From f11468442c78d95adae9c447a7f6d74158ce2bf3 Mon Sep 17 00:00:00 2001
From: lambday <heavensdevil6909@gmail.com>
Date: Sun, 7 Jul 2013 13:33:00 +0530
Subject: [PATCH] performance test of sparse-matrix vector product added

---
 benchmarks/sparse_test.cpp | 130 +++++++++++++++++++++++++++++++++++++
 1 file changed, 130 insertions(+)
 create mode 100644 benchmarks/sparse_test.cpp

diff --git a/benchmarks/sparse_test.cpp b/benchmarks/sparse_test.cpp
new file mode 100644
index 00000000000..39e625103d1
--- /dev/null
+++ b/benchmarks/sparse_test.cpp
@@ -0,0 +1,130 @@
+/*
+ * This program is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 3 of the License, or
+ * (at your option) any later version.
+ * 
+ * Written (W) 2013 Soumyajit De
+ */
+
+#include <shogun/lib/common.h>
+
+#ifdef HAVE_EIGEN3
+#include <shogun/lib/SGVector.h>
+#include <shogun/lib/SGSparseMatrix.h>
+#include <shogun/lib/SGSparseVector.h>
+#include <shogun/mathematics/Math.h>
+#include <shogun/mathematics/eigen3.h>
+#include <time.h>
+
+using namespace shogun;
+using namespace Eigen;
+
+SGVector<float64_t> sg_m_apply(SGSparseMatrix<float64_t> m, SGVector<float64_t> v)
+{
+	SGVector<float64_t> r(v.vlen);
+	ASSERT(v.vlen==m.num_vectors);
+	for (index_t i=0; i<m.num_vectors; ++i)
+		r[i]=m[i].dense_dot(1.0, v.vector, v.vlen, 0.0);
+
+	return r;
+}
+
+int main(int argc, char** argv)
+{
+	init_shogun_with_defaults();
+	//sg_io->set_loglevel(MSG_GCDEBUG);
+
+	const index_t n=100;
+	const index_t times=5;
+	const index_t size=1000000;
+	SGVector<float64_t> v(size);
+	v.set_const(1.0);
+	Map<VectorXd> map_v(v.vector, v.vlen);
+	clock_t start, end;
+
+	SG_SPRINT("time\tshogun (s)\teigen3 (s)\n\n");
+	for (index_t t=0; t<times; ++t)
+	{
+//#ifdef RUN_SHOGUN
+		SGSparseMatrix<float64_t> sg_m(size, size);
+		typedef SGSparseVectorEntry<float64_t> Entry;
+		SGSparseVector<float64_t> *vec=SG_MALLOC(SGSparseVector<float64_t>, size);
+
+		// for first row
+		Entry *first=SG_MALLOC(Entry, size);
+		// the digonal index for row #1
+		first[0].feat_index=0;  
+		first[0].entry=1.836593;
+		for (index_t i=1; i<size; ++i)
+		{
+			// fill the index for row #1
+			first[i].feat_index=i; 
+			first[i].entry=0.02;
+		}
+		vec[0].features=first;
+		vec[0].num_feat_entries=size;
+		sg_m[0]=vec[0].get();
+
+		// fill the rest of the rows
+		Entry** rest=SG_MALLOC(Entry*, size-1);
+		for (index_t i=0; i<size-1; ++i)
+		{
+			// the first col
+			rest[i]=SG_MALLOC(Entry, 2);
+			rest[i][0].feat_index=0; 
+			rest[i][0].entry=0.01;
+
+			// the diagonal element
+			rest[i][1].feat_index=i+1; 
+			rest[i][1].entry=1.836593;
+
+			vec[i+1].features=rest[i];
+			vec[i+1].num_feat_entries=2;
+
+			sg_m[i+1]=vec[i+1].get();
+		}
+		SGVector<float64_t> r(size);
+
+		// sg starts
+		start=clock();
+		for (index_t i=0; i<n; ++i)
+			r=sg_m_apply(sg_m, v);
+		end=clock();
+
+		float64_t sg_time=static_cast<float64_t>(end-start)/CLOCKS_PER_SEC;
+
+		Map<VectorXd> map_r(r.vector, r.vlen);
+		float64_t sg_norm=map_r.norm();
+
+//#endif // RUN_SHOGUN
+
+//#ifdef RUN_EIGEN
+		const SparseMatrix<float64_t> &eig_m=EigenSparseUtil<float64_t>::toEigenSparse(sg_m);
+		VectorXd eig_r(size);
+
+		// eigen3 starts
+		start=clock();
+		for (index_t i=0; i<n; ++i)
+			eig_r=eig_m*map_v;
+		end=clock();
+
+		float64_t eig_time=static_cast<float64_t>(end-start)/CLOCKS_PER_SEC;
+
+		float64_t eig_norm=eig_r.norm();
+//#endif // RUN_EIGEN
+
+		SG_SPRINT("%d\t%lf\t%lf\n", t, sg_time, eig_time);
+		ASSERT(sg_time>eig_time);
+		ASSERT(CMath::abs(sg_norm-eig_norm)<=CMath::MACHINE_EPSILON)
+
+		SG_FREE(vec);
+		SG_FREE(rest);
+	}
+
+
+	exit_shogun();
+
+	return 0;
+}
+#endif // HAVE_EIGEN3