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July 2, 2013 23:19
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Version 1.2 of NVIDIA's double-double arithmetic header, distributed in accordance with its BSD License.
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/* | |
* Copyright (c) 2011-2013 NVIDIA Corporation. All rights reserved. | |
* | |
* Redistribution and use in source and binary forms, with or without | |
* modification, are permitted provided that the following conditions are met: | |
* | |
* Redistributions of source code must retain the above copyright notice, | |
* this list of conditions and the following disclaimer. | |
* | |
* Redistributions in binary form must reproduce the above copyright notice, | |
* this list of conditions and the following disclaimer in the documentation | |
* and/or other materials provided with the distribution. | |
* | |
* Neither the name of NVIDIA Corporation nor the names of its contributors | |
* may be used to endorse or promote products derived from this software | |
* without specific prior written permission. | |
* | |
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | |
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | |
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | |
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE | |
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR | |
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF | |
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS | |
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN | |
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) | |
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | |
* POSSIBILITY OF SUCH DAMAGE. | |
*/ | |
/* | |
* Release 1.2 | |
* | |
* (1) Deployed new implementation of div_dbldbl() and sqrt_dbldbl() based on | |
* Newton-Raphson iteration, providing significant speedup. | |
* (2) Added new function rsqrt_dbldbl() which provides reciprocal square root. | |
* | |
* Release 1.1 | |
* | |
* (1) Fixed a bug affecting add_dbldbl() and sub_dbldbl() that in very rare | |
* cases returned results with reduced accuracy. | |
* (2) Replaced the somewhat inaccurate error bounds with the experimentally | |
* observed maximum relative error. | |
*/ | |
#if !defined(DBLDBL_H_) | |
#define DBLDBL_H_ | |
#if defined(__cplusplus) | |
extern "C" { | |
#endif /* __cplusplus */ | |
#include <math.h> /* import sqrt() */ | |
/* The head of a double-double number is stored in the most significant part | |
of a double2 (the y-component). The tail is stored in the least significant | |
part of the double2 (the x-component). All double-double operands must be | |
normalized on both input to and return from all basic operations, i.e. the | |
magnitude of the tail shall be <= 0.5 ulp of the head. | |
*/ | |
typedef double2 dbldbl; | |
/* Create a double-double from two doubles. No normalization is performed, | |
so the head and tail components passed in must satisfy the normalization | |
requirement. To create a double-double from two arbitrary double-precision | |
numbers, use add_double_to_dbldbl(). | |
*/ | |
__device__ __forceinline__ dbldbl make_dbldbl (double head, double tail) | |
{ | |
dbldbl z; | |
z.x = tail; | |
z.y = head; | |
return z; | |
} | |
/* Return the head of a double-double number */ | |
__device__ __forceinline__ double get_dbldbl_head (dbldbl a) | |
{ | |
return a.y; | |
} | |
/* Return the tail of a double-double number */ | |
