diff --git a/fastlib/u/nvasil/sparse/bfile.txt b/fastlib/u/nvasil/sparse/bfile.txt
new file mode 100644
index 0000000000..cf1043061f
--- /dev/null
+++ b/fastlib/u/nvasil/sparse/bfile.txt
@@ -0,0 +1,101 @@
+100
+7.346300e-001
+7.374979e-001
+6.936535e-001
+6.702775e-001
+3.585772e-001
+3.788121e-002
+6.882729e-001
+5.103941e-001
+9.355582e-002
+6.561860e-001
+2.742218e-001
+8.160376e-001
+4.988111e-001
+4.135763e-001
+7.811456e-002
+1.533728e-001
+7.781087e-001
+7.116524e-002
+6.191919e-001
+7.837094e-001
+3.357823e-001
+4.321649e-001
+9.888512e-001
+6.287611e-001
+5.200221e-001
+8.553515e-001
+2.970969e-001
+6.629188e-001
+2.882765e-001
+4.245862e-001
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+8.619233e-002
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diff --git a/fastlib/u/nvasil/sparse/build.py b/fastlib/u/nvasil/sparse/build.py
new file mode 100644
index 0000000000..d108d541ad
--- /dev/null
+++ b/fastlib/u/nvasil/sparse/build.py
@@ -0,0 +1,14 @@
+librule(
+  	name="sparse",
+		headers=["sparse_matrix.h", "conjugate_gradient.cc" ],
+		deplibs=["fastlib:fastlib"]
+		);
+
+binrule(
+		name="sparse_test",
+		sources=["sparse_matrix_unit.cc"],
+		headers=["sparse_matrix.h"],
+		deplibs=["fastlib:fastlib"]
+		);
+
+
diff --git a/fastlib/u/nvasil/sparse/conjugate_gradient.cc b/fastlib/u/nvasil/sparse/conjugate_gradient.cc
new file mode 100644
index 0000000000..c292d1c234
--- /dev/null
+++ b/fastlib/u/nvasil/sparse/conjugate_gradient.cc
@@ -0,0 +1,51 @@
+/*
+ * =====================================================================================
+ *
+ *       Filename:  conjugate_gradient.cc
+ *
+ *    Description:  
+ *
+ *        Version:  1.0
+ *        Created:  06/21/2007 01:13:30 PM EDT
+ *       Revision:  none
+ *       Compiler:  gcc
+ *
+ *         Author:  Nikolaos Vasiloglou (NV), nvasil@ieee.org
+ *        Company:  Georgia Tech Fastlab-ESP Lab
+ *
+ * =====================================================================================
+ */
+
+
+namespace sparse {
+// solves the problem A*x=b
+// where A is sparse semipositive definite 
+template<typename T> 
+void ConjugateGradient(Matrix<T> &A, T *b, T* x, T tolerance) {
+	index_t dimension=A.get_dimension();
+  T* r =  NewVector(dimension);
+	T* p =  NewVector(dimension);	
+  A.Multiply(x,r); // r=A*x
+	VectorMinus(b, r) // r=b-r;
+	memcpy(p, r, dimension*sizeof(T));
+	T *temp1=NewVector(dimension);
+  while() {
+		A.Multiply(p, temp1); // temp1=A*p;
+		T rr=VectorDotProduct(r, r, dimension);
+	  T alpha=rr/VectorDotProduct(temp1, p, dimension); // a=(r,r)/(A*p,p)
+    VectorPlusTimes(x, alpha, p, dimension, x);    // x=x+a*p
+    T error=alpha*VectorDotProduct(p, p)/VectorDotProduct(x, x);
+		if (error<tolerance) {
+		  break;
+		}
+		VectorMinusTimes(r, alpha, temp1, r);          // r=r-a*A*p;
+	  // beta=(r_j+1, r_j+1) / (r_j, r_j)
+		T beta=VectorDotProduct(r, r, dimension)/rr;  
+		// p = r + b*p
+		VectorPlusTimes(r, beta, p, dimension, p);	
+	} 
+	DeleteVector(r, dimension);
+	DeleteVector(p, dimension);
+	DeleteVector(temp1, dimension);
+}
+};
diff --git a/fastlib/u/nvasil/sparse/sparse_matrix.h b/fastlib/u/nvasil/sparse/sparse_matrix.h
new file mode 100644
index 0000000000..ee824e074e
--- /dev/null
+++ b/fastlib/u/nvasil/sparse/sparse_matrix.h
@@ -0,0 +1,319 @@
+/*
+ * =====================================================================================
