scaling
bool overflow = multiplication_overflow<Rep1>(lhs.value(), scale_factor);

if (!overflow) {
// Standard calculation without overflow
Rep1 scaled_dividend = lhs.value() * scale_factor;
Rep1 quotient = scaled_dividend / rhs.value();
Rep1 remainder = scaled_dividend % rhs.value();

// Apply rounding based on remainder
if (rounding_mode == decimal_rounding_mode::HALF_UP) {
// Round half away from zero
// Avoid abs() ambiguity for __int128 by using conditional
auto abs_remainder = (remainder < 0) ? -remainder : remainder;
auto abs_divisor = (rhs.value() < 0) ? -rhs.value() : rhs.value();
if (abs_remainder * 2 >= abs_divisor) {
// Round away from zero: if quotient is positive, add 1; if negative, subtract 1
quotient += (quotient >= 0) ? 1 : -1;
}
} else if (rounding_mode == decimal_rounding_mode::HALF_EVEN) {
// Banker's rounding
// Avoid abs() ambiguity for __int128 by using conditional

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auto abs_rem_2 = ((remainder < 0) ? -remainder : remainder) * 2;
auto abs_divisor = (rhs.value() < 0) ? -rhs.value() : rhs.value();
if (abs_rem_2 > abs_divisor || (abs_rem_2 == abs_divisor && (quotient % 2) != 0)) {
// Round to nearest even: direction depends on quotient sign
quotient += (quotient >= 0) ? 1 : -1;
}
}

return fixed_point<Rep1, Rad1>{scaled_integer<Rep1>{quotient, lhs.scale()}};
}

// Handle overflow cases with type promotion
if constexpr (cuda::std::is_same_v<Rep1, int32_t>) {
// Try int64_t first
using WiderRep = int64_t;
WiderRep wide_scale = static_cast<WiderRep>(scale_factor);
bool overflow_in_int64 =
multiplication_overflow<WiderRep>(static_cast<WiderRep>(lhs.value()), wide_scale);

if (!overflow_in_int64) {
WiderRep scaled_dividend = static_cast<WiderRep>(lhs.value()) * wide_scale;
WiderRep wide_divisor = static_cast<WiderRep>(rhs.value());
WiderRep quotient = scaled_dividend / wide_divisor;
WiderRep remainder = scaled_dividend % wide_divisor;

// Apply rounding
if (rounding_mode == decimal_rounding_mode::HALF_UP) {
auto abs_remainder = (remainder < 0) ? -remainder : remainder;
auto abs_divisor = (wide_divisor < 0) ? -wide_divisor : wide_divisor;
if (abs_remainder * 2 >= abs_divisor) { quotient += (quotient >= 0) ? 1 : -1; }
} else if (rounding_mode == decimal_rounding_mode::HALF_EVEN) {
auto abs_rem_2 = ((remainder < 0) ? -remainder : remainder) * 2;
auto abs_divisor = (wide_divisor < 0) ? -wide_divisor : wide_divisor;
if (abs_rem_2 > abs_divisor || (abs_rem_2 == abs_divisor && (quotient % 2) != 0)) {
quotient += (quotient >= 0) ? 1 : -1;
}
}

return fixed_point<Rep1, Rad1>{
scaled_integer<Rep1>{static_cast<Rep1>(quotient), lhs.scale()}};
}
}

// Fallback to __int128_t for severe overflow cases
using WidestRep = __int128_t;
WidestRep wide_scale = static_cast<WidestRep>(scale_factor);
WidestRep scaled_dividend = static_cast<WidestRep>(lhs.value()) * wide_scale;
WidestRep wide_divisor = static_cast<WidestRep>(rhs.value());
WidestRep quotient = scaled_dividend / wide_divisor;
WidestRep remainder = scaled_dividend % wide_divisor;

// Apply rounding
if (rounding_mode == decimal_rounding_mode::HALF_UP) {

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Can we pull out some of this logic into a function templated on the rep? It looks like it's repeated several times.

WidestRep abs_rem = (remainder < 0) ? -remainder : remainder;
WidestRep abs_div = (wide_divisor < 0) ? -wide_divisor : wide_divisor;
if (abs_rem * 2 >= abs_div) { quotient += (quotient >= 0) ? 1 : -1; }
} else if (rounding_mode == decimal_rounding_mode::HALF_EVEN) {
WidestRep abs_rem = (remainder < 0) ? -remainder : remainder;
WidestRep abs_div = (wide_divisor < 0) ? -wide_divisor : wide_divisor;
WidestRep abs_rem_2 = abs_rem * 2;
if (abs_rem_2 > abs_div || (abs_rem_2 == abs_div && (quotient % 2) != 0)) {
quotient += (quotient >= 0) ? 1 : -1;
}
}

return fixed_point<Rep1, Rad1>{scaled_integer<Rep1>{static_cast<Rep1>(quotient), lhs.scale()}};
}

// EQUALITY COMPARISON Operation
template <typename Rep1, Radix Rad1>
CUDF_HOST_DEVICE inline bool operator==(fixed_point<Rep1, Rad1> const& lhs,
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