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104 lines
4.7 KiB
Plaintext
104 lines
4.7 KiB
Plaintext
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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///////////////////////////////////////////////////////////////////////////////
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// Polynomial approximation of cumulative normal distribution function
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///////////////////////////////////////////////////////////////////////////////
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__device__ inline float cndGPU(float d) {
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const float A1 = 0.31938153f;
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const float A2 = -0.356563782f;
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const float A3 = 1.781477937f;
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const float A4 = -1.821255978f;
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const float A5 = 1.330274429f;
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const float RSQRT2PI = 0.39894228040143267793994605993438f;
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float K = __fdividef(1.0f, (1.0f + 0.2316419f * fabsf(d)));
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float cnd = RSQRT2PI * __expf(-0.5f * d * d) *
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(K * (A1 + K * (A2 + K * (A3 + K * (A4 + K * A5)))));
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if (d > 0) cnd = 1.0f - cnd;
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return cnd;
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}
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///////////////////////////////////////////////////////////////////////////////
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// Black-Scholes formula for both call and put
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///////////////////////////////////////////////////////////////////////////////
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__device__ inline void BlackScholesBodyGPU(float &CallResult, float &PutResult,
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float S, // Stock price
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float X, // Option strike
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float T, // Option years
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float R, // Riskless rate
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float V // Volatility rate
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) {
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float sqrtT, expRT;
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float d1, d2, CNDD1, CNDD2;
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sqrtT = __fdividef(1.0F, rsqrtf(T));
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d1 = __fdividef(__logf(S / X) + (R + 0.5f * V * V) * T, V * sqrtT);
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d2 = d1 - V * sqrtT;
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CNDD1 = cndGPU(d1);
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CNDD2 = cndGPU(d2);
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// Calculate Call and Put simultaneously
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expRT = __expf(-R * T);
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CallResult = S * CNDD1 - X * expRT * CNDD2;
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PutResult = X * expRT * (1.0f - CNDD2) - S * (1.0f - CNDD1);
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}
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////////////////////////////////////////////////////////////////////////////////
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// Process an array of optN options on GPU
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////////////////////////////////////////////////////////////////////////////////
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extern "C" __launch_bounds__(128) __global__
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void BlackScholesGPU(float2 *__restrict d_CallResult,
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float2 *__restrict d_PutResult,
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float2 *__restrict d_StockPrice,
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float2 *__restrict d_OptionStrike,
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float2 *__restrict d_OptionYears, float Riskfree,
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float Volatility, int optN) {
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////Thread index
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const int opt = blockDim.x * blockIdx.x + threadIdx.x;
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// Calculating 2 options per thread to increase ILP (instruction level
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// parallelism)
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if (opt < (optN / 2)) {
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float callResult1, callResult2;
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float putResult1, putResult2;
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BlackScholesBodyGPU(callResult1, putResult1, d_StockPrice[opt].x,
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d_OptionStrike[opt].x, d_OptionYears[opt].x, Riskfree,
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Volatility);
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BlackScholesBodyGPU(callResult2, putResult2, d_StockPrice[opt].y,
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d_OptionStrike[opt].y, d_OptionYears[opt].y, Riskfree,
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Volatility);
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d_CallResult[opt] = make_float2(callResult1, callResult2);
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d_PutResult[opt] = make_float2(putResult1, putResult2);
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}
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}
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