+ * 
+ *       Filename:  sparse_matrix.h
+ * 
+ *    Description:  
+ * 
+ *        Version:  1.0
+ *        Created:  06/20/2007 02:40:16 PM EDT
+ *       Revision:  none
+ *       Compiler:  gcc
+ * 
+ *         Author:  Nikolaos Vasiloglou (NV), nvasil@ieee.org
+ *        Company:  Georgia Tech Fastlab-ESP Lab
+ * 
+ * =====================================================================================
+ */
+
+#ifndef SPARSE_MATRIX_H_
+#define SPARSE_MATRIX_H_
+
+#include <errno.h>
+#include <algorithm>
+#include <string>
+#include <sys/mman.h>
+#include "fastlib/fastlib.h"
+
+using namespace std;
+
+namespace sparse {
+template<typename T>
+class Matrix {
+ public:
+	typedef pair<index_t, T> NonZeroElement_t;
+	template<typename > friend class Matrix;
+	Matrix(){
+	  allocation_flag_=false;
+	}
+	~Matrix(){};
+	void Init(index_t dimension, 
+			      int32 max_non_zero) {
+		dimension_=dimension;
+		max_non_zero_=max_non_zero;
+		index_t alloc_size = dimension_ * 
+			                   max_non_zero_ * sizeof(NonZeroElement_t);
+		ptr_rows_ = (NonZeroElement_t *)mmap(NULL, alloc_size, 
+			          PROT_READ | PROT_WRITE, 
+								MAP_SHARED | MAP_ANONYMOUS, -1, 0);
+	  if (ptr_rows_==MAP_FAILED) {
+	    FATAL("Couldn't allocate memory for the ptr_rows_, error: %s\n",
+			  	  strerror(errno));
+	  }
+    allocation_flag_=true;
+		row_elements_=(int32 *)mmap(NULL, dimension_*sizeof(int32) , 
+			             PROT_READ | PROT_WRITE, 
+								   MAP_SHARED | MAP_ANONYMOUS, -1, 0);
+
+		Fill();
+	}
+	void Init(NonZeroElement_t *ptr_rows,
+			      index_t dimension,
+			      int32 max_non_zero) {
+	  ptr_rows_=ptr_rows;
+		dimension_=dimension;
+		max_non_zero_=max_non_zero;
+    row_elements_=(int32 *)mmap(NULL, dimension_*sizeof(int32) , 
+			             PROT_READ | PROT_WRITE, 
+								   MAP_SHARED | MAP_ANONYMOUS, -1, 0);
+
+		Fill();
+	}
+	void Init(string file) {
+	  FILE *fp=fopen(file.c_str(), "r");
+		if (fp==NULL) {
+		  FATAL("Error %s while trying to open %s\n", 
+					  strerror(errno), file.c_str());
+		}
+		fscanf(fp, "%i %i\n", dimension_, max_non_zero_);
+    index_t alloc_size = dimension_ * 
+			                   max_non_zero_ * sizeof(NonZeroElement_t);
+		ptr_rows_ = (NonZeroElement_t *)mmap(NULL, alloc_size, 
+			          PROT_READ | PROT_WRITE, 
+								MAP_SHARED | MAP_ANONYMOUS, -1, 0);
+	  if (ptr_rows_==MAP_FAILED) {
+	    FATAL("Couldn't allocate memory for the ptr_rows_, error: %s\n",
+			  	  strerror(errno));
+	  }
+    allocation_flag_=true;
+		row_elements_=(int32 *)mmap(NULL, dimension_*sizeof(int32) , 
+			             PROT_READ | PROT_WRITE, 
+								   MAP_SHARED | MAP_ANONYMOUS, -1, 0);
+
+		Fill();
+		long long i,j;
+		double val;
+		while (feof(fp)==false) {
+		  fscanf(fp,"%lli %lli %lg\n", &i, &j, &val);
+		  this->set(i, j, val);
+		}
+		fclose(fp);
+	}
+	void Destruct() {
+	  if (allocation_flag_==true) {
+			index_t alloc_size = dimension_ * 
+			                   max_non_zero_ * sizeof(NonZeroElement_t);
+		  munmap(ptr_rows_, alloc_size);
+		}
+		munmap(row_elements_, dimension_*sizeof(int32));
+  }
+  
+	inline T get(index_t  i, index_t j) {
+		index_t row = i*max_non_zero_;
+		DEBUG_ASSERT_MSG(i<dimension_ && i>=0,
+				            "Tried to access row %lli > %lli\n",
+			              (signed long long)i,
