diff --git a/Eigen/Core b/Eigen/Core
index 864bde551..080511fc9 100644
--- a/Eigen/Core
+++ b/Eigen/Core
@@ -200,6 +200,12 @@ using std::ptrdiff_t;
   #include "src/Core/arch/GPU/MathFunctions.h"
 #endif
 
+#if defined EIGEN_VECTORIZE_SYCL
+  #include "src/Core/arch/SYCL/InteropHeaders.h"
+  #include "src/Core/arch/SYCL/PacketMath.h"
+  #include "src/Core/arch/SYCL/MathFunctions.h"
+  #include "src/Core/arch/SYCL/TypeCasting.h"
+#endif
 #include "src/Core/arch/Default/Settings.h"
 
 #include "src/Core/functors/TernaryFunctors.h"
diff --git a/Eigen/src/Core/arch/GPU/Half.h b/Eigen/src/Core/arch/GPU/Half.h
index ab9d27591..aca56fa72 100644
--- a/Eigen/src/Core/arch/GPU/Half.h
+++ b/Eigen/src/Core/arch/GPU/Half.h
@@ -83,7 +83,11 @@ struct __half_raw {
  #if defined(EIGEN_CUDACC_VER) && EIGEN_CUDACC_VER < 90000
 // In CUDA < 9.0, __half is the equivalent of CUDA 9's __half_raw
  typedef __half __half_raw;
- #endif
+ #endif // defined(EIGEN_HAS_CUDA_FP16)
+
+#elif defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__)
+typedef cl::sycl::half __half_raw;
+
 #endif
 
 EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half_raw raw_uint16_to_half(unsigned short x);
@@ -200,6 +204,7 @@ struct half : public half_impl::half_base {
     x = other.x;
     return *this;
   }
+
 };
 
 } // end namespace Eigen
diff --git a/Eigen/src/Core/util/Macros.h b/Eigen/src/Core/util/Macros.h
index f59b93608..bcdede61e 100644
--- a/Eigen/src/Core/util/Macros.h
+++ b/Eigen/src/Core/util/Macros.h
@@ -571,20 +571,19 @@
 
 // Does the compiler fully support const expressions? (as in c++14)
 #ifndef EIGEN_HAS_CONSTEXPR
-
   #if defined(EIGEN_CUDACC)
   // Const expressions are supported provided that c++11 is enabled and we're using either clang or nvcc 7.5 or above
-  #if EIGEN_MAX_CPP_VER>=14 && (__cplusplus > 199711L && (EIGEN_COMP_CLANG || EIGEN_CUDACC_VER >= 70500))
-    #define EIGEN_HAS_CONSTEXPR 1
-  #endif
+    #if EIGEN_MAX_CPP_VER>=14 && (__cplusplus > 199711L && (EIGEN_COMP_CLANG || EIGEN_CUDACC_VER >= 70500))
+      #define EIGEN_HAS_CONSTEXPR 1
+    #endif
   #elif EIGEN_MAX_CPP_VER>=14 && (__has_feature(cxx_relaxed_constexpr) || (defined(__cplusplus) && __cplusplus >= 201402L) || \
     (EIGEN_GNUC_AT_LEAST(4,8) && (__cplusplus > 199711L)) || \
     (EIGEN_COMP_CLANG >= 306 && (__cplusplus > 199711L)))
-  #define EIGEN_HAS_CONSTEXPR 1
+    #define EIGEN_HAS_CONSTEXPR 1
   #endif
 
   #ifndef EIGEN_HAS_CONSTEXPR
-  #define EIGEN_HAS_CONSTEXPR 0
+    #define EIGEN_HAS_CONSTEXPR 0
   #endif
 
 #endif // EIGEN_HAS_CONSTEXPR
@@ -643,9 +642,12 @@
     #ifdef __CUDACC_RELAXED_CONSTEXPR__
       #define EIGEN_CONSTEXPR_ARE_DEVICE_FUNC
     #endif
-  #elif defined(__clang__) && defined(__CUDA__)
-    // clang++ always considers constexpr functions as implicitly __host__ __device__
-    #define EIGEN_CONSTEXPR_ARE_DEVICE_FUNC
+    // See bug 1580: clang/CUDA fails to make the following calls
+    // to constexpr bool std::equal_to::operator() even when
+    // EIGEN_CONSTEXPR_ARE_DEVICE_FUNC is defined in c++14 only.
+    // #elif defined(__clang__) && defined(__CUDA__) && EIGEN_HAS_CONSTEXPR == 1
+    //   // clang++ always considers constexpr functions as implicitly __host__ __device__
+    //   #define EIGEN_CONSTEXPR_ARE_DEVICE_FUNC
   #endif
 #endif
 
