diff --git a/base/export.jl b/base/export.jl
index 8e2279ddf05cd..060ef03779ade 100644
--- a/base/export.jl
+++ b/base/export.jl
@@ -634,6 +634,7 @@ export
     diagmm!,
     dot,
     eig,
+    eigvals,
     expm,
     eye,
     factors,
@@ -661,7 +662,6 @@ export
     randsym,
     rank,
     rref,
-    sdd,
     solve,
     svd,
     svdvals,
diff --git a/base/linalg.jl b/base/linalg.jl
index 771e4b3263495..8ee32e2b0e0ae 100644
--- a/base/linalg.jl
+++ b/base/linalg.jl
@@ -314,7 +314,9 @@ diag(A::AbstractVector) = error("Perhaps you meant to use diagm().")
 #diagm{T}(v::Union(AbstractVector{T},AbstractMatrix{T}))
 
 function norm(x::AbstractVector, p::Number)
-    if p == Inf
+    if length(x) == 0
+        return 0.0
+    elseif p == Inf
         return max(abs(x))
     elseif p == -Inf
         return min(abs(x))
@@ -326,14 +328,17 @@ end
 norm(x::AbstractVector) = sqrt(real(dot(x,x)))
 
 function norm(A::AbstractMatrix, p)
-    if size(A,1) == 1 || size(A,2) == 1
+    m, n = size(A)
+    if m == 0 || n == 0
+        return 0.0
+    elseif m == 1 || n == 1
         return norm(reshape(A, numel(A)), p)
     elseif p == 1
         return max(sum(abs(A),1))
     elseif p == 2
         return max(svd(A)[2])
     elseif p == Inf
-        max(sum(abs(A),2))
+        return max(sum(abs(A),2))
     elseif p == "fro"
         return sqrt(sum(diag(A'*A)))
     else
@@ -344,6 +349,8 @@ end
 norm(A::AbstractMatrix) = norm(A, 2)
 rank(A::AbstractMatrix, tol::Real) = sum(svdvals(A) .> tol)
 function rank(A::AbstractMatrix)
+    m,n = size(A)
+    if m == 0 || n == 0; return 0; end
     sv = svdvals(A)
     sum(sv .> max(size(A,1),size(A,2))*eps(sv[1]))
 end
diff --git a/base/linalg_lapack.jl b/base/linalg_lapack.jl
index 3c4c49a10ab0d..bd24799b655d5 100644
--- a/base/linalg_lapack.jl
+++ b/base/linalg_lapack.jl
@@ -1,41 +1,58 @@
 # linear algebra functions that use the Lapack module
 
-eig{T<:Integer}(x::StridedMatrix{T}) = eig(float64(x))
-
-function eig{T<:LapackScalar}(A::StridedMatrix{T})
-    if ishermitian(A) return Lapack.syev!('V','U',copy(A)) end
-                                        # Only compute right eigenvectors
-    if iscomplex(A) return Lapack.geev!('N','V',copy(A))[2:3] end
-    VL, WR, WI, VR = Lapack.geev!('N','V',copy(A))
-    if all(WI .== 0.) return WR, VR end
+function eig{T<:LapackScalar}(A::StridedMatrix{T}, vecs::Bool)
     n = size(A, 2)
-    evec = complex(zeros(T, n, n))
-    j = 1
-    while j <= n
-        if WI[j] == 0.0
-            evec[:,j] = VR[:,j]
-        else
-            evec[:,j]   = VR[:,j] + im*VR[:,j+1]
-            evec[:,j+1] = VR[:,j] - im*VR[:,j+1]
+    if n == 0; return vecs ? (zeros(T, 0), zeros(T, 0, 0)) : zeros(T, 0, 0); end
+
+    if ishermitian(A); return Lapack.syev!(vecs ? 'V' : 'N', 'U', copy(A)); end
+
+    if iscomplex(A)
+        W, VR = Lapack.geev!('N', vecs ? 'V' : 'N', copy(A))[2:3]
+        if vecs; return W, VR; end
+        return W
+    end
+
+    VL, WR, WI, VR = Lapack.geev!('N', vecs ? 'V' : 'N', copy(A))
+    if all(WI .== 0.) 
+        if vecs; return WR, VR; end
+        return WR
+    end
+    if vecs    
+        evec = complex(zeros(T, n, n))
+        j = 1
+        while j <= n
+            if WI[j] == 0.0
+                evec[:,j] = VR[:,j]
+            else
+                evec[:,j]   = VR[:,j] + im*VR[:,j+1]
+                evec[:,j+1] = VR[:,j] - im*VR[:,j+1]
+                j += 1
+            end
             j += 1
         end
-        j += 1
+        return complex(WR, WI), evec
     end
-    complex(WR, WI), evec
+    complex(WR, WI)
 end
 
-sdd!{T<:LapackScalar}(A::StridedMatrix{T},vecs::Char) = Lapack.gesdd!(vecs, copy(A))
-sdd{T<:LapackScalar}(A::StridedMatrix{T},vecs::Char) = sdd!(copy(A), vecs)
-sdd{T<:Real}(x::StridedMatrix{T},vecs::Char) = sdd(float64(x),vecs)
-sdd(A) = sdd(A, 'A')
+eig{T<:Integer}(x::StridedMatrix{T}, vecs::Bool) = eig(float64(x), vecs)
+eig(x::StridedMatrix) = eig(x, true)
+eigvals(x::StridedMatrix) = eig(x, false)
 
-function svd{T<:LapackScalar}(A::StridedMatrix{T},vecs::Bool)
-    Lapack.gesvd!(vecs ? 'A' : 'N', vecs ? 'A' : 'N', copy(A))
+function svd{T<:LapackScalar}(A::StridedMatrix{T},vecs::Bool,thin::Bool)
+    m,n = size(A)
+    if m == 0 || n == 0
+        if vecs; return (eye(m, thin ? n : m), zeros(0), eye(n,n)); end
+        return (zeros(T, 0, 0), zeros(T, 0), zeros(T, 0, 0))
+    end
+    if vecs; return Lapack.gesdd!(thin ? 'O' : 'A', copy(A)); end
+    Lapack.gesdd!('N', copy(A))
 end
 
-svd{T<:Integer}(x::StridedMatrix{T},vecs) = svd(float64(x),vecs)
-svd(A) = svd(A,true)
-svdvals(A) = svd(A,false)[2]
+svd{T<:Integer}(x::StridedMatrix{T},vecs,thin) = svd(float64(x),vecs,thin)
+svd(A::StridedMatrix) = svd(A,true,false)
+svd(A::StridedMatrix, thin::Bool) = svd(A,true,thin)
+svdvals(A) = svd(A,false,true)[2]
 
 function (\){T<:LapackScalar}(A::StridedMatrix{T}, B::StridedVecOrMat{T})
     Acopy = copy(A)