A Tool for Chemical Kinetics Simulation on Accelerated Architectures

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Presentation transcript:

A Tool for Chemical Kinetics Simulation on Accelerated Architectures John C. Linford ParaTools, Inc. NASA Booth 17 November 2014, SC’14

Chemical Kinetic Simulation Combustion Air and Water Quality Climate Change Wildfires Volcanic Eruptions Plastics Devolatilzation Microorganism Growth Cell Biology SC'14, Copyright © ParaTools, Inc.

70% of GEOS-Chem Runtime is Chemistry Eight threads Intel Core i7-4820K CPU 3.70GHz SC'14, Copyright © ParaTools, Inc.

70% of GEOS-Chem Runtime is Chemistry Eight threads Intel Core i7-4820K CPU 3.70GHz SC'14, Copyright © ParaTools, Inc.

Kppa: The Kinetic PreProcessor Accelerated Code generation Analysis Lexical parser CUDA Kppa Fortran C Python Code optimized Domain Specific Language Serial Multi-core GPGPU Intel MIC Architecture SC'14, Copyright © ParaTools, Inc.

Sparse Matrix/Vector Code Generation <% d_Decomp.begin() piv = lang.Variable('piv', REAL, 'Row element divided by diagonal') piv.declare() %> ${size_t} idx = blockDim.x*blockIdx.x+threadIdx.x; if(idx < ${ncells32}) { ${A} += idx; lang.upindent() for i in xrange(1, nvar): for j in xrange(crow[i], diag[i]): c = icol[j] d = diag[c] piv.assign(A[j*ncells32] / A[d*ncells32]) A[j*ncells32].assign(piv) ... } <% d_Decomp.end() %> Generates C, C++, CUDA, Fortran, or Python A[334] = t1; A[337] = -A[272]*t1 + A[337]; A[338] = -A[273]*t1 + A[338]; A[339] = -A[274]*t1 + A[339]; A[340] = -A[275]*t1 + A[340]; t2 = A[335]/A[329]; A[335] = t2; A[337] = -A[330]*t2 + A[337]; A[338] = -A[331]*t2 + A[338]; A[339] = -A[332]*t2 + A[339]; A[340] = -A[333]*t2 + A[340]; t3 = A[341]/A[59]; SC'14, Copyright © ParaTools, Inc.

Simplify During Code Generation X[27] = ((A[43]*A[43]*A[43]) + (A[43]*A[43]) – (A[43]) – (5+4)) / (A[43]*A[43] + (8-6)*A[43] + 1) Simplify Fortran X(28) = A(44) - 1 SC'14, Copyright © ParaTools, Inc.

Fewer Operations, Faster Runtimes SC'14, Copyright © ParaTools, Inc.

Performance Results Baseline: hand-tuned KPP-generated code Use KPP to generate a serial code A skilled programmer parallelizes the code Comparison: unmodified Kppa-generated code Same input files as KPP No modification to source Results: Xeon Phi: 140% faster NVIDIA K40: 160% faster Xeon with OpenMP: 60% faster Exact same hardware SC'14, Copyright © ParaTools, Inc.

Performance Results SC'14, Copyright © ParaTools, Inc.

Chemical Kernel Runtime SC'14, Copyright © ParaTools, Inc.

SBIR Project Status NASA SBIR, Phase I successful Phase II to implement: Advanced reaction rate functions Knight’s Landing support FPGA support Auto-tuning source for hardware parameters User interface and prototyping environment SC'14, Copyright © ParaTools, Inc.

Downloads, tutorials, resources http://www.paratools.com/kppa Downloads, tutorials, resources SC'14, Copyright © ParaTools, Inc.