__device__ __forceinline__ double get_dbldbl_tail (dbldbl a) | |
{ | |
return a.x; | |
} | |
/* Compute error-free sum of two unordered doubles. See Knuth, TAOCP vol. 2 */ | |
__device__ __forceinline__ dbldbl add_double_to_dbldbl (double a, double b) | |
{ | |
double t1, t2; | |
dbldbl z; | |
z.y = __dadd_rn (a, b); | |
t1 = __dadd_rn (z.y, -a); | |
t2 = __dadd_rn (z.y, -t1); | |
t1 = __dadd_rn (b, -t1); | |
t2 = __dadd_rn (a, -t2); | |
z.x = __dadd_rn (t1, t2); | |
return z; | |
} | |
/* Compute error-free product of two doubles. Take full advantage of FMA */ | |
__device__ __forceinline__ dbldbl mul_double_to_dbldbl (double a, double b) | |
{ | |
dbldbl z; | |
z.y = __dmul_rn (a, b); | |
z.x = __fma_rn (a, b, -z.y); | |
return z; | |
} | |
/* Negate a double-double number, by separately negating head and tail */ | |
__device__ __forceinline__ dbldbl neg_dbldbl (dbldbl a) | |
{ | |
dbldbl z; | |
z.y = -a.y; | |
z.x = -a.x; | |
return z; | |
} | |
/* Compute high-accuracy sum of two double-double operands. In the absence of | |
underflow and overflow, the maximum relative error observed with 10 billion | |
test cases was 3.0716194922303448e-32 (~= 2**-104.6826). | |
This implementation is based on: Andrew Thall, Extended-Precision | |
Floating-Point Numbers for GPU Computation. Retrieved on 7/12/2011 | |
from http://andrewthall.org/papers/df64_qf128.pdf. | |
*/ | |
__device__ __forceinline__ dbldbl add_dbldbl (dbldbl a, dbldbl b) | |
{ | |
dbldbl z; | |
double t1, t2, t3, t4, t5, e; | |
t1 = __dadd_rn (a.y, b.y); | |
t2 = __dadd_rn (t1, -a.y); | |
t3 = __dadd_rn (__dadd_rn (a.y, t2 - t1), __dadd_rn (b.y, -t2)); | |
t4 = __dadd_rn (a.x, b.x); | |
t2 = __dadd_rn (t4, -a.x); | |
t5 = __dadd_rn (__dadd_rn (a.x, t2 - t4), __dadd_rn (b.x, -t2)); | |
t3 = __dadd_rn (t3, t4); | |
t4 = __dadd_rn (t1, t3); | |
t3 = __dadd_rn (t1 - t4, t3); | |
t3 = __dadd_rn (t3, t5); | |
z.y = e = __dadd_rn (t4, t3); | |
z.x = __dadd_rn (t4 - e, t3); | |
return z; | |
} | |
/* Compute high-accuracy difference of two double-double operands. In the | |
absence of underflow and overflow, the maximum relative error observed | |
with 10 billion test cases was 3.0716194922303448e-32 (~= 2**-104.6826). | |
This implementation is based on: Andrew Thall, Extended-Precision | |
Floating-Point Numbers for GPU Computation. Retrieved on 7/12/2011 | |
from http://andrewthall.org/papers/df64_qf128.pdf. | |
*/ | |
__device__ __forceinline__ dbldbl sub_dbldbl (dbldbl a, dbldbl b) | |
{ | |
dbldbl z; | |
double t1, t2, t3, t4, t5, e; | |
t1 = __dadd_rn (a.y, -b.y); | |
t2 = __dadd_rn (t1, -a.y); | |
t3 = __dadd_rn (__dadd_rn (a.y, t2 - t1), - __dadd_rn (b.y, t2)); | |
t4 = __dadd_rn (a.x, -b.x); | |
t2 = __dadd_rn (t4, -a.x); | |
t5 = __dadd_rn (__dadd_rn (a.x, t2 - t4), - __dadd_rn (b.x, t2)); | |
t3 = __dadd_rn (t3, t4); | |
t4 = __dadd_rn (t1, t3); | |
t3 = __dadd_rn (t1 - t4, t3); | |
t3 = __dadd_rn (t3, t5); | |
z.y = e = __dadd_rn (t4, t3); | |
z.x = __dadd_rn (t4 - e, t3); | |
return z; | |
} | |
/* Compute high-accuracy product of two double-double operands, taking full | |
advantage of FMA. In the absence of underflow and overflow, the maximum | |
relative error observed with 10 billion test cases was 5.238480533564479e-32 | |
(~= 2**-103.9125). | |
*/ | |
__device__ __forceinline__ dbldbl mul_dbldbl (dbldbl a, dbldbl b) | |
{ | |
dbldbl t, z; | |
double e; | |
t.y = __dmul_rn (a.y, b.y); | |
t.x = __fma_rn (a.y, b.y, -t.y); | |