@@ -1076,11 +1078,13 @@ namespace Eigen {
 #   endif
 #endif
 
-#ifdef EIGEN_HAS_VARIADIC_TEMPLATES
+#if EIGEN_HAS_VARIADIC_TEMPLATES
 // The all function is used to enable a variadic version of eigen_assert which can take a parameter pack as its input.
 namespace Eigen {
 namespace internal {
-bool all(){ return true; }
+
+inline bool all(){ return true; }
+
 template<typename T, typename ...Ts>
 bool all(T t, Ts ... ts){ return t && all(ts...); }
 
@@ -1088,5 +1092,15 @@ bool all(T t, Ts ... ts){ return t && all(ts...); }
 }
 #endif
 
+// Wrapping #pragma unroll in a macro since it is required for SYCL
+#if defined(__SYCL_DEVICE_ONLY__)
+  #if defined(_MSC_VER)
+    #define EIGEN_UNROLL_LOOP __pragma(unroll)
+  #else
+    #define EIGEN_UNROLL_LOOP _Pragma("unroll")
+  #endif
+#else
+  #define EIGEN_UNROLL_LOOP
+#endif
 
 #endif // EIGEN_MACROS_H
diff --git a/Eigen/src/Core/util/Meta.h b/Eigen/src/Core/util/Meta.h
index 658cfa9eb..f27b8e85d 100755
--- a/Eigen/src/Core/util/Meta.h
+++ b/Eigen/src/Core/util/Meta.h
@@ -569,7 +569,7 @@ template<typename T, typename U> struct scalar_product_traits
 } // end namespace internal
 
 namespace numext {
-  
+
 #if defined(EIGEN_GPU_COMPILE_PHASE)
 template<typename T> EIGEN_DEVICE_FUNC   void swap(T &a, T &b) { T tmp = b; b = a; a = tmp; }
 #else
diff --git a/test/dynalloc.cpp b/test/dynalloc.cpp
index ceecd76e3..1c74866ba 100644
--- a/test/dynalloc.cpp
+++ b/test/dynalloc.cpp
@@ -15,6 +15,7 @@
 #define ALIGNMENT 1
 #endif
 
+typedef Matrix<float,16,1> Vector16f;
 typedef Matrix<float,8,1> Vector8f;
 
 void check_handmade_aligned_malloc()
@@ -70,7 +71,7 @@ struct MyStruct
 {
   EIGEN_MAKE_ALIGNED_OPERATOR_NEW
   char dummychar;
-  Vector8f avec;
+  Vector16f avec;
 };
 
 class MyClassA
@@ -78,7 +79,7 @@ class MyClassA
   public:
     EIGEN_MAKE_ALIGNED_OPERATOR_NEW
     char dummychar;
-    Vector8f avec;
+    Vector16f avec;
 };
 
 template<typename T> void check_dynaligned()
@@ -145,6 +146,7 @@ EIGEN_DECLARE_TEST(dynalloc)
     CALL_SUBTEST(check_dynaligned<Vector4d>() );
     CALL_SUBTEST(check_dynaligned<Vector4i>() );
     CALL_SUBTEST(check_dynaligned<Vector8f>() );
+    CALL_SUBTEST(check_dynaligned<Vector16f>() );
   }
 
   {
diff --git a/test/main.h b/test/main.h
index 5d64bc736..de8a4865f 100644
--- a/test/main.h
+++ b/test/main.h
@@ -193,7 +193,7 @@ namespace Eigen
 
 #define EIGEN_DEFAULT_IO_FORMAT IOFormat(4, 0, "  ", "\n", "", "", "", "")
 
-#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__)
+#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__) && !defined(__SYCL_DEVICE_ONLY__)
   #define EIGEN_EXCEPTIONS
 #endif
 
