Google Git
Sign in
eigen/mirror/d57430dd73ab2f88aa5e45c370f6ab91103ff18a^!/.
commit
d57430dd73ab2f88aa5e45c370f6ab91103ff18a
[log]
author
Mehdi Goli <mehdi.goli@codeplay.com>
Tue Nov 08 17:08:02 2016 +0000
committer
Mehdi Goli <mehdi.goli@codeplay.com>
Tue Nov 08 17:08:02 2016 +0000
tree
d3d46d788686c38b1da1cb696807d51334829e5a
parent
dad177be010b45ba42425ab04af6dde6c479453b [diff]
Converting all sycl buffers to uninitialised device only buffers; adding memcpyHostToDevice and memcpyDeviceToHost on syclDevice; modifying all examples to obey the new rules; moving sycl queue creating to the device based on Benoit suggestion; removing the sycl specefic condition for returning m_result in TensorReduction.h according to Benoit suggestion.

diff --git a/cmake/EigenTesting.cmake b/cmake/EigenTesting.cmake
index 9ebd06a..047e964 100644
--- a/cmake/EigenTesting.cmake
+++ b/cmake/EigenTesting.cmake

@@ -1,23 +1,23 @@
 
 macro(ei_add_property prop value)
-  get_property(previous GLOBAL PROPERTY ${prop})  
+  get_property(previous GLOBAL PROPERTY ${prop})
   if ((NOT previous) OR (previous STREQUAL ""))
     set_property(GLOBAL PROPERTY ${prop} "${value}")
   else()
     set_property(GLOBAL PROPERTY ${prop} "${previous} ${value}")
-  endif()  
+  endif()
 endmacro(ei_add_property)
 
 #internal. See documentation of ei_add_test for details.
 macro(ei_add_test_internal testname testname_with_suffix)
   set(targetname ${testname_with_suffix})
-  
+
   if(EIGEN_ADD_TEST_FILENAME_EXTENSION)
     set(filename ${testname}.${EIGEN_ADD_TEST_FILENAME_EXTENSION})
   else()
     set(filename ${testname}.cpp)
   endif()
-  
+
   if(EIGEN_ADD_TEST_FILENAME_EXTENSION STREQUAL cu)
     if(EIGEN_TEST_CUDA_CLANG)
       set_source_files_properties(${filename} PROPERTIES LANGUAGE CXX)
@@ -42,7 +42,7 @@
   else()
     add_executable(${targetname} ${filename})
   endif()
-  
+
   if (targetname MATCHES "^eigen2_")
     add_dependencies(eigen2_buildtests ${targetname})
   else()
@@ -56,20 +56,20 @@
       ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_DEBUG_ASSERTS=1")
     endif(EIGEN_DEBUG_ASSERTS)
   endif(EIGEN_NO_ASSERTION_CHECKING)
-  
+
   ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_TEST_MAX_SIZE=${EIGEN_TEST_MAX_SIZE}")
 
   ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_TEST_FUNC=${testname}")
-  
+
   if(MSVC)
     ei_add_target_property(${targetname} COMPILE_FLAGS "/bigobj")
-  endif()  
+  endif()
 
   # let the user pass flags.
   if(${ARGC} GREATER 2)
     ei_add_target_property(${targetname} COMPILE_FLAGS "${ARGV2}")
   endif(${ARGC} GREATER 2)
-  
+
   if(EIGEN_TEST_CUSTOM_CXX_FLAGS)
     ei_add_target_property(${targetname} COMPILE_FLAGS "${EIGEN_TEST_CUSTOM_CXX_FLAGS}")
   endif()
@@ -95,12 +95,12 @@
       # notice: no double quotes around ${libs_to_link} here. It may be a list.
       target_link_libraries(${targetname} ${libs_to_link})
     endif()
-  endif() 
+  endif()
 
   add_test(${testname_with_suffix} "${targetname}")
-  
+
   # Specify target and test labels accoirding to EIGEN_CURRENT_SUBPROJECT
-  get_property(current_subproject GLOBAL PROPERTY EIGEN_CURRENT_SUBPROJECT)  
+  get_property(current_subproject GLOBAL PROPERTY EIGEN_CURRENT_SUBPROJECT)
   if ((current_subproject) AND (NOT (current_subproject STREQUAL "")))
     set_property(TARGET ${targetname} PROPERTY LABELS "Build${current_subproject}")
     add_dependencies("Build${current_subproject}" ${targetname})
@@ -128,14 +128,14 @@
     OUTPUT ${include_file}
     COMMAND ${CMAKE_COMMAND} -E echo "\\#include \\\"${host_file}\\\"" > ${include_file}
     COMMAND ${CMAKE_COMMAND} -E echo "\\#include \\\"${bc_file}.sycl\\\"" >> ${include_file}
-    DEPENDS ${filename}
+    DEPENDS ${filename} ${bc_file}.sycl
     COMMENT "Building ComputeCpp integration header file ${include_file}"
   )
   # Add a custom target for the generated integration header
-  add_custom_target(${testname}_integration_header_woho DEPENDS ${include_file})
+  add_custom_target(${testname}_integration_header_sycl DEPENDS ${include_file})
 
   add_executable(${targetname} ${include_file})
-  add_dependencies(${targetname} ${testname}_integration_header_woho)
+  add_dependencies(${targetname} ${testname}_integration_header_sycl)
   add_sycl_to_target(${targetname} ${filename} ${CMAKE_CURRENT_BINARY_DIR})
 
   if (targetname MATCHES "^eigen2_")
@@ -258,7 +258,7 @@
   else()
     set(filename ${testname}.cpp)
   endif()
-  
+
   file(READ "${filename}" test_source)
   set(parts 0)
   string(REGEX MATCHALL "CALL_SUBTEST_[0-9]+|EIGEN_TEST_PART_[0-9]+|EIGEN_SUFFIXES(;[0-9]+)+"
@@ -379,7 +379,7 @@
   elseif(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
     message(STATUS "Explicit vectorization disabled (alignment kept enabled)")
   else()
-  
+
   message(STATUS "Maximal matrix/vector size: ${EIGEN_TEST_MAX_SIZE}")
 
     if(EIGEN_TEST_SSE2)
@@ -453,13 +453,13 @@
     else()
       message(STATUS "ARMv8 NEON:        Using architecture defaults")
     endif()
- 
+
     if(EIGEN_TEST_ZVECTOR)
       message(STATUS "S390X ZVECTOR:     ON")
     else()
       message(STATUS "S390X ZVECTOR:     Using architecture defaults")
     endif()
-   
+
     if(EIGEN_TEST_CXX11)
       message(STATUS "C++11:             ON")
     else()
@@ -505,7 +505,7 @@
 
   set_property(GLOBAL PROPERTY EIGEN_FAILTEST_FAILURE_COUNT "0")
   set_property(GLOBAL PROPERTY EIGEN_FAILTEST_COUNT "0")
-  
+
   # uncomment anytime you change the ei_get_compilerver_from_cxx_version_string macro
   # ei_test_get_compilerver_from_cxx_version_string()
 endmacro(ei_init_testing)
@@ -514,22 +514,22 @@
   # if the sitename is not yet set, try to set it
   if(NOT ${SITE} OR ${SITE} STREQUAL "")
     set(eigen_computername $ENV{COMPUTERNAME})
-	set(eigen_hostname $ENV{HOSTNAME})
+  set(eigen_hostname $ENV{HOSTNAME})
     if(eigen_hostname)
       set(SITE ${eigen_hostname})
-	elseif(eigen_computername)
-	  set(SITE ${eigen_computername})
+  elseif(eigen_computername)
+    set(SITE ${eigen_computername})
     endif()
   endif()
   # in case it is already set, enforce lower case
   if(SITE)
     string(TOLOWER ${SITE} SITE)
-  endif()  
+  endif()
 endmacro(ei_set_sitename)
 
 macro(ei_get_compilerver VAR)
     if(MSVC)
-      # on windows system, we use a modified CMake script  
+      # on windows system, we use a modified CMake script
       include(EigenDetermineVSServicePack)
       EigenDetermineVSServicePack( my_service_pack )
 