+										(signed long long)dimension_);
+		for(int32 k=0; k<row_elements_[i]; k++) {
+			if (ptr_rows_[row+k].first ==j) {
+			  return ptr_rows_[row+k].second;
+			} 
+		}
+    FATAL("Tried to access %lli, %lli "
+					"element which is zero", 
+					(signed long long)i,
+					(signed long long)j);		
+	}
+
+	inline void set(index_t  i, index_t j, T value) {
+		index_t row = i*max_non_zero_;
+		DEBUG_ASSERT_MSG(i<dimension_ && i>=0,
+				            "Tried to access row %lli > %lli\n",
+			              (signed long long)i,
+										(signed long long)dimension_);
+    DEBUG_ASSERT_MSG(row_elements_[i]<max_non_zero_,
+	      "The matrix is overfull, increase sparsity\n");
+    int32 k=row_elements_[i];
+		row_elements_[i]++;
+		ptr_rows_[row+k].first=j;
+		ptr_rows_[row+k].second=value;
+	}			
+	void Advise() {
+    if (madvise(ptr_rows_, 
+				    dimension_*max_non_zero_*sizeof(NonZeroElement_t),
+						MADV_SEQUENTIAL)==-1) {
+		  NONFATAL("Advising failed error %s\n", strerror(errno));
+		}
+	}
+	void UnAdvise() {
+	  if (madvise(ptr_rows_, 
+				    dimension_*max_non_zero_*sizeof(NonZeroElement_t),
+						MADV_NORMAL)==-1) {
+		  NONFATAL("Advising failed error %s\n", strerror(errno));
+		}
+	}
+  void Multiply(T* vec, T* result) {
+	  for(index_t i=0; i<dimension_; i++) {
+		  result[i]=0;
+			index_t row=i*max_non_zero_;
+			for(index_t k=0; k<row_elements_[i]; k++) {
+			  result[i]+=ptr_rows_[row+k].second * 
+					         vec[ptr_rows_[row+k].first];
+			}
+		}
+	}
+  void MakeFast() {
+	  for(index_t i=0; i<dimension_; i++) {
+			std::sort(ptr_rows_+i*(max_non_zero_), 
+					      ptr_rows_+i*(max_non_zero_)+row_elements_[i]);
+		}
+	}
+ 
+  inline T FastGet(index_t i, index_t j) {
+	  index_t ind = BinarySearch(i*max_non_zero_,
+															 i*max_non_zero_+row_elements_[i],
+															 j);
+		FATAL("You are trying to access %lli , %lli "
+				  "which is nonzero\n",
+				  (signed long long)i,
+				  (signed long long)j);
+		return ptr_rows_[ind].second;
+	}
+
+	inline bool IsZero(index_t i, index_t j) {
+	  index_t ind = BinarySearch(i*max_non_zero_,
+															 i*max_non_zero_+row_elements_[i]-1,
+															 j);
+		return ind==-1;
+	}
+
+	index_t get_dimension() {
+	  return dimension_;
+	}
+	index_t get_non_zeros_elements() {
+	  index_t total=0;
+		for(index_t i=0; i<dimension_; i++) {
+		  total+=row_elements_[i];
+		}
+		return total;
+	}
+ private:
+  NonZeroElement_t *ptr_rows_;
+	index_t dimension_;
+	int32 max_non_zero_;
+	bool allocation_flag_;
+	int32 *row_elements_;
+	void Fill() {
+	  for(index_t i=0; i<dimension_; i++) {
+			for(int32 j=0; j<max_non_zero_; j++){
+		    ptr_rows_[i*max_non_zero_+j].first=-1;
+			}
+		  row_elements_[i]=0;
+		}
+	}
+	inline index_t BinarySearch(index_t low, 
+			                 index_t high, 
+											 index_t value) {
+	  while(low <= high) {
+		  index_t mid=(low+high)/2;
+			if (ptr_rows_[mid].first > value) {
+			  high=mid-1;
+			} else {
+			  if (ptr_rows_[mid].first < value) {
+				  low=mid+1;
+				} else {
+			    return mid;
+			  }
+		  }
+		}
+		return -1;
+	}
+};
+
+// solves the problem A*x=b
+// where A is sparse semipositive definite 
+template<typename T> 
+void ConjugateGradient(Matrix<T> &A, T *b, T* x);
+template<typename T>
+inline T VectorDotProduct(T* a, T* b, index_t size) {
+  T result=0;