@@ -272,7 +272,7 @@ namespace Eigen
       }
     #endif //EIGEN_EXCEPTIONS
 
-  #elif !defined(__CUDACC__) && !defined(__HIPCC__)// EIGEN_DEBUG_ASSERTS
+  #elif !defined(__CUDACC__) && !defined(__HIPCC__) && !defined(__SYCL_DEVICE_ONLY__) // EIGEN_DEBUG_ASSERTS
     // see bug 89. The copy_bool here is working around a bug in gcc <= 4.3
     #define eigen_assert(a) \
       if( (!Eigen::internal::copy_bool(a)) && (!no_more_assert) )\
@@ -329,7 +329,7 @@ namespace Eigen
     std::cout << "Can't VERIFY_RAISES_STATIC_ASSERT( " #a " ) with exceptions disabled\n";
 #endif
     
-  #if !defined(__CUDACC__) && !defined(__HIPCC__)
+  #if !defined(__CUDACC__) && !defined(__HIPCC__) && !defined(__SYCL_DEVICE_ONLY__)
   #define EIGEN_USE_CUSTOM_ASSERT
   #endif
 
@@ -845,4 +845,4 @@ int main(int argc, char *argv[])
 #ifdef _MSC_VER
   // 4503 - decorated name length exceeded, name was truncated
   #pragma warning( disable : 4503)
-#endif
+#endif
\ No newline at end of file
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
index 97f90f638..ab3731952 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
@@ -538,8 +538,8 @@ class TensorBase<Derived, ReadOnlyAccessors>
     // Fourier transforms
     template <int FFTDataType, int FFTDirection, typename FFT> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     const TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection>
-    fft(const FFT& fft) const {
-      return TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection>(derived(), fft);
+    fft(const FFT& dims) const {
+      return TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection>(derived(), dims);
     }
 
     // Scan.
@@ -723,8 +723,8 @@ class TensorBase<Derived, ReadOnlyAccessors>
 
     template <typename Broadcast> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     const TensorBroadcastingOp<const Broadcast, const Derived>
-    broadcast(const Broadcast& broadcast) const {
-      return TensorBroadcastingOp<const Broadcast, const Derived>(derived(), broadcast);
+    broadcast(const Broadcast& bcast) const {
+      return TensorBroadcastingOp<const Broadcast, const Derived>(derived(), bcast);
     }
 
     template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -832,8 +832,8 @@ class TensorBase<Derived, ReadOnlyAccessors>
     }
     template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     const TensorShufflingOp<const Shuffle, const Derived>
-    shuffle(const Shuffle& shuffle) const {
-      return TensorShufflingOp<const Shuffle, const Derived>(derived(), shuffle);
+    shuffle(const Shuffle& shfl) const {
+      return TensorShufflingOp<const Shuffle, const Derived>(derived(), shfl);
     }
     template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     const TensorStridingOp<const Strides, const Derived>
@@ -1030,13 +1030,13 @@ class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> {
 
     template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     const TensorShufflingOp<const Shuffle, const Derived>
-    shuffle(const Shuffle& shuffle) const {
-      return TensorShufflingOp<const Shuffle, const Derived>(derived(), shuffle);
+    shuffle(const Shuffle& shfl) const {
+      return TensorShufflingOp<const Shuffle, const Derived>(derived(), shfl);
     }
     template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     TensorShufflingOp<const Shuffle, Derived>
-    shuffle(const Shuffle& shuffle) {
-      return TensorShufflingOp<const Shuffle, Derived>(derived(), shuffle);
+    shuffle(const Shuffle& shfl) {
+      return TensorShufflingOp<const Shuffle, Derived>(derived(), shfl);
     }
 
     template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -1052,8 +1052,8 @@ class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> {
 
     // Select the device on which to evaluate the expression.
     template <typename DeviceType>
-    TensorDevice<Derived, DeviceType> device(const DeviceType& device) {
-      return TensorDevice<Derived, DeviceType>(device, derived());
+    TensorDevice<Derived, DeviceType> device(const DeviceType& dev) {
+      return TensorDevice<Derived, DeviceType>(dev, derived());
     }
 