@@ -541,20 +541,20 @@
     else()
     # on all other system we rely on ${CMAKE_CXX_COMPILER}
     # supporting a "--version" or "/version" flag
-    
+
     if(WIN32 AND ${CMAKE_CXX_COMPILER_ID} EQUAL "Intel")
       set(EIGEN_CXX_FLAG_VERSION "/version")
     else()
       set(EIGEN_CXX_FLAG_VERSION "--version")
     endif()
-    
+
     execute_process(COMMAND ${CMAKE_CXX_COMPILER} ${EIGEN_CXX_FLAG_VERSION}
                     OUTPUT_VARIABLE eigen_cxx_compiler_version_string OUTPUT_STRIP_TRAILING_WHITESPACE)
     string(REGEX REPLACE "[\n\r].*"  ""  eigen_cxx_compiler_version_string  ${eigen_cxx_compiler_version_string})
-    
+
     ei_get_compilerver_from_cxx_version_string("${eigen_cxx_compiler_version_string}" CNAME CVER)
     set(${VAR} "${CNAME}-${CVER}")
-    
+
   endif()
 endmacro(ei_get_compilerver)
 
@@ -563,13 +563,13 @@
 # the testing macro call in ei_init_testing() of the EigenTesting.cmake file.
 # See also the ei_test_get_compilerver_from_cxx_version_string macro at the end of the file
 macro(ei_get_compilerver_from_cxx_version_string VERSTRING CNAME CVER)
-  # extract possible compiler names  
+  # extract possible compiler names
   string(REGEX MATCH "g\\+\\+"      ei_has_gpp    ${VERSTRING})
   string(REGEX MATCH "llvm|LLVM"    ei_has_llvm   ${VERSTRING})
   string(REGEX MATCH "gcc|GCC"      ei_has_gcc    ${VERSTRING})
   string(REGEX MATCH "icpc|ICC"     ei_has_icpc   ${VERSTRING})
   string(REGEX MATCH "clang|CLANG"  ei_has_clang  ${VERSTRING})
-  
+
   # combine them
   if((ei_has_llvm) AND (ei_has_gpp OR ei_has_gcc))
     set(${CNAME} "llvm-g++")
@@ -584,7 +584,7 @@
   else()
     set(${CNAME} "_")
   endif()
-  
+
   # extract possible version numbers
   # first try to extract 3 isolated numbers:
   string(REGEX MATCH " [0-9]+\\.[0-9]+\\.[0-9]+" eicver ${VERSTRING})
@@ -602,9 +602,9 @@
       endif()
     endif()
   endif()
-  
+
   string(REGEX REPLACE ".(.*)" "\\1" ${CVER} ${eicver})
-  
+
 endmacro(ei_get_compilerver_from_cxx_version_string)
 
 macro(ei_get_cxxflags VAR)
@@ -633,30 +633,30 @@
   elseif(EIGEN_TEST_SSE3)
     set(${VAR} SSE3)
   elseif(EIGEN_TEST_SSE2 OR IS_64BIT_ENV)
-    set(${VAR} SSE2)  
+    set(${VAR} SSE2)
   endif()
 
   if(EIGEN_TEST_OPENMP)
     if (${VAR} STREQUAL "")
-	  set(${VAR} OMP)
-	else()
-	  set(${VAR} ${${VAR}}-OMP)
-	endif()
+    set(${VAR} OMP)
+  else()
+    set(${VAR} ${${VAR}}-OMP)
   endif()
-  
+  endif()
+
   if(EIGEN_DEFAULT_TO_ROW_MAJOR)
     if (${VAR} STREQUAL "")
-	  set(${VAR} ROW)
-	else()
-	  set(${VAR} ${${VAR}}-ROWMAJ)
-	endif()  
+    set(${VAR} ROW)
+  else()
+    set(${VAR} ${${VAR}}-ROWMAJ)
+  endif()
   endif()
 endmacro(ei_get_cxxflags)
 
 macro(ei_set_build_string)
   ei_get_compilerver(LOCAL_COMPILER_VERSION)
   ei_get_cxxflags(LOCAL_COMPILER_FLAGS)
-  
+
   include(EigenDetermineOSVersion)
   DetermineOSVersion(OS_VERSION)
 
@@ -672,11 +672,11 @@
   else()
     set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-64bit)
   endif()
-  
+
   if(EIGEN_TEST_CXX11)
     set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-cxx11)
   endif()
-  
+
   if(EIGEN_BUILD_STRING_SUFFIX)
     set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-${EIGEN_BUILD_STRING_SUFFIX})
   endif()

diff --git a/cmake/FindComputeCpp.cmake b/cmake/FindComputeCpp.cmake
index 3aab5b8..07ebed6 100644
--- a/cmake/FindComputeCpp.cmake
+++ b/cmake/FindComputeCpp.cmake

@@ -1,6 +1,21 @@
 #.rst:
 # FindComputeCpp
 #---------------
+#
+#   Copyright 2016 Codeplay Software Ltd.
+#
+#   Licensed under the Apache License, Version 2.0 (the "License");
+#   you may not use these files except in compliance with the License.
+#   You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+#
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
 
 #########################
 #  FindComputeCpp.cmake
@@ -8,6 +23,11 @@
 #
 #  Tools for finding and building with ComputeCpp.
 #
+#  User must define COMPUTECPP_PACKAGE_ROOT_DIR pointing to the ComputeCpp
+#   installation.
+#
+#  Latest version of this file can be found at:
+#    https://github.com/codeplaysoftware/computecpp-sdk
 
 # Require CMake version 3.2.2 or higher
 cmake_minimum_required(VERSION 3.2.2)
@@ -32,7 +52,6 @@
       message(FATAL_ERROR
         "host compiler - Not found! (clang version must be at least 3.6)")
     else()
-			set(COMPUTECPP_DISABLE_GCC_DUAL_ABI "True")
       message(STATUS "host compiler - clang ${CMAKE_CXX_COMPILER_VERSION}")
     endif()
 else()
@@ -48,11 +67,12 @@
 # Find OpenCL package
 find_package(OpenCL REQUIRED)
 
-# Find ComputeCpp package
-if(EXISTS ${COMPUTECPP_PACKAGE_ROOT_DIR})
-  message(STATUS "ComputeCpp package - Found (${COMPUTECPP_PACKAGE_ROOT_DIR})")
+# Find ComputeCpp packagee
+if(NOT COMPUTECPP_PACKAGE_ROOT_DIR)
+  message(FATAL_ERROR
+    "ComputeCpp package - Not found! (please set COMPUTECPP_PACKAGE_ROOT_DIR")
 else()
-  message(FATAL_ERROR "ComputeCpp package - Not found! (please set COMPUTECPP_PACKAGE_ROOT_DIR) (${COMPUTECPP_PACKAGE_ROOT_DIR})")
+  message(STATUS "ComputeCpp package - Found")
 endif()
 option(COMPUTECPP_PACKAGE_ROOT_DIR "Path to the ComputeCpp Package")
 
@@ -61,9 +81,9 @@
   ${COMPUTECPP_PACKAGE_ROOT_DIR} PATH_SUFFIXES bin)
 if (EXISTS ${COMPUTECPP_DEVICE_COMPILER})
   mark_as_advanced(COMPUTECPP_DEVICE_COMPILER)
-  message(STATUS "compute++ - Found (${COMPUTECPP_PACKAGE_ROOT_DIR})")
+  message(STATUS "compute++ - Found")
 else()
-  message(FATAL_ERROR "compute++ - Not found! (${COMPUTECPP_DEVICE_COMPILER}) (${COMPUTECPP_PACKAGE_ROOT_DIR})")
+  message(FATAL_ERROR "compute++ - Not found! (${COMPUTECPP_DEVICE_COMPILER})")
 endif()
 
