diff --git a/examples_cuda/deferred/drvapi_error_string.h b/examples_cuda/deferred/drvapi_error_string.h
new file mode 100644
index 00000000..ce85f152
--- /dev/null
+++ b/examples_cuda/deferred/drvapi_error_string.h
@@ -0,0 +1,370 @@
+/*
+ * Copyright 1993-2012 NVIDIA Corporation.  All rights reserved.
+ *
+ * Please refer to the NVIDIA end user license agreement (EULA) associated
+ * with this source code for terms and conditions that govern your use of
+ * this software. Any use, reproduction, disclosure, or distribution of
+ * this software and related documentation outside the terms of the EULA
+ * is strictly prohibited.
+ *
+ */
+ 
+#ifndef _DRVAPI_ERROR_STRING_H_
+#define _DRVAPI_ERROR_STRING_H_
+
+#include <stdio.h>
+#include <string.h>
+#include <stdlib.h>
+
+// Error Code string definitions here
+typedef struct
+{
+    char const *error_string;
+    int  error_id;
+} s_CudaErrorStr;
+
+/**
+ * Error codes
+ */
+static s_CudaErrorStr sCudaDrvErrorString[] =
+{
+    /**
+     * The API call returned with no errors. In the case of query calls, this
+     * can also mean that the operation being queried is complete (see
+     * ::cuEventQuery() and ::cuStreamQuery()).
+     */
+    { "CUDA_SUCCESS", 0 },
+
+    /**
+     * This indicates that one or more of the parameters passed to the API call
+     * is not within an acceptable range of values.
+     */
+    { "CUDA_ERROR_INVALID_VALUE", 1 },
+
+    /**
+     * The API call failed because it was unable to allocate enough memory to
+     * perform the requested operation.
+     */
+    { "CUDA_ERROR_OUT_OF_MEMORY", 2 },
+
+    /**
+     * This indicates that the CUDA driver has not been initialized with
+     * ::cuInit() or that initialization has failed.
+     */
+    { "CUDA_ERROR_NOT_INITIALIZED", 3 },
+
+    /**
+     * This indicates that the CUDA driver is in the process of shutting down.
+     */
+    { "CUDA_ERROR_DEINITIALIZED", 4 },
+
+    /**
+     * This indicates profiling APIs are called while application is running
+     * in visual profiler mode. 
+    */
+    { "CUDA_ERROR_PROFILER_DISABLED", 5 },
+    /**
+     * This indicates profiling has not been initialized for this context. 
+     * Call cuProfilerInitialize() to resolve this. 
+    */
+    { "CUDA_ERROR_PROFILER_NOT_INITIALIZED", 6 },
+    /**
+     * This indicates profiler has already been started and probably
+     * cuProfilerStart() is incorrectly called.
+    */
+    { "CUDA_ERROR_PROFILER_ALREADY_STARTED", 7 },
+    /**
+     * This indicates profiler has already been stopped and probably
+     * cuProfilerStop() is incorrectly called.
+    */
+    { "CUDA_ERROR_PROFILER_ALREADY_STOPPED", 8 },  
+    /**
+     * This indicates that no CUDA-capable devices were detected by the installed
+     * CUDA driver.
+     */
+    { "CUDA_ERROR_NO_DEVICE (no CUDA-capable devices were detected)", 100 },
+
+    /**
+     * This indicates that the device ordinal supplied by the user does not
+     * correspond to a valid CUDA device.
+     */
+    { "CUDA_ERROR_INVALID_DEVICE (device specified is not a valid CUDA device)", 101 },
+
+
+    /**
+     * This indicates that the device kernel image is invalid. This can also
+     * indicate an invalid CUDA module.
+     */
+    { "CUDA_ERROR_INVALID_IMAGE", 200 },
+
+    /**
+     * This most frequently indicates that there is no context bound to the
+     * current thread. This can also be returned if the context passed to an
+     * API call is not a valid handle (such as a context that has had
+     * ::cuCtxDestroy() invoked on it). This can also be returned if a user
+     * mixes different API versions (i.e. 3010 context with 3020 API calls).
+     * See ::cuCtxGetApiVersion() for more details.
+     */
+    { "CUDA_ERROR_INVALID_CONTEXT", 201 },
+
+    /**
+     * This indicated that the context being supplied as a parameter to the
+     * API call was already the active context.
+     * \deprecated
+     * This error return is deprecated as of CUDA 3.2. It is no longer an
+     * error to attempt to push the active context via ::cuCtxPushCurrent().
+     */
+    { "CUDA_ERROR_CONTEXT_ALREADY_CURRENT", 202 },
+
+    /**
+     * This indicates that a map or register operation has failed.
+     */
+    { "CUDA_ERROR_MAP_FAILED", 205 },
+
+    /**
+     * This indicates that an unmap or unregister operation has failed.
+     */
+    { "CUDA_ERROR_UNMAP_FAILED", 206 },
+
+    /**
+     * This indicates that the specified array is currently mapped and thus
+     * cannot be destroyed.
+     */
+    { "CUDA_ERROR_ARRAY_IS_MAPPED", 207 },
+
+    /**
+     * This indicates that the resource is already mapped.
+     */
+    { "CUDA_ERROR_ALREADY_MAPPED", 208 },
+
+    /**
+     * This indicates that there is no kernel image available that is suitable
+     * for the device. This can occur when a user specifies code generation
+     * options for a particular CUDA source file that do not include the
+     * corresponding device configuration.
+     */
+    { "CUDA_ERROR_NO_BINARY_FOR_GPU", 209 },
+
+    /**
+     * This indicates that a resource has already been acquired.
+     */
+    { "CUDA_ERROR_ALREADY_ACQUIRED", 210 },
+
+    /**
+     * This indicates that a resource is not mapped.
+     */
+    { "CUDA_ERROR_NOT_MAPPED", 211 },
+
+    /**
+     * This indicates that a mapped resource is not available for access as an
+     * array.
+     */
+    { "CUDA_ERROR_NOT_MAPPED_AS_ARRAY", 212 },
+
+    /**
+     * This indicates that a mapped resource is not available for access as a
+     * pointer.
+     */
+    { "CUDA_ERROR_NOT_MAPPED_AS_POINTER", 213 },
+
+    /**
+     * This indicates that an uncorrectable ECC error was detected during
+     * execution.
+     */
+    { "CUDA_ERROR_ECC_UNCORRECTABLE", 214 },
+
+    /**
+     * This indicates that the ::CUlimit passed to the API call is not
+     * supported by the active device.
+     */
+    { "CUDA_ERROR_UNSUPPORTED_LIMIT", 215 },
+
+    /**
+     * This indicates that the ::CUcontext passed to the API call can
+     * only be bound to a single CPU thread at a time but is already 
+     * bound to a CPU thread.
+     */
+    { "CUDA_ERROR_CONTEXT_ALREADY_IN_USE", 216 },
+
+    /**
+     * This indicates that peer access is not supported across the given
+     * devices.
+     */
+    { "CUDA_ERROR_PEER_ACCESS_UNSUPPORTED", 217},
+
+    /**
+     * This indicates that the device kernel source is invalid.
+     */
+    { "CUDA_ERROR_INVALID_SOURCE", 300 },
+
+    /**
+     * This indicates that the file specified was not found.
+     */
+    { "CUDA_ERROR_FILE_NOT_FOUND", 301 },
+
+    /**
+     * This indicates that a link to a shared object failed to resolve.
+     */
+    { "CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND", 