  protected:
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h
index 1db8d6124..877603421 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h
@@ -89,7 +89,7 @@ EIGEN_STRONG_INLINE void MergeResourceRequirements(
   // policy if block shapes/sizes conflict).
   *block_shape = resources[0].block_shape;
   *block_total_size = resources[0].block_total_size;
-  for (int i = 1; i < resources.size(); ++i) {
+  for (std::vector<TensorOpResourceRequirements>::size_type i = 1; i < resources.size(); ++i) {
     if (resources[i].block_shape == TensorBlockShapeType::kSkewedInnerDims &&
         *block_shape != TensorBlockShapeType::kSkewedInnerDims) {
       *block_shape = TensorBlockShapeType::kSkewedInnerDims;
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h b/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
index e1649fb47..e604456e8 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
@@ -274,8 +274,8 @@ struct TensorContractionEvaluatorBase
                           op.lhsExpression(), op.rhsExpression()), device),
     m_rightImpl(choose(Cond<static_cast<int>(Layout) == static_cast<int>(ColMajor)>(),
                           op.rhsExpression(), op.lhsExpression()), device),
-        m_output_kernel(op.outputKernel()),
         m_device(device),
+        m_output_kernel(op.outputKernel()),
         m_result(NULL) {
     EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) ==
          static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout)),
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h b/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
index 0d3ca966c..a07e32db0 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
@@ -527,8 +527,8 @@ struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelAr
       Scalar* local = (Scalar*)m_device.allocate(kernel_sz);
       typedef TensorEvalToOp<const KernelArgType> EvalTo;
       EvalTo evalToTmp(local, m_kernelArg);
-      const bool PacketAccess = internal::IsVectorizable<Device, KernelArgType>::value;
-      internal::TensorExecutor<const EvalTo, Device, PacketAccess>::run(evalToTmp, m_device);
+      const bool Vectorize = internal::IsVectorizable<Device, KernelArgType>::value;
+      internal::TensorExecutor<const EvalTo, Device, Vectorize>::run(evalToTmp, m_device);
 
       m_kernel = local;
       m_local_kernel = true;
@@ -786,7 +786,7 @@ struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelAr
   };
 
   EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const GpuDevice& device)
-      : m_inputImpl(op.inputExpression(), device), m_kernelArg(op.kernelExpression()), m_kernelImpl(op.kernelExpression(), device), m_indices(op.indices()), m_buf(NULL), m_kernel(NULL), m_local_kernel(false), m_device(device)
+      : m_inputImpl(op.inputExpression(), device), m_kernelImpl(op.kernelExpression(), device), m_kernelArg(op.kernelExpression()), m_indices(op.indices()), m_buf(NULL), m_kernel(NULL), m_local_kernel(false), m_device(device)
   {
     EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<InputArgType, GpuDevice>::Layout) == static_cast<int>(TensorEvaluator<KernelArgType, GpuDevice>::Layout)), YOU_MADE_A_PROGRAMMING_MISTAKE);
 
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h b/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h
index 5a16ebe50..cc134228a 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h
@@ -91,18 +91,31 @@ static EIGEN_STRONG_INLINE void wait_until_ready(SyncType* n) {
   }
 }
 
+// An abstract interface to a device specific memory allocator.
+class Allocator {
+ public:
+  virtual ~Allocator() {}
+  EIGEN_DEVICE_FUNC virtual void* allocate(size_t num_bytes) const = 0;
+  EIGEN_DEVICE_FUNC virtual void deallocate(void* buffer) const = 0;
+};
 
 // Build a thread pool device on top the an existing pool of threads.
 struct ThreadPoolDevice {
   // The ownership of the thread pool remains with the caller.
-  ThreadPoolDevice(ThreadPoolInterface* pool, int num_cores) : pool_(pool), num_threads_(num_cores) { }
+  ThreadPoolDevice(ThreadPoolInterface* pool, int num_cores, Allocator* allocator = nullptr)
+      : pool_(pool), num_threads_(num_cores), allocator_(allocator) { }
 
   EIGEN_STRONG_INLINE void* allocate(size_t num_bytes) const {
-    return internal::aligned_malloc(num_bytes);
+    return allocator_ ? allocator_->allocate(num_bytes)
+        : internal::aligned_malloc(num_bytes);
   }
 
   EIGEN_STRONG_INLINE void deallocate(void* buffer) const {
-    internal::aligned_free(buffer);
+    if (allocator_) {
+      allocator_->deallocate(buffer);
+    } else {
+      internal::aligned_free(buffer);
+    }
   }
 
     EIGEN_STRONG_INLINE void* allocate_temp(size_t num_bytes) const {
@@ -275,9 +288,13 @@ struct ThreadPoolDevice {
   // Thread pool accessor.
   ThreadPoolInterface* getPool() const { return pool_; }
 
+  // Allocator accessor.
+  Allocator* allocator() const { return allocator_; }
+
  private:
   ThreadPoolInterface* pool_;
   int num_threads_;
+  Allocator* allocator_;
 };
 