 # Obtain the path to computecpp_info
@@ -71,9 +91,9 @@
   ${COMPUTECPP_PACKAGE_ROOT_DIR} PATH_SUFFIXES bin)
 if (EXISTS ${COMPUTECPP_INFO_TOOL})
   mark_as_advanced(${COMPUTECPP_INFO_TOOL})
-  message(STATUS "computecpp_info - Found (${COMPUTECPP_PACKAGE_ROOT_DIR})")
+  message(STATUS "computecpp_info - Found")
 else()
-  message(FATAL_ERROR "computecpp_info - Not found! (${COMPUTECPP_INFO_TOOL}) (${COMPUTECPP_PACKAGE_ROOT_DIR})")
+  message(FATAL_ERROR "computecpp_info - Not found! (${COMPUTECPP_INFO_TOOL})")
 endif()
 
 # Obtain the path to the ComputeCpp runtime library
@@ -85,15 +105,15 @@
   mark_as_advanced(COMPUTECPP_RUNTIME_LIBRARY)
   message(STATUS "libComputeCpp.so - Found")
 else()
-  message(FATAL_ERROR "libComputeCpp.so - Not found! (${COMPUTECPP_PACKAGE_ROOT_DIR})")
+  message(FATAL_ERROR "libComputeCpp.so - Not found!")
 endif()
 
 # Obtain the ComputeCpp include directory
 set(COMPUTECPP_INCLUDE_DIRECTORY ${COMPUTECPP_PACKAGE_ROOT_DIR}/include/)
 if (NOT EXISTS ${COMPUTECPP_INCLUDE_DIRECTORY})
-  message(FATAL_ERROR "ComputeCpp includes - Not found! (${COMPUTECPP_PACKAGE_ROOT_DIR}/include/)")
+  message(FATAL_ERROR "ComputeCpp includes - Not found!")
 else()
-  message(STATUS "ComputeCpp includes - Found (${COMPUTECPP_PACKAGE_ROOT_DIR})")
+  message(STATUS "ComputeCpp includes - Found")
 endif()
 
 # Obtain the package version
@@ -144,7 +164,7 @@
 #
 #  targetName : Name of the target.
 #  sourceFile : Source file to be compiled.
-#  binaryDir  : Intermediate output directory for the integration header.
+#  binaryDir : Intermediate directory to output the integration header.
 #
 function(__build_spir targetName sourceFile binaryDir)
 
@@ -176,12 +196,13 @@
     OUTPUT ${outputSyclFile}
     COMMAND ${COMPUTECPP_DEVICE_COMPILER}
             ${COMPUTECPP_DEVICE_COMPILER_FLAGS}
-            -I${COMPUTECPP_INCLUDE_DIRECTORY}
+            -isystem ${COMPUTECPP_INCLUDE_DIRECTORY}
             ${COMPUTECPP_PLATFORM_SPECIFIC_ARGS}
             ${device_compiler_includes}
             -o ${outputSyclFile}
             -c ${CMAKE_CURRENT_SOURCE_DIR}/${sourceFile}
     DEPENDS ${sourceFile}
+    WORKING_DIRECTORY ${binaryDir}
   COMMENT "Building ComputeCpp integration header file ${outputSyclFile}")
 
   # Add a custom target for the generated integration header
@@ -190,10 +211,6 @@
   # Add a dependency on the integration header
   add_dependencies(${targetName} ${targetName}_integration_header)
 
-  # Force inclusion of the integration header for the host compiler
-  #set(compileFlags -include ${include_file} "-Wall")
-  target_compile_options(${targetName} PUBLIC ${compileFlags})
-
   # Set the host compiler C++ standard to C++11
   set_property(TARGET ${targetName} PROPERTY CXX_STANDARD 11)
 
@@ -210,11 +227,11 @@
 #######################
 #
 #  Adds a SYCL compilation custom command associated with an existing
-#  target and sets a dependency on that new command.
+#  target and sets a dependancy on that new command.
 #
 #  targetName : Name of the target to add a SYCL to.
 #  sourceFile : Source file to be compiled for SYCL.
-#  binaryDir  : Intermediate output directory for the integration header.
+#  binaryDir : Intermediate directory to output the integration header.
 #
 function(add_sycl_to_target targetName sourceFile binaryDir)
 

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h b/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h
index 4231a11..8333301 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h

@@ -16,95 +16,93 @@
 #define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_SYCL_H
 
 namespace Eigen {
-/// \struct BufferT is used to specialise add_sycl_buffer function for
-//  two types of buffer we have. When the MapAllocator is true, we create the
-//  sycl buffer with MapAllocator.
-/// We have to const_cast the input pointer in order to work around the fact
-/// that sycl does not accept map allocator for const pointer.
-template <typename T, bool MapAllocator>
-struct BufferT {
-  using Type = cl::sycl::buffer<T, 1, cl::sycl::map_allocator<T>>;
-  static inline void add_sycl_buffer(const T *ptr, size_t num_bytes,std::map<const void *, std::shared_ptr<void>> &buffer_map) {
-    buffer_map.insert(std::pair<const void *, std::shared_ptr<void>>(ptr, std::shared_ptr<void>(std::make_shared<Type>(Type(const_cast<T *>(ptr), cl::sycl::range<1>(num_bytes))))));
-  }
-};
-
-/// specialisation of the \ref BufferT when the MapAllocator is false. In this
-/// case we only create the device-only buffer.
-template <typename T>
-struct BufferT<T, false> {
-  using Type = cl::sycl::buffer<T, 1>;
-  static inline void add_sycl_buffer(const T *ptr, size_t num_bytes, std::map<const void *, std::shared_ptr<void>> &buffer_map) {
-    buffer_map.insert(std::pair<const void *, std::shared_ptr<void>>(ptr, std::shared_ptr<void>(std::make_shared<Type>(Type(cl::sycl::range<1>(num_bytes))))));
-  }
-};
-
 struct SyclDevice {
   /// class members
   /// sycl queue
-  cl::sycl::queue &m_queue;
+  mutable cl::sycl::queue m_queue;
   /// std::map is the container used to make sure that we create only one buffer
-  /// per pointer. The lifespan of the buffer
-  /// now depends on the lifespan of SyclDevice. If a non-read-only pointer is
-  /// needed to be accessed on the host we should manually deallocate it.
+  /// per pointer. The lifespan of the buffer now depends on the lifespan of SyclDevice.
+  /// If a non-read-only pointer is needed to be accessed on the host we should manually deallocate it.
   mutable std::map<const void *, std::shared_ptr<void>> buffer_map;
-
-  SyclDevice(cl::sycl::queue &q) : m_queue(q) {}
+  /// creating device by using selector
+  template<typename dev_Selector> SyclDevice(dev_Selector s)
+  :m_queue(cl::sycl::queue(s, [=](cl::sycl::exception_list l) {
+    for (const auto& e : l) {
+      try {
+        std::rethrow_exception(e);
+      } catch (cl::sycl::exception e) {
+          std::cout << e.what() << std::endl;
+        }
+    }
+  })) {}
   // destructor
   ~SyclDevice() { deallocate_all(); }
 