t.x = __fma_rn (a.x, b.x, t.x); | |
t.x = __fma_rn (a.y, b.x, t.x); | |
t.x = __fma_rn (a.x, b.y, t.x); | |
z.y = e = __dadd_rn (t.y, t.x); | |
z.x = __dadd_rn (t.y - e, t.x); | |
return z; | |
} | |
/* Compute high-accuracy quotient of two double-double operands, using Newton- | |
Raphson iteration. Based on: T. Nagai, H. Yoshida, H. Kuroda, Y. Kanada. | |
Fast Quadruple Precision Arithmetic Library on Parallel Computer SR11000/J2. | |
In Proceedings of the 8th International Conference on Computational Science, | |
ICCS '08, Part I, pp. 446-455. In the absence of underflow and overflow, the | |
maximum relative error observed with 10 billion test cases was | |
1.0161322480099059e-31 (~= 2**-102.9566). | |
*/ | |
__device__ __forceinline__ dbldbl div_dbldbl (dbldbl a, dbldbl b) | |
{ | |
dbldbl t, z; | |
double e, r; | |
r = 1.0 / b.y; | |
t.y = __dmul_rn (a.y, r); | |
e = __fma_rn (b.y, -t.y, a.y); | |
t.y = __fma_rn (r, e, t.y); | |
t.x = __fma_rn (b.y, -t.y, a.y); | |
t.x = __dadd_rn (a.x, t.x); | |
t.x = __fma_rn (b.x, -t.y, t.x); | |
e = __dmul_rn (r, t.x); | |
t.x = __fma_rn (b.y, -e, t.x); | |
t.x = __fma_rn (r, t.x, e); | |
z.y = e = __dadd_rn (t.y, t.x); | |
z.x = __dadd_rn (t.y - e, t.x); | |
return z; | |
} | |
/* Compute high-accuracy square root of a double-double number. Newton-Raphson | |
iteration based on equation 4 from a paper by Alan Karp and Peter Markstein, | |
High Precision Division and Square Root, ACM TOMS, vol. 23, no. 4, December | |
1997, pp. 561-589. In the absence of underflow and overflow, the maximum | |
relative error observed with 10 billion test cases was | |
3.7564109505601846e-32 (~= 2**-104.3923). | |
*/ | |
__device__ __forceinline__ dbldbl sqrt_dbldbl (dbldbl a) | |
{ | |
dbldbl t, z; | |
double e, y, s, r; | |
r = rsqrt (a.y); | |
if (a.y == 0.0) r = 0.0; | |
y = __dmul_rn (a.y, r); | |
s = __fma_rn (y, -y, a.y); | |
r = __dmul_rn (0.5, r); | |
z.y = e = __dadd_rn (s, a.x); | |
z.x = __dadd_rn (s - e, a.x); | |
t.y = __dmul_rn (r, z.y); | |
t.x = __fma_rn (r, z.y, -t.y); | |
t.x = __fma_rn (r, z.x, t.x); | |
r = __dadd_rn (y, t.y); | |
s = __dadd_rn (y - r, t.y); | |
s = __dadd_rn (s, t.x); | |
z.y = e = __dadd_rn (r, s); | |
z.x = __dadd_rn (r - e, s); | |
return z; | |
} | |
/* Compute high-accuracy reciprocal square root of a double-double number. | |
Based on Newton-Raphson iteration. In the absence of underflow and overflow, | |
the maximum relative error observed with 10 billion test cases was | |
6.4937771666026349e-32 (~= 2**-103.6026) | |
*/ | |
__device__ __forceinline__ dbldbl rsqrt_dbldbl (dbldbl a) | |
{ | |
dbldbl z; | |
double r, s, e; | |
r = rsqrt (a.y); | |
e = __dmul_rn (a.y, r); | |
s = __fma_rn (e, -r, 1.0); | |
e = __fma_rn (a.y, r, -e); | |
s = __fma_rn (e, -r, s); | |
e = __dmul_rn (a.x, r); | |
s = __fma_rn (e, -r, s); | |
e = 0.5 * r; | |
z.y = __dmul_rn (e, s); | |
z.x = __fma_rn (e, s, -z.y); | |
s = __dadd_rn (r, z.y); | |
r = __dadd_rn (r, -s); | |
r = __dadd_rn (r, z.y); | |
r = __dadd_rn (r, z.x); | |
z.y = e = __dadd_rn (s, r); | |
z.x = __dadd_rn (s - e, r); | |
return z; | |
} | |
#if defined(__cplusplus) | |
} | |
#endif /* __cplusplus */ | |
#endif /* DBLDBL_H_ */ |
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yeah... I went back and looked at the original paper... this is definately wrong. The paper starts off by dividing by b.x not b.y. I implemented exactly what is in the paper and the results are much better.