 
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h b/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h
index 8f7a81575..028902fea 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h
@@ -126,7 +126,7 @@ struct TensorEvaluator
   }
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void getResourceRequirements(
-      std::vector<internal::TensorOpResourceRequirements>* resources) const {}
+      std::vector<internal::TensorOpResourceRequirements>*) const {}
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void block(TensorBlock* block) const {
     assert(m_data != NULL);
@@ -255,7 +255,7 @@ struct TensorEvaluator<const Derived, Device>
   }
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void getResourceRequirements(
-      std::vector<internal::TensorOpResourceRequirements>* resources) const {}
+      std::vector<internal::TensorOpResourceRequirements>*) const {}
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void block(TensorBlock* block) const {
     assert(m_data != NULL);
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
index a456f308b..2778bf5ec 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
@@ -124,8 +124,8 @@ struct TensorEvaluator<const TensorForcedEvalOp<ArgType>, Device>
     }
     typedef TensorEvalToOp< const typename internal::remove_const<ArgType>::type > EvalTo;
     EvalTo evalToTmp(m_buffer, m_op);
-    const bool PacketAccess = internal::IsVectorizable<Device, const ArgType>::value;
-    internal::TensorExecutor<const EvalTo, typename internal::remove_const<Device>::type, PacketAccess>::run(evalToTmp, m_device);
+    const bool Vectorize = internal::IsVectorizable<Device, const ArgType>::value;
+    internal::TensorExecutor<const EvalTo, typename internal::remove_const<Device>::type, Vectorize>::run(evalToTmp, m_device);
     return true;
   }
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
index 8ed1796df..0dd524a30 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
@@ -21,6 +21,7 @@ namespace Eigen {
 template<typename T> struct MakePointer {
   typedef T* Type;
   typedef T& RefType;
+  typedef T ScalarType;
 };
 
 namespace internal{
@@ -97,7 +98,7 @@ template<typename XprType> class TensorForcedEvalOp;
 template<typename ExpressionType, typename DeviceType> class TensorDevice;
 template<typename Derived, typename Device> struct TensorEvaluator;
 
-class NoOpOutputKernel;
+struct NoOpOutputKernel;
 
 struct DefaultDevice;
 struct ThreadPoolDevice;
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h b/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
index fbe69aabc..98f125408 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
@@ -61,8 +61,8 @@ class TensorShufflingOp : public TensorBase<TensorShufflingOp<Shuffle, XprType>
   typedef typename Eigen::internal::traits<TensorShufflingOp>::StorageKind StorageKind;
   typedef typename Eigen::internal::traits<TensorShufflingOp>::Index Index;
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorShufflingOp(const XprType& expr, const Shuffle& shuffle)
-      : m_xpr(expr), m_shuffle(shuffle) {}
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorShufflingOp(const XprType& expr, const Shuffle& shfl)
+      : m_xpr(expr), m_shuffle(shfl) {}
 
     EIGEN_DEVICE_FUNC
     const Shuffle& shufflePermutation() const { return m_shuffle; }
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorTrace.h b/unsupported/Eigen/CXX11/src/Tensor/TensorTrace.h
index c8b2fad1e..ea53bb04b 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorTrace.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorTrace.h
@@ -273,11 +273,11 @@ struct TensorEvaluator<const TensorTraceOp<Dims, ArgType>, Device>
 
   Dimensions m_dimensions;
   TensorEvaluator<ArgType, Device> m_impl;
+  // Initialize the size of the trace dimension
+  Index m_traceDim;
   const Device& m_device;
   array<bool, NumInputDims> m_reduced;
   array<Index, NumReducedDims> m_reducedDims;
-  // Initialize the size of the trace dimension
-  Index m_traceDim;
   array<Index, NumOutputDims> m_outputStrides;
   array<Index, NumReducedDims> m_reducedStrides;
   array<Index, NumOutputDims> m_preservedStrides;
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h b/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
index 006b37921..0a394c88d 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
@@ -59,6 +59,7 @@ struct traits<Tensor<Scalar_, NumIndices_, Options_, IndexType_> >
   template <typename T> struct MakePointer {
     typedef T* Type;
     typedef T& RefType;
+    typedef T ScalarType;
 
   };
   typedef typename MakePointer<Scalar>::Type PointerType;
@@ -80,6 +81,7 @@ struct traits<TensorFixedSize<Scalar_, Dimensions, Options_, IndexType_> >
   template <typename T> struct MakePointer {
     typedef T* Type;
     typedef T& RefType;
+    typedef T ScalarType;
 