-  template <typename T>
-  void deallocate(const T *p) const {
+  template <typename T> void deallocate(T *p) const {
     auto it = buffer_map.find(p);
     if (it != buffer_map.end()) {
       buffer_map.erase(it);
+      internal::aligned_free(p);
     }
   }
-  void deallocate_all() const { buffer_map.clear(); }
+  void deallocate_all() const {
+    std::map<const void *, std::shared_ptr<void>>::iterator it=buffer_map.begin();
+    while (it!=buffer_map.end()) {
+      auto p=it->first;
+      buffer_map.erase(it);
+      internal::aligned_free(const_cast<void*>(p));
+      it=buffer_map.begin();
+    }
+    buffer_map.clear();
+  }
 
   /// creation of sycl accessor for a buffer. This function first tries to find
-  /// the buffer in the buffer_map.
-  /// If found it gets the accessor from it, if not, the function then adds an
-  /// entry by creating a sycl buffer
-  /// for that particular pointer.
-  template <cl::sycl::access::mode AcMd, bool MapAllocator, typename T>
-  inline cl::sycl::accessor<T, 1, AcMd, cl::sycl::access::target::global_buffer>
+  /// the buffer in the buffer_map. If found it gets the accessor from it, if not,
+  ///the function then adds an entry by creating a sycl buffer for that particular pointer.
+  template <cl::sycl::access::mode AcMd, typename T> inline cl::sycl::accessor<T, 1, AcMd, cl::sycl::access::target::global_buffer>
   get_sycl_accessor(size_t num_bytes, cl::sycl::handler &cgh, const T * ptr) const {
-    return (get_sycl_buffer<MapAllocator,T>(num_bytes, ptr).template get_access<AcMd, cl::sycl::access::target::global_buffer>(cgh));
+    return (get_sycl_buffer<T>(num_bytes, ptr)->template get_access<AcMd, cl::sycl::access::target::global_buffer>(cgh));
   }
 
-template <bool MapAllocator, typename T>
- inline typename BufferT<T, MapAllocator>::Type
-  get_sycl_buffer(size_t num_bytes,const T * ptr) const {
-    if(MapAllocator && !ptr){
-      eigen_assert("pointer with map_Allocator cannot be null. Please initialise the input pointer"); }
-    auto it = buffer_map.find(ptr);
-    if (it == buffer_map.end()) {
-      BufferT<T, MapAllocator>::add_sycl_buffer(ptr, num_bytes, buffer_map);
-    }
-    return (*((typename BufferT<T, MapAllocator>::Type*)((buffer_map.at(ptr).get()))));
+  template<typename T> inline  std::pair<std::map<const void *, std::shared_ptr<void>>::iterator,bool> add_sycl_buffer(const T *ptr, size_t num_bytes) const {
+    using Type = cl::sycl::buffer<T, 1>;
+    std::pair<std::map<const void *, std::shared_ptr<void>>::iterator,bool> ret = buffer_map.insert(std::pair<const void *, std::shared_ptr<void>>(ptr, std::shared_ptr<void>(new Type(cl::sycl::range<1>(num_bytes)),
+      [](void *dataMem) { delete static_cast<Type*>(dataMem); })));
+    (static_cast<Type*>(buffer_map.at(ptr).get()))->set_final_data(nullptr);
+    return ret;
+  }
+
+  template <typename T> inline cl::sycl::buffer<T, 1>* get_sycl_buffer(size_t num_bytes,const T * ptr) const {
+    return static_cast<cl::sycl::buffer<T, 1>*>(add_sycl_buffer(ptr, num_bytes).first->second.get());
   }
 
   /// allocating memory on the cpu
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void *allocate(size_t num_bytes) const {
-    return internal::aligned_malloc(num_bytes);
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void *allocate(size_t) const {
+    return internal::aligned_malloc(8);
   }
 
   // some runtime conditions that can be applied here
   bool isDeviceSuitable() const { return true; }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void deallocate(void *buffer) const {
-    internal::aligned_free(buffer);
-  }
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpy(void *dst, const void *src, size_t n) const {
     ::memcpy(dst, src, n);
   }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyHostToDevice(void *dst, const void *src, size_t n) const {
-    memcpy(dst, src, n);
+
+  template<typename T> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyHostToDevice(T *dst, const T *src, size_t n) const {
+    auto host_acc= (static_cast<cl::sycl::buffer<T, 1>*>(add_sycl_buffer(dst, n).first->second.get()))-> template get_access<cl::sycl::access::mode::discard_write, cl::sycl::access::target::host_buffer>();
+    memcpy(host_acc.get_pointer(), src, n);
   }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyDeviceToHost(void *dst, const void *src, size_t n) const {
-    memcpy(dst, src, n);
+ /// whith the current implementation of sycl, the data is copied twice from device to host. This will be fixed soon.
+  template<typename T> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyDeviceToHost(T *dst, const T *src, size_t n) const {
+    auto it = buffer_map.find(src);
+    if (it != buffer_map.end()) {
+      auto host_acc= (static_cast<cl::sycl::buffer<T, 1>*>(it->second.get()))-> template get_access<cl::sycl::access::mode::read, cl::sycl::access::target::host_buffer>();
+      memcpy(dst,host_acc.get_pointer(),  n);
+    } else{
+      eigen_assert("no device memory found. The memory might be destroyed before creation");
+    }
   }
+
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memset(void *buffer, int c, size_t n) const {
     ::memset(buffer, c, n);
   }
@@ -112,6 +110,7 @@
   return 1;
   }
 };
+
 }  // end namespace Eigen
 
 #endif  // EIGEN_CXX11_TENSOR_TENSOR_DEVICE_SYCL_H

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h b/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
index 367bccf..f731bf1 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h

@@ -662,13 +662,7 @@
     }
   }
 
-  /// required by sycl in order to extract the output accessor
-#ifndef EIGEN_USE_SYCL
-  EIGEN_DEVICE_FUNC typename MakePointer_<Scalar>::Type data() const { return NULL; }
-#else
-  EIGEN_DEVICE_FUNC typename MakePointer_<Scalar>::Type data() const {
-    return m_result; }
-#endif
+  EIGEN_DEVICE_FUNC typename MakePointer_<Scalar>::Type data() const { return m_result; }
   /// required by sycl in order to extract the accessor
   const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
   /// added for sycl in order to construct the buffer from the sycl device

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorReductionSycl.h b/unsupported/Eigen/CXX11/src/Tensor/TensorReductionSycl.h
index 1c89132..3daecb0 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorReductionSycl.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorReductionSycl.h

@@ -27,9 +27,9 @@
 
 template<typename CoeffReturnType, typename KernelName> struct syclGenericBufferReducer{
 template<typename BufferTOut, typename BufferTIn>
-static void run(BufferTOut& bufOut, BufferTIn& bufI, const Eigen::SyclDevice& dev, size_t length, size_t local){
+static void run(BufferTOut* bufOut, BufferTIn& bufI, const Eigen::SyclDevice& dev, size_t length, size_t local){
   do {
-          auto f = [length, local, &bufOut, &bufI](cl::sycl::handler& h) mutable {
+          auto f = [length, local, bufOut, &bufI](cl::sycl::handler& h) mutable {
             cl::sycl::nd_range<1> r{cl::sycl::range<1>{std::max(length, local)},
                                     cl::sycl::range<1>{std::min(length, local)}};
             /* Two accessors are used: one to the buffer that is being reduced,
@@ -37,7 +37,7 @@
             auto aI =
                 bufI.template get_access<cl::sycl::access::mode::read_write>(h);
             auto aOut =
-                bufOut.template get_access<cl::sycl::access::mode::discard_write>(h);
+                bufOut->template get_access<cl::sycl::access::mode::discard_write>(h);
             cl::sycl::accessor<CoeffReturnType, 1, cl::sycl::access::mode::read_write,
                                cl::sycl::access::target::local>
                 scratch(cl::sycl::range<1>(local), h);
@@ -134,7 +134,7 @@
     /// if the shared memory is less than the GRange, we set shared_mem size to the TotalSize and in this case one kernel would be created for recursion to reduce all to one.
     if (GRange < outTileSize) outTileSize=GRange;
     // getting final out buffer at the moment the created buffer is true because there is no need for assign
-    auto out_buffer =dev.template get_sycl_buffer<true, typename Eigen::internal::remove_all<CoeffReturnType>::type>(self.dimensions().TotalSize(), output);
+    auto out_buffer =dev.template get_sycl_buffer<typename Eigen::internal::remove_all<CoeffReturnType>::type>(self.dimensions().TotalSize(), output);
     /// creating the shared memory for calculating reduction.
     /// This one is used to collect all the reduced value of shared memory as we dont have global barrier on GPU. Once it is saved we can
     /// recursively apply reduction on it in order to reduce the whole.
@@ -208,7 +208,7 @@
     dev.m_queue.submit([&](cl::sycl::handler &cgh) {
       // create a tuple of accessors from Evaluator
       auto tuple_of_accessors =  TensorSycl::internal::createTupleOfAccessors(cgh, self.impl());
-      auto output_accessor = dev.template get_sycl_accessor<cl::sycl::access::mode::discard_write, true>(num_coeffs_to_preserve,cgh, output);
+      auto output_accessor = dev.template get_sycl_accessor<cl::sycl::access::mode::discard_write>(num_coeffs_to_preserve,cgh, output);
 