+	for(index_t i=0; i<size; i++) {
+	  result+=a[i]*b[i];
+	}
+	return result;
+}
+template<typename T>
+inline void VectorPlus(T* a, T* b, index_t size, T* c) {
+  for(index_t i=0; i<size; i++) {
+	  c[i]=a[i]+b[i];
+	}
+}
+template<typename T>
+inline void VectorPlusTimes(T* a, T scalar, T* b, index_t size, T* c) {
+  for(index_t i=0; i<size; i++) {
+	  c[i]=a[i]+scalar*b[i];
+	}
+}
+template<typename T>
+inline void VectorMinusTimes(T* a, T scalar, T* b, index_t size, T* c) {
+  for(index_t i=0; i<size; i++) {
+	  c[i]=a[i]-scalar*b[i];
+	}
+}
+
+template<typename T>
+inline void VectorMinus(T* a, T* b, index_t size, T* c) {
+  for(index_t i=0; i<size; i++) {
+	  c[i]=a[i]-b[i];
+	}
+}
+template<typename T>
+inline void VectorMultiplyScalar(T* vector_in, T scalar, index_t size, 
+		                      T* vector_out) {
+  for(index_t i=0; i<size; i++) {
+	  vector_out[i]=vector_in[i]*scalar;
+	}
+}
+template<typename T>
+inline T *NewVector(index_t size) {
+  T* out = (T*)mmap(NULL, size*sizeof(T), 
+	         PROT_READ | PROT_WRITE, 
+				   MAP_SHARED | MAP_ANONYMOUS, -1, 0);
+	if (madvise(out, size*sizeof(T),
+						MADV_SEQUENTIAL)==-1) {
+	  NONFATAL("Advising failed error %s\n", strerror(errno));
+	}
+  return out;
+}
+
+template<typename T>
+inline void DeleteVector(T* vector, index_t size) {
+  if (munmap(vector, size*sizeof(T))<0) {
+	  NONFATAL("Failed to unmap memory, error:%s\n", strerror(errno));
+	}
+}
+
+template<typename T>
+T *ReadVectorFromFile(string filename) {
+	FILE *fp;
+	fp=fopen(filename.c_str(), "r");
+  if (fp==NULL) {
+	  FATAL("Error %s while trying to open %s\n", strerror(errno));
+	}
+	long long size;
+	fscanf(fp, "%lli\n", &size);
+  T *ptr = NewVector<T>(size);
+	index_t i=0;
+	while (!feof(fp)) {
+		double value;
+	  fscanf(fp, "%lg", &value);
+		ptr[i]=(T)value;
+		i++;
+	}
+  fclose(fp);
+	return ptr;
+}
+
+
+};
+#endif // SPARSE_MATRIX_H_
diff --git a/fastlib/u/nvasil/sparse/sparse_matrix.txt b/fastlib/u/nvasil/sparse/sparse_matrix.txt
new file mode 100644
index 0000000000..ded01f9b16
--- /dev/null
+++ b/fastlib/u/nvasil/sparse/sparse_matrix.txt
@@ -0,0 +1,1817 @@
+100 24
+1 3 0.664438
+1 13 0.590944
+1 17 0.655779
+1 20 0.872673
+1 25 0.829382
+1 29 0.953315
+1 30 0.589027
+1 40 0.052128
+1 42 0.523904
+1 45 0.474484
+1 46 0.361999
+1 47 0.553318
+1 59 0.624345
+1 61 0.346019
+1 62 0.305001
+1 66 0.717042
+1 71 0.440940
+1 72 0.554369
+1 73 0.114245
+1 74 0.635088
+1 75 0.350227
+1 84 0.036090
+1 94 0.611102
+1 96 0.211177
+2 12 0.174376
+2 17 0.867039
+2 22 0.702509
+2 23 0.390910
+2 26 0.729493
+2 29 0.941871
+2 34 0.659477
+2 57 0.349864
+2 60 0.246087
+2 65 0.815712
+2 69 0.286254
+2 72 0.823947
+2 75 0.467771
+2 76 0.794068
+2 83 0.533563
+2 87 0.919668
+2 93 0.339884
+2 94 0.341080
+2 95 0.114607
+3 1 0.664438
+3 10 0.343782
+3 18 0.934498
+3 27 0.222679
+3 32 0.284368
+3 35 0.026782
+3 37 0.003311
+3 44 0.170563
+3 50 0.357325
+3 51 0.233821
+3 53 0.747417
+3 59 0.112209
+3 62 0.983658
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+3 89 0.311452
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+4 18 0.633350
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+5 5 0.225498
+5 6 0.668385
+5 11 0.930229
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+5 56 0.756580
+5 58 0.892897
+5 74 0.565059
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+5 82 0.282778