   };
   typedef typename MakePointer<Scalar>::Type PointerType;
@@ -105,6 +107,8 @@ struct traits<TensorMap<PlainObjectType, Options_, MakePointer_> >
     typedef MakePointer_<T> MakePointerT;
     typedef typename MakePointerT::Type Type;
     typedef typename MakePointerT::RefType RefType;
+    typedef typename MakePointerT::ScalarType ScalarType;
+
 
   };
   typedef typename MakePointer<Scalar>::Type PointerType;
diff --git a/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h b/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
index 279fe5cd3..13d959df4 100755
--- a/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
+++ b/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
@@ -684,10 +684,15 @@ template<typename DerType> struct NumTraits<AutoDiffScalar<DerType> >
 }
 
 namespace std {
+
 template <typename T>
 class numeric_limits<Eigen::AutoDiffScalar<T> >
   : public numeric_limits<typename T::Scalar> {};
 
+template <typename T>
+class numeric_limits<Eigen::AutoDiffScalar<T&> >
+  : public numeric_limits<typename T::Scalar> {};
+
 }  // namespace std
 
 #endif // EIGEN_AUTODIFF_SCALAR_H
diff --git a/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h b/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h
index dbcc9d8ac..5784cbc86 100644
--- a/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h
+++ b/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h
@@ -193,6 +193,8 @@ struct lgamma_impl<float> {
 #if !defined(EIGEN_GPU_COMPILE_PHASE) && (defined(_BSD_SOURCE) || defined(_SVID_SOURCE)) && !defined(__APPLE__) 
     int dummy;
     return ::lgammaf_r(x, &dummy);
+#elif defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__)
+    return cl::sycl::lgamma(x);
 #else
     return ::lgammaf(x);
 #endif
@@ -206,6 +208,8 @@ struct lgamma_impl<double> {
 #if !defined(EIGEN_GPU_COMPILE_PHASE) && (defined(_BSD_SOURCE) || defined(_SVID_SOURCE)) && !defined(__APPLE__) 
     int dummy;
     return ::lgamma_r(x, &dummy);
+#elif defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__)
+    return cl::sycl::lgamma(x);
 #else
     return ::lgamma(x);
 #endif
@@ -423,13 +427,25 @@ struct erf_retval {
 template <>
 struct erf_impl<float> {
   EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE float run(float x) { return ::erff(x); }
+  static EIGEN_STRONG_INLINE float run(float x) {
+#if defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__)
+    return cl::sycl::erf(x);
+#else
+    return ::erff(x);
+#endif
+  }
 };
 
 template <>
 struct erf_impl<double> {
   EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE double run(double x) { return ::erf(x); }
+  static EIGEN_STRONG_INLINE double run(double x) {
+#if defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__)
+    return cl::sycl::erf(x);
+#else
+    return ::erf(x);
+#endif
+  }
 };
 #endif  // EIGEN_HAS_C99_MATH
 
@@ -456,13 +472,25 @@ struct erfc_retval {
 template <>
 struct erfc_impl<float> {
   EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE float run(const float x) { return ::erfcf(x); }
+  static EIGEN_STRONG_INLINE float run(const float x) {
+#if defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__)
+    return cl::sycl::erfc(x);
+#else
+    return ::erfcf(x);
+#endif
+  }
 };
 
 template <>
 struct erfc_impl<double> {
   EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE double run(const double x) { return ::erfc(x); }
+  static EIGEN_STRONG_INLINE double run(const double x) {
+#if defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__)
+    return cl::sycl::erfc(x);
+#else
+    return ::erfc(x);
+#endif
+  }
 };
 #endif  // EIGEN_HAS_C99_MATH
 
diff --git a/unsupported/test/cxx11_tensor_concatenation.cpp b/unsupported/test/cxx11_tensor_concatenation.cpp
index 9189a609b..f53515b4e 100644
--- a/unsupported/test/cxx11_tensor_concatenation.cpp
+++ b/unsupported/test/cxx11_tensor_concatenation.cpp
@@ -50,7 +50,13 @@ static void test_static_dimension_failure()
       .reshape(Tensor<int, 3>::Dimensions(2, 3, 1))
       .concatenate(right, 0);
   Tensor<int, 2, DataLayout> alternative = left
-      .concatenate(right.reshape(Tensor<int, 2>::Dimensions{{{2, 3}}}), 0);
+   // Clang compiler break with {{{}}} with an ambigous error on copy constructor
+  // the variadic DSize constructor added for #ifndef EIGEN_EMULATE_CXX11_META_H.
+  // Solution:
+  // either the code should change to 
+  //  Tensor<int, 2>::Dimensions{{2, 3}}
+  // or Tensor<int, 2>::Dimensions{Tensor<int, 2>::Dimensions{{2, 3}}}
+      .concatenate(right.reshape(Tensor<int, 2>::Dimensions{{2, 3}}), 0);
 }
 