       cgh.parallel_for<Self>( cl::sycl::nd_range<1>(cl::sycl::range<1>(GRange), cl::sycl::range<1>(tileSize)), [=](cl::sycl::nd_item<1> itemID) {
         typedef typename TensorSycl::internal::ConvertToDeviceExpression<const HostExpr>::Type DevExpr;

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractAccessor.h b/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractAccessor.h
index 3af5f8c..b1da685 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractAccessor.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractAccessor.h

@@ -56,10 +56,10 @@
   -> decltype(utility::tuple::append(ExtractAccessor<Arg1>::getTuple(cgh, eval1),utility::tuple::append(ExtractAccessor<Arg2>::getTuple(cgh, eval2), ExtractAccessor<Arg3>::getTuple(cgh, eval3)))) {
     return utility::tuple::append(ExtractAccessor<Arg1>::getTuple(cgh, eval1),utility::tuple::append(ExtractAccessor<Arg2>::getTuple(cgh, eval2), ExtractAccessor<Arg3>::getTuple(cgh, eval3)));
   }
-  template< cl::sycl::access::mode AcM,  bool MapAllocator, typename Arg> static inline auto getAccessor(cl::sycl::handler& cgh, Arg eval)
-  -> decltype(utility::tuple::make_tuple( eval.device().template get_sycl_accessor<AcM, MapAllocator,
+  template< cl::sycl::access::mode AcM, typename Arg> static inline auto getAccessor(cl::sycl::handler& cgh, Arg eval)
+  -> decltype(utility::tuple::make_tuple( eval.device().template get_sycl_accessor<AcM,
   typename Eigen::internal::remove_all<typename Arg::CoeffReturnType>::type>(eval.dimensions().TotalSize(), cgh,eval.data()))){
-    return utility::tuple::make_tuple(eval.device().template get_sycl_accessor<AcM, MapAllocator, typename Eigen::internal::remove_all<typename Arg::CoeffReturnType>::type>(eval.dimensions().TotalSize(), cgh,eval.data()));
+    return utility::tuple::make_tuple(eval.device().template get_sycl_accessor<AcM, typename Eigen::internal::remove_all<typename Arg::CoeffReturnType>::type>(eval.dimensions().TotalSize(), cgh,eval.data()));
   }
 };
 
@@ -141,8 +141,8 @@
 template <typename PlainObjectType, int Options_, typename Dev>\
 struct ExtractAccessor<TensorEvaluator<CVQual TensorMap<PlainObjectType, Options_>, Dev> > {\
   static inline auto getTuple(cl::sycl::handler& cgh,const TensorEvaluator<CVQual TensorMap<PlainObjectType, Options_>, Dev> eval)\
-  -> decltype(AccessorConstructor::template getAccessor<ACCType, true>(cgh, eval)){\
-    return AccessorConstructor::template getAccessor<ACCType, true>(cgh, eval);\
+  -> decltype(AccessorConstructor::template getAccessor<ACCType>(cgh, eval)){\
+    return AccessorConstructor::template getAccessor<ACCType>(cgh, eval);\
   }\
 };
 TENSORMAPEXPR(const, cl::sycl::access::mode::read)
@@ -153,8 +153,8 @@
 template <typename Expr, typename Dev>
 struct ExtractAccessor<TensorEvaluator<const TensorForcedEvalOp<Expr>, Dev> > {
   static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<const TensorForcedEvalOp<Expr>, Dev> eval)
-  -> decltype(AccessorConstructor::template getAccessor<cl::sycl::access::mode::read, false>(cgh, eval)){
-    return AccessorConstructor::template getAccessor<cl::sycl::access::mode::read, false>(cgh, eval);
+  -> decltype(AccessorConstructor::template getAccessor<cl::sycl::access::mode::read>(cgh, eval)){
+    return AccessorConstructor::template getAccessor<cl::sycl::access::mode::read>(cgh, eval);
   }
 };
 
@@ -167,8 +167,8 @@
 template <typename Expr, typename Dev>
 struct ExtractAccessor<TensorEvaluator<const TensorEvalToOp<Expr>, Dev> > {
   static inline auto getTuple(cl::sycl::handler& cgh,const TensorEvaluator<const TensorEvalToOp<Expr>, Dev> eval)
-  -> decltype(utility::tuple::append(AccessorConstructor::template getAccessor<cl::sycl::access::mode::write, false>(cgh, eval), AccessorConstructor::getTuple(cgh, eval.impl()))){
-    return utility::tuple::append(AccessorConstructor::template getAccessor<cl::sycl::access::mode::write, false>(cgh, eval), AccessorConstructor::getTuple(cgh, eval.impl()));
+  -> decltype(utility::tuple::append(AccessorConstructor::template getAccessor<cl::sycl::access::mode::write>(cgh, eval), AccessorConstructor::getTuple(cgh, eval.impl()))){
+    return utility::tuple::append(AccessorConstructor::template getAccessor<cl::sycl::access::mode::write>(cgh, eval), AccessorConstructor::getTuple(cgh, eval.impl()));
   }
 };
 
@@ -181,8 +181,8 @@
 template <typename OP, typename Dim, typename Expr, typename Dev>
 struct ExtractAccessor<TensorEvaluator<const TensorReductionOp<OP, Dim, Expr>, Dev> > {
   static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<const TensorReductionOp<OP, Dim, Expr>, Dev> eval)
-  -> decltype(AccessorConstructor::template getAccessor<cl::sycl::access::mode::read, false>(cgh, eval)){
-    return AccessorConstructor::template getAccessor<cl::sycl::access::mode::read, false>(cgh, eval);
+  -> decltype(AccessorConstructor::template getAccessor<cl::sycl::access::mode::read>(cgh, eval)){
+    return AccessorConstructor::template getAccessor<cl::sycl::access::mode::read>(cgh, eval);
   }
 };
 

diff --git a/unsupported/test/cxx11_tensor_broadcast_sycl.cpp b/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
index ecebf7d..7201bfe 100644
--- a/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
+++ b/unsupported/test/cxx11_tensor_broadcast_sycl.cpp

@@ -25,55 +25,50 @@
 using Eigen::Tensor;
 using Eigen::TensorMap;
 
-// Types used in tests:
-using TestTensor = Tensor<float, 3>;
-using TestTensorMap = TensorMap<Tensor<float, 3>>;
-static void test_broadcast_sycl(){
+static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
 