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+5 92 0.603004
+5 96 0.119078
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+7 9 0.299776
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+7 18 0.802907
+7 20 0.495369
+7 22 0.512166
+7 38 0.283605
+7 48 0.494668
+7 52 0.228327
+7 55 0.510215
+7 63 0.477973
+7 68 0.062698
+7 71 0.928300
+7 78 0.676117
+7 79 0.260692
+7 83 0.032723
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+8 34 0.956409
+8 35 0.629297
+8 37 0.207158
+8 41 0.005092
+8 42 0.349534
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+8 73 0.734359
+8 75 0.400418
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+9 85 0.490606
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+9 92 0.618881
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+10 79 0.371381
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+11 43 0.042373
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diff --git a/fastlib/u/nvasil/sparse/sparse_matrix_unit.cc b/fastlib/u/nvasil/sparse/sparse_matrix_unit.cc
new file mode 100644
index 0000000000..265702af97
--- /dev/null
+++ b/fastlib/u/nvasil/sparse/sparse_matrix_unit.cc
@@ -0,0 +1,82 @@
+/*
+ * =====================================================================================
+ *
+ *       Filename:  sparse_matrix_unit.cc
+ *
+ *    Description:  
+ *
+ *        Version:  1.0
+ *        Created:  06/22/2007 09:35:38 AM EDT
+ *       Revision:  none
+ *       Compiler:  gcc
+ *
+ *         Author:  Nikolaos Vasiloglou (NV), nvasil@ieee.org
+ *        Company:  Georgia Tech Fastlab-ESP Lab
+ *
+ * =====================================================================================
+ */
+#include "fastlib/fastlib.h"
+#include "base/test.h"
+#include "u/nvasil/sparse/sparse_matrix.h"
+
+namespace sparse {
+template<typename T>
+class MatrixTest {
+ public:
+	void Init(){
+	  size_=100;
+		non_zero_=10;
+		matrix_.Init(100, 10);
+		for(index_t i=0; i<size_; i++) {
+		  for(index_t j=0; j<non_zero_; j++) {
+			  matrix_.set(i, j, float32(i*size_+j));
+			}
+		}
+		matrixfile_="sparse_matrix.txt";
+		xfile_="xfile.txt";
+		bfile_="bfile.txt";
+	};
+	void Destruct(){
+	  matrix_.Destruct();
+	}
+  void TestAccess(){
+	  for(index_t i=0; i<size_; i++) {
+		  for(index_t j=0; j<non_zero_; j++) {
+			  TEST_ASSERT(matrix_.get(i, j)==float32(i*size_+j));
+			}
+		}
+	}
+  
+  void TestConjugateGradient() {
+		matrix_.Destruct();
+		matrix_.Init(matrixfile_);
+		T *b=ReadVectorFromFile<T>(bfile_);
+		T *x=ReadVectorFromFile<T>(xfile_);
+	  T *xconjg=NewVector<T>(size_);	
+	  ConjugateGradient(matrix_, b,  xconjg);
+		for(index_t i=0; i<size_; i++) {
+		  TEST_DOUBLE_APPROX(xconjg[i], x[i], 0.0001);
+		}
+	}
+  void TestAll() {
+	  Init();
+		TestAccess();
+		Destruct();
+		Init();
+    TestConjugateGradient();
+		Destruct();
+	}	
+ private:
+	Matrix<T>  matrix_;
+	index_t size_;
+	index_t non_zero_;
+  string matrixfile_;
+  string xfile_;
+  string bfile_;	
+};
+};
+
+int main(int argc, char *argv[]) {
+	sparse::MatrixTest<float32> matrix_test;
+	matrix_test.TestAll();
+}
diff --git a/fastlib/u/nvasil/sparse/xfile.txt b/fastlib/u/nvasil/sparse/xfile.txt
new file mode 100644
index 0000000000..79c2a06382
--- /dev/null
+++ b/fastlib/u/nvasil/sparse/xfile.txt
@@ -0,0 +1,101 @@
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