 template<int DataLayout>
diff --git a/unsupported/test/cxx11_tensor_thread_pool.cpp b/unsupported/test/cxx11_tensor_thread_pool.cpp
index 20a197f2b..5c3aae482 100644
--- a/unsupported/test/cxx11_tensor_thread_pool.cpp
+++ b/unsupported/test/cxx11_tensor_thread_pool.cpp
@@ -16,6 +16,25 @@
 
 using Eigen::Tensor;
 
+class TestAllocator : public Allocator {
+ public:
+  ~TestAllocator() override {}
+  EIGEN_DEVICE_FUNC void* allocate(size_t num_bytes) const override {
+    const_cast<TestAllocator*>(this)->alloc_count_++;
+    return internal::aligned_malloc(num_bytes);
+  }
+  EIGEN_DEVICE_FUNC void deallocate(void* buffer) const override {
+    const_cast<TestAllocator*>(this)->dealloc_count_++;
+    internal::aligned_free(buffer);
+  }
+
+  int alloc_count() const { return alloc_count_; }
+  int dealloc_count() const { return dealloc_count_; }
+
+ private:
+  int alloc_count_ = 0;
+  int dealloc_count_ = 0;
+};
 
 void test_multithread_elementwise()
 {
@@ -374,14 +393,14 @@ void test_multithread_random()
 }
 
 template<int DataLayout>
-void test_multithread_shuffle()
+void test_multithread_shuffle(Allocator* allocator)
 {
   Tensor<float, 4, DataLayout> tensor(17,5,7,11);
   tensor.setRandom();
 
   const int num_threads = internal::random<int>(2, 11);
   ThreadPool threads(num_threads);
-  Eigen::ThreadPoolDevice device(&threads, num_threads);
+  Eigen::ThreadPoolDevice device(&threads, num_threads, allocator);
 
   Tensor<float, 4, DataLayout> shuffle(7,5,11,17);
   array<ptrdiff_t, 4> shuffles = {{2,1,3,0}};
@@ -398,6 +417,21 @@ void test_multithread_shuffle()
   }
 }
 
+void test_threadpool_allocate(TestAllocator* allocator)
+{
+  const int num_threads = internal::random<int>(2, 11);
+  const int num_allocs = internal::random<int>(2, 11);
+  ThreadPool threads(num_threads);
+  Eigen::ThreadPoolDevice device(&threads, num_threads, allocator);
+
+  for (int a = 0; a < num_allocs; ++a) {
+    void* ptr = device.allocate(512);
+    device.deallocate(ptr);
+  }
+  VERIFY(allocator != nullptr);
+  VERIFY_IS_EQUAL(allocator->alloc_count(), num_allocs);
+  VERIFY_IS_EQUAL(allocator->dealloc_count(), num_allocs);
+}
 
 EIGEN_DECLARE_TEST(cxx11_tensor_thread_pool)
 {
@@ -424,6 +458,9 @@ EIGEN_DECLARE_TEST(cxx11_tensor_thread_pool)
 
   CALL_SUBTEST_6(test_memcpy());
   CALL_SUBTEST_6(test_multithread_random());
-  CALL_SUBTEST_6(test_multithread_shuffle<ColMajor>());
-  CALL_SUBTEST_6(test_multithread_shuffle<RowMajor>());
+
+  TestAllocator test_allocator;
+  CALL_SUBTEST_6(test_multithread_shuffle<ColMajor>(nullptr));
+  CALL_SUBTEST_6(test_multithread_shuffle<RowMajor>(&test_allocator));
+  CALL_SUBTEST_6(test_threadpool_allocate(&test_allocator));
 }
diff --git a/unsupported/test/cxx11_tensor_trace.cpp b/unsupported/test/cxx11_tensor_trace.cpp
index 1579bc1eb..0cb23060e 100644
--- a/unsupported/test/cxx11_tensor_trace.cpp
+++ b/unsupported/test/cxx11_tensor_trace.cpp
@@ -37,7 +37,7 @@ static void test_all_dimensions_trace() {
   VERIFY_IS_EQUAL(result1(), sum);
 