-	cl::sycl::gpu_selector s;
-  cl::sycl::queue q(s, [=](cl::sycl::exception_list l) {
-    for (const auto& e : l) {
-      try {
-        std::rethrow_exception(e);
-      } catch (cl::sycl::exception e) {
-        std::cout << e.what() << std::endl;
+  // BROADCAST test:
+  array<int, 4> in_range   = {{2, 3, 5, 7}};
+  array<int, 4> broadcasts = {{2, 3, 1, 4}};
+  array<int, 4> out_range;  // = in_range * broadcasts
+  for (size_t i = 0; i < out_range.size(); ++i)
+    out_range[i] = in_range[i] * broadcasts[i];
+
+  Tensor<float, 4>  input(in_range);
+  Tensor<float, 4> out(out_range);
+
+  for (size_t i = 0; i < in_range.size(); ++i)
+    VERIFY_IS_EQUAL(out.dimension(i), out_range[i]);
+
+
+  for (int i = 0; i < input.size(); ++i)
+    input(i) = static_cast<float>(i);
+
+  float * gpu_in_data  = static_cast<float*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_out_data  = static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
+
+  TensorMap<Tensor<float, 4>>  gpu_in(gpu_in_data, in_range);
+  TensorMap<Tensor<float, 4>> gpu_out(gpu_out_data, out_range);
+  sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(float));
+  gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
+
+  for (int i = 0; i < 4; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 28; ++l) {
+          VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), out(i,j,k,l));
+        }
       }
     }
-  });
-	SyclDevice sycl_device(q);
-	// BROADCAST test:
-	array<int, 4> in_range   = {{2, 3, 5, 7}};
-	array<int, in_range.size()> broadcasts = {{2, 3, 1, 4}};
-	array<int, in_range.size()> out_range;  // = in_range * broadcasts
-	for (size_t i = 0; i < out_range.size(); ++i)
-		out_range[i] = in_range[i] * broadcasts[i];
-
-	Tensor<float, in_range.size()>  input(in_range);
-	Tensor<float, out_range.size()> output(out_range);
-
-	for (int i = 0; i < input.size(); ++i)
-		input(i) = static_cast<float>(i);
-
-	TensorMap<decltype(input)>  gpu_in(input.data(), in_range);
-	TensorMap<decltype(output)> gpu_out(output.data(), out_range);
-		gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
-		sycl_device.deallocate(output.data());
-
-	for (size_t i = 0; i < in_range.size(); ++i)
-		VERIFY_IS_EQUAL(output.dimension(i), out_range[i]);
-
-	for (int i = 0; i < 4; ++i) {
-		for (int j = 0; j < 9; ++j) {
-			for (int k = 0; k < 5; ++k) {
-				for (int l = 0; l < 28; ++l) {
-					VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), output(i,j,k,l));
-				}
-			}
-		}
-	}
-	printf("Broadcast Test Passed\n");
+  }
+  printf("Broadcast Test Passed\n");
+  sycl_device.deallocate(gpu_in_data);
+  sycl_device.deallocate(gpu_out_data);
 }
 
 void test_cxx11_tensor_broadcast_sycl() {
-  CALL_SUBTEST(test_broadcast_sycl());
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST(test_broadcast_sycl(sycl_device));
 }

diff --git a/unsupported/test/cxx11_tensor_device_sycl.cpp b/unsupported/test/cxx11_tensor_device_sycl.cpp
index f54fc87..7f79753 100644
--- a/unsupported/test/cxx11_tensor_device_sycl.cpp
+++ b/unsupported/test/cxx11_tensor_device_sycl.cpp

@@ -20,20 +20,12 @@
 #include "main.h"
 #include <unsupported/Eigen/CXX11/Tensor>
 
-void test_device_sycl() {
-  cl::sycl::gpu_selector s;
-  cl::sycl::queue q(s, [=](cl::sycl::exception_list l) {
-    for (const auto& e : l) {
-      try {
-        std::rethrow_exception(e);
-      } catch (cl::sycl::exception e) {
-        std::cout << e.what() << std::endl;
-      }
-    }
-  });
-  Eigen::SyclDevice sycl_device(q);
-	printf("Helo from ComputeCpp: Device Exists\n");
+void test_device_sycl(const Eigen::SyclDevice &sycl_device) {
+  std::cout <<"Helo from ComputeCpp: the requested device exists and the device name is : "
+    << sycl_device.m_queue.get_device(). template get_info<cl::sycl::info::device::name>() <<std::endl;;
 }
 void test_cxx11_tensor_device_sycl() {
-  CALL_SUBTEST(test_device_sycl());
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST(test_device_sycl(sycl_device));
 }

diff --git a/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp b/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
index 182ec7f..5690da7 100644
--- a/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
+++ b/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp

@@ -22,18 +22,7 @@
 
 using Eigen::Tensor;
 
-void test_forced_eval_sycl() {
-	cl::sycl::gpu_selector s;
-  cl::sycl::queue q(s, [=](cl::sycl::exception_list l) {
-    for (const auto& e : l) {
-      try {
-        std::rethrow_exception(e);
-      } catch (cl::sycl::exception e) {
-        std::cout << e.what() << std::endl;
-      }
-    }
-  });
-	SyclDevice sycl_device(q);
+void test_forced_eval_sycl(const Eigen::SyclDevice &sycl_device) {
 
   int sizeDim1 = 100;
   int sizeDim2 = 200;
@@ -43,17 +32,22 @@
   Eigen::Tensor<float, 3> in2(tensorRange);
   Eigen::Tensor<float, 3> out(tensorRange);
 
+  float * gpu_in1_data  = static_cast<float*>(sycl_device.allocate(in1.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_in2_data  = static_cast<float*>(sycl_device.allocate(in2.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_out_data =  static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
+
   in1 = in1.random() + in1.constant(10.0f);
   in2 = in2.random() + in2.constant(10.0f);
 
-	// creating TensorMap from tensor
-  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_in1(in1.data(), tensorRange);
-  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_in2(in2.data(), tensorRange);
-  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_out(out.data(), tensorRange);
-
+  // creating TensorMap from tensor
+  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_in1(gpu_in1_data, tensorRange);
+  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_in2(gpu_in2_data, tensorRange);
+  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_out(gpu_out_data, tensorRange);
+  sycl_device.memcpyHostToDevice(gpu_in1_data, in1.data(),(in1.dimensions().TotalSize())*sizeof(float));
+  sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in1.dimensions().TotalSize())*sizeof(float));
   /// c=(a+b)*b
-	gpu_out.device(sycl_device) =(gpu_in1 + gpu_in2).eval() * gpu_in2;
-	sycl_device.deallocate(out.data());
+  gpu_out.device(sycl_device) =(gpu_in1 + gpu_in2).eval() * gpu_in2;
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
   for (int i = 0; i < sizeDim1; ++i) {
     for (int j = 0; j < sizeDim2; ++j) {
       for (int k = 0; k < sizeDim3; ++k) {
@@ -62,7 +56,15 @@
       }
     }
   }
-	printf("(a+b)*b Test Passed\n");
+  printf("(a+b)*b Test Passed\n");
+  sycl_device.deallocate(gpu_in1_data);
+  sycl_device.deallocate(gpu_in2_data);
+  sycl_device.deallocate(gpu_out_data);
+
 }
 
-void test_cxx11_tensor_forced_eval_sycl() { CALL_SUBTEST(test_forced_eval_sycl()); }
+void test_cxx11_tensor_forced_eval_sycl() {
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST(test_forced_eval_sycl(sycl_device));
+}

diff --git a/unsupported/test/cxx11_tensor_reduction_sycl.cpp b/unsupported/test/cxx11_tensor_reduction_sycl.cpp
index bd09744..a9ef829 100644
--- a/unsupported/test/cxx11_tensor_reduction_sycl.cpp
+++ b/unsupported/test/cxx11_tensor_reduction_sycl.cpp

@@ -22,126 +22,117 @@
 
 
 
-static void test_full_reductions_sycl() {
-
-
-  cl::sycl::gpu_selector s;
-    cl::sycl::queue q(s, [=](cl::sycl::exception_list l) {
-      for (const auto& e : l) {
-        try {
-          std::rethrow_exception(e);
-        } catch (cl::sycl::exception e) {
-          std::cout << e.what() << std::endl;
-        }
-      }
-    });
-  Eigen::SyclDevice sycl_device(q);
+static void test_full_reductions_sycl(const Eigen::SyclDevice&  sycl_device) {
 
   const int num_rows = 452;
   const int num_cols = 765;
   array<int, 2> tensorRange = {{num_rows, num_cols}};
 
   Tensor<float, 2> in(tensorRange);
+  Tensor<float, 0> full_redux;
+  Tensor<float, 0> full_redux_gpu;
+
   in.setRandom();
 
-  Tensor<float, 0> full_redux;
-  Tensor<float, 0> full_redux_g;
   full_redux = in.sum();
-  float* out_data = (float*)sycl_device.allocate(sizeof(float));
-  TensorMap<Tensor<float, 2> >  in_gpu(in.data(), tensorRange);
-  TensorMap<Tensor<float, 0> >  full_redux_gpu(out_data);
-  full_redux_gpu.device(sycl_device) = in_gpu.sum();
-  sycl_device.deallocate(out_data);
+
+  float* gpu_in_data = static_cast<float*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(float)));
+  float* gpu_out_data =(float*)sycl_device.allocate(sizeof(float));
+
+  TensorMap<Tensor<float, 2> >  in_gpu(gpu_in_data, tensorRange);
+  TensorMap<Tensor<float, 0> >  out_gpu(gpu_out_data);
+
+  sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.dimensions().TotalSize())*sizeof(float));
+  out_gpu.device(sycl_device) = in_gpu.sum();
+  sycl_device.memcpyDeviceToHost(full_redux_gpu.data(), gpu_out_data, sizeof(float));
   // Check that the CPU and GPU reductions return the same result.
   VERIFY_IS_APPROX(full_redux_gpu(), full_redux());
 
+  sycl_device.deallocate(gpu_in_data);
+  sycl_device.deallocate(gpu_out_data);
 }
 
-
-static void test_first_dim_reductions_sycl() {
-
-
-  cl::sycl::gpu_selector s;
-    cl::sycl::queue q(s, [=](cl::sycl::exception_list l) {
-      for (const auto& e : l) {
-        try {
-          std::rethrow_exception(e);
-        } catch (cl::sycl::exception e) {
-          std::cout << e.what() << std::endl;
-        }
-      }
-    });
-  Eigen::SyclDevice sycl_device(q);
+static void test_first_dim_reductions_sycl(const Eigen::SyclDevice& sycl_device) {
 
   int dim_x = 145;
   int dim_y = 1;
   int dim_z = 67;
 
   array<int, 3> tensorRange = {{dim_x, dim_y, dim_z}};
-
-  Tensor<float, 3> in(tensorRange);
-  in.setRandom();
   Eigen::array<int, 1> red_axis;
   red_axis[0] = 0;
-  Tensor<float, 2> redux = in.sum(red_axis);
   array<int, 2> reduced_tensorRange = {{dim_y, dim_z}};
-  Tensor<float, 2> redux_g(reduced_tensorRange);
-  TensorMap<Tensor<float, 3> >  in_gpu(in.data(), tensorRange);
-  float* out_data = (float*)sycl_device.allocate(dim_y*dim_z*sizeof(float));
-  TensorMap<Tensor<float, 2> >  redux_gpu(out_data, dim_y, dim_z );
-  redux_gpu.device(sycl_device) = in_gpu.sum(red_axis);
 
-  sycl_device.deallocate(out_data);
+  Tensor<float, 3> in(tensorRange);
+  Tensor<float, 2> redux(reduced_tensorRange);
+  Tensor<float, 2> redux_gpu(reduced_tensorRange);
+
+  in.setRandom();
+
+  redux= in.sum(red_axis);
+
+  float* gpu_in_data = static_cast<float*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(float)));
+  float* gpu_out_data = static_cast<float*>(sycl_device.allocate(redux_gpu.dimensions().TotalSize()*sizeof(float)));
+
+  TensorMap<Tensor<float, 3> >  in_gpu(gpu_in_data, tensorRange);
+  TensorMap<Tensor<float, 2> >  out_gpu(gpu_out_data, reduced_tensorRange);
+
+  sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.dimensions().TotalSize())*sizeof(float));
+  out_gpu.device(sycl_device) = in_gpu.sum(red_axis);
+  sycl_device.memcpyDeviceToHost(redux_gpu.data(), gpu_out_data, redux_gpu.dimensions().TotalSize()*sizeof(float));
+
   // Check that the CPU and GPU reductions return the same result.
-  for(int j=0; j<dim_y; j++ )
-    for(int k=0; k<dim_z; k++ )
+  for(int j=0; j<reduced_tensorRange[0]; j++ )
+    for(int k=0; k<reduced_tensorRange[1]; k++ )
       VERIFY_IS_APPROX(redux_gpu(j,k), redux(j,k));
+
+  sycl_device.deallocate(gpu_in_data);
+  sycl_device.deallocate(gpu_out_data);
 }
 
-
-static void test_last_dim_reductions_sycl() {
-
-
-  cl::sycl::gpu_selector s;
-    cl::sycl::queue q(s, [=](cl::sycl::exception_list l) {
-      for (const auto& e : l) {
-        try {
-          std::rethrow_exception(e);
-        } catch (cl::sycl::exception e) {
-          std::cout << e.what() << std::endl;
-        }
-      }
-    });
-  Eigen::SyclDevice sycl_device(q);
+static void test_last_dim_reductions_sycl(const Eigen::SyclDevice &sycl_device) {
 
   int dim_x = 567;
   int dim_y = 1;
   int dim_z = 47;
 
   array<int, 3> tensorRange = {{dim_x, dim_y, dim_z}};
-
-  Tensor<float, 3> in(tensorRange);
-  in.setRandom();
   Eigen::array<int, 1> red_axis;
   red_axis[0] = 2;
-  Tensor<float, 2> redux = in.sum(red_axis);
   array<int, 2> reduced_tensorRange = {{dim_x, dim_y}};
-  Tensor<float, 2> redux_g(reduced_tensorRange);
-  TensorMap<Tensor<float, 3> >  in_gpu(in.data(), tensorRange);
-  float* out_data = (float*)sycl_device.allocate(dim_x*dim_y*sizeof(float));
-  TensorMap<Tensor<float, 2> >  redux_gpu(out_data, dim_x, dim_y );
-  redux_gpu.device(sycl_device) = in_gpu.sum(red_axis);
 
-  sycl_device.deallocate(out_data);
+  Tensor<float, 3> in(tensorRange);
+  Tensor<float, 2> redux(reduced_tensorRange);
+  Tensor<float, 2> redux_gpu(reduced_tensorRange);
+
+  in.setRandom();
+
+  redux= in.sum(red_axis);
+
+  float* gpu_in_data = static_cast<float*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(float)));
+  float* gpu_out_data = static_cast<float*>(sycl_device.allocate(redux_gpu.dimensions().TotalSize()*sizeof(float)));
+
+  TensorMap<Tensor<float, 3> >  in_gpu(gpu_in_data, tensorRange);
+  TensorMap<Tensor<float, 2> >  out_gpu(gpu_out_data, reduced_tensorRange);
+
+  sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.dimensions().TotalSize())*sizeof(float));
+  out_gpu.device(sycl_device) = in_gpu.sum(red_axis);
+  sycl_device.memcpyDeviceToHost(redux_gpu.data(), gpu_out_data, redux_gpu.dimensions().TotalSize()*sizeof(float));
   // Check that the CPU and GPU reductions return the same result.
-  for(int j=0; j<dim_x; j++ )
-    for(int k=0; k<dim_y; k++ )
+  for(int j=0; j<reduced_tensorRange[0]; j++ )
+    for(int k=0; k<reduced_tensorRange[1]; k++ )
       VERIFY_IS_APPROX(redux_gpu(j,k), redux(j,k));
+
+  sycl_device.deallocate(gpu_in_data);
+  sycl_device.deallocate(gpu_out_data);
+
 }
 
 void test_cxx11_tensor_reduction_sycl() {
-  CALL_SUBTEST((test_full_reductions_sycl()));
-  CALL_SUBTEST((test_first_dim_reductions_sycl()));
-  CALL_SUBTEST((test_last_dim_reductions_sycl()));
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST((test_full_reductions_sycl(sycl_device)));
+  CALL_SUBTEST((test_first_dim_reductions_sycl(sycl_device)));
+  CALL_SUBTEST((test_last_dim_reductions_sycl(sycl_device)));
 
 }

diff --git a/unsupported/test/cxx11_tensor_sycl.cpp b/unsupported/test/cxx11_tensor_sycl.cpp
index 0f66cd8..6a9c334 100644
--- a/unsupported/test/cxx11_tensor_sycl.cpp
+++ b/unsupported/test/cxx11_tensor_sycl.cpp

@@ -27,42 +27,33 @@
 using Eigen::Tensor;
 using Eigen::TensorMap;
 
-// Types used in tests:
-using TestTensor = Tensor<float, 3>;
-using TestTensorMap = TensorMap<Tensor<float, 3>>;
-
-void test_sycl_cpu() {
-  cl::sycl::gpu_selector s;
-  cl::sycl::queue q(s, [=](cl::sycl::exception_list l) {
-    for (const auto& e : l) {
-      try {
-        std::rethrow_exception(e);
-      } catch (cl::sycl::exception e) {
-        std::cout << e.what() << std::endl;
-      }
-    }
-  });
-  SyclDevice sycl_device(q);
+void test_sycl_cpu(const Eigen::SyclDevice &sycl_device) {
 
   int sizeDim1 = 100;
   int sizeDim2 = 100;
   int sizeDim3 = 100;
   array<int, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}};
-  TestTensor in1(tensorRange);
-  TestTensor in2(tensorRange);
-  TestTensor in3(tensorRange);
-  TestTensor out(tensorRange);
-  in1 = in1.random();
+  Tensor<float, 3> in1(tensorRange);
+  Tensor<float, 3> in2(tensorRange);
+  Tensor<float, 3> in3(tensorRange);
+  Tensor<float, 3> out(tensorRange);
+
   in2 = in2.random();
   in3 = in3.random();
-  TestTensorMap gpu_in1(in1.data(), tensorRange);
-  TestTensorMap gpu_in2(in2.data(), tensorRange);
-  TestTensorMap gpu_in3(in3.data(), tensorRange);
-  TestTensorMap gpu_out(out.data(), tensorRange);
+
+  float * gpu_in1_data  = static_cast<float*>(sycl_device.allocate(in1.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_in2_data  = static_cast<float*>(sycl_device.allocate(in2.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_in3_data  = static_cast<float*>(sycl_device.allocate(in3.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_out_data =  static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
+
+  TensorMap<Tensor<float, 3>> gpu_in1(gpu_in1_data, tensorRange);
+  TensorMap<Tensor<float, 3>> gpu_in2(gpu_in2_data, tensorRange);
+  TensorMap<Tensor<float, 3>> gpu_in3(gpu_in3_data, tensorRange);
+  TensorMap<Tensor<float, 3>> gpu_out(gpu_out_data, tensorRange);
 
   /// a=1.2f
   gpu_in1.device(sycl_device) = gpu_in1.constant(1.2f);
-  sycl_device.deallocate(in1.data());
+  sycl_device.memcpyDeviceToHost(in1.data(), gpu_in1_data ,(in1.dimensions().TotalSize())*sizeof(float));
   for (int i = 0; i < sizeDim1; ++i) {
     for (int j = 0; j < sizeDim2; ++j) {
       for (int k = 0; k < sizeDim3; ++k) {
@@ -74,7 +65,7 @@
 
   /// a=b*1.2f
   gpu_out.device(sycl_device) = gpu_in1 * 1.2f;
-  sycl_device.deallocate(out.data());
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data ,(out.dimensions().TotalSize())*sizeof(float));
   for (int i = 0; i < sizeDim1; ++i) {
     for (int j = 0; j < sizeDim2; ++j) {
       for (int k = 0; k < sizeDim3; ++k) {
@@ -86,8 +77,9 @@
   printf("a=b*1.2f Test Passed\n");
 
   /// c=a*b
+  sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in2.dimensions().TotalSize())*sizeof(float));
   gpu_out.device(sycl_device) = gpu_in1 * gpu_in2;
-  sycl_device.deallocate(out.data());
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
   for (int i = 0; i < sizeDim1; ++i) {
     for (int j = 0; j < sizeDim2; ++j) {
       for (int k = 0; k < sizeDim3; ++k) {
@@ -101,7 +93,7 @@
 
   /// c=a+b
   gpu_out.device(sycl_device) = gpu_in1 + gpu_in2;
-  sycl_device.deallocate(out.data());
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
   for (int i = 0; i < sizeDim1; ++i) {
     for (int j = 0; j < sizeDim2; ++j) {
       for (int k = 0; k < sizeDim3; ++k) {
@@ -115,7 +107,7 @@
 
   /// c=a*a
   gpu_out.device(sycl_device) = gpu_in1 * gpu_in1;
-  sycl_device.deallocate(out.data());
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
   for (int i = 0; i < sizeDim1; ++i) {
     for (int j = 0; j < sizeDim2; ++j) {
       for (int k = 0; k < sizeDim3; ++k) {
@@ -125,12 +117,11 @@
       }
     }
   }
-
   printf("c= a*a Test Passed\n");
 
   //a*3.14f + b*2.7f
   gpu_out.device(sycl_device) =  gpu_in1 * gpu_in1.constant(3.14f) + gpu_in2 * gpu_in2.constant(2.7f);
-  sycl_device.deallocate(out.data());
+  sycl_device.memcpyDeviceToHost(out.data(),gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
   for (int i = 0; i < sizeDim1; ++i) {
     for (int j = 0; j < sizeDim2; ++j) {
       for (int k = 0; k < sizeDim3; ++k) {
@@ -143,8 +134,9 @@
   printf("a*3.14f + b*2.7f Test Passed\n");
 
   ///d= (a>0.5? b:c)
+  sycl_device.memcpyHostToDevice(gpu_in3_data, in3.data(),(in3.dimensions().TotalSize())*sizeof(float));
   gpu_out.device(sycl_device) =(gpu_in1 > gpu_in1.constant(0.5f)).select(gpu_in2, gpu_in3);
-  sycl_device.deallocate(out.data());
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
   for (int i = 0; i < sizeDim1; ++i) {
     for (int j = 0; j < sizeDim2; ++j) {
       for (int k = 0; k < sizeDim3; ++k) {
@@ -155,8 +147,13 @@
     }
   }
   printf("d= (a>0.5? b:c) Test Passed\n");
-
+  sycl_device.deallocate(gpu_in1_data);
+  sycl_device.deallocate(gpu_in2_data);
+  sycl_device.deallocate(gpu_in3_data);
+  sycl_device.deallocate(gpu_out_data);
 }
 void test_cxx11_tensor_sycl() {
-  CALL_SUBTEST(test_sycl_cpu());
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST(test_sycl_cpu(sycl_device));
 }