   Tensor<float, 5, DataLayout> tensor2(7, 7, 7, 7, 7);
-  array<ptrdiff_t, 5> dims({{2, 1, 0, 3, 4}});
+  array<ptrdiff_t, 5> dims = { { 2, 1, 0, 3, 4 } };
   Tensor<float, 0, DataLayout> result2 = tensor2.trace(dims);
   VERIFY_IS_EQUAL(result2.rank(), 0);
   sum = 0.0f;
@@ -52,7 +52,7 @@ template <int DataLayout>
 static void test_simple_trace() {
   Tensor<float, 3, DataLayout> tensor1(3, 5, 3);
   tensor1.setRandom();
-  array<ptrdiff_t, 2> dims1({{0, 2}});
+  array<ptrdiff_t, 2> dims1 = { { 0, 2 } };
   Tensor<float, 1, DataLayout> result1 = tensor1.trace(dims1);
   VERIFY_IS_EQUAL(result1.rank(), 1);
   VERIFY_IS_EQUAL(result1.dimension(0), 5);
@@ -67,7 +67,7 @@ static void test_simple_trace() {
 
   Tensor<float, 4, DataLayout> tensor2(5, 5, 7, 7);
   tensor2.setRandom();
-  array<ptrdiff_t, 2> dims2({{2, 3}});
+  array<ptrdiff_t, 2> dims2 = { { 2, 3 } };
   Tensor<float, 2, DataLayout> result2 = tensor2.trace(dims2);
   VERIFY_IS_EQUAL(result2.rank(), 2);
   VERIFY_IS_EQUAL(result2.dimension(0), 5);
@@ -82,7 +82,7 @@ static void test_simple_trace() {
     }
   }
 
-  array<ptrdiff_t, 2> dims3({{1, 0}});
+  array<ptrdiff_t, 2> dims3 = { { 1, 0 } };
   Tensor<float, 2, DataLayout> result3 = tensor2.trace(dims3);
   VERIFY_IS_EQUAL(result3.rank(), 2);
   VERIFY_IS_EQUAL(result3.dimension(0), 7);
@@ -99,7 +99,7 @@ static void test_simple_trace() {
 
   Tensor<float, 5, DataLayout> tensor3(3, 7, 3, 7, 3);
   tensor3.setRandom();
-  array<ptrdiff_t, 3> dims4({{0, 2, 4}});
+  array<ptrdiff_t, 3> dims4 = { { 0, 2, 4 } };
   Tensor<float, 2, DataLayout> result4 = tensor3.trace(dims4);
   VERIFY_IS_EQUAL(result4.rank(), 2);
   VERIFY_IS_EQUAL(result4.dimension(0), 7);
@@ -116,7 +116,7 @@ static void test_simple_trace() {
 
   Tensor<float, 5, DataLayout> tensor4(3, 7, 4, 7, 5);
   tensor4.setRandom();
-  array<ptrdiff_t, 2> dims5({{1, 3}});
+  array<ptrdiff_t, 2> dims5 = { { 1, 3 } };
   Tensor<float, 3, DataLayout> result5 = tensor4.trace(dims5);
   VERIFY_IS_EQUAL(result5.rank(), 3);
   VERIFY_IS_EQUAL(result5.dimension(0), 3);
@@ -140,7 +140,7 @@ template<int DataLayout>
 static void test_trace_in_expr() {
   Tensor<float, 4, DataLayout> tensor(2, 3, 5, 3);
   tensor.setRandom();
-  array<ptrdiff_t, 2> dims({{1, 3}});
+  array<ptrdiff_t, 2> dims = { { 1, 3 } };
   Tensor<float, 2, DataLayout> result(2, 5);
   result = result.constant(1.0f) - tensor.trace(dims);
   VERIFY_IS_EQUAL(result.rank(), 2);
@@ -168,4 +168,4 @@ EIGEN_DECLARE_TEST(cxx11_tensor_trace) {
   CALL_SUBTEST(test_simple_trace<RowMajor>());
   CALL_SUBTEST(test_trace_in_expr<ColMajor>());
   CALL_SUBTEST(test_trace_in_expr<RowMajor>());
-}
+}
\ No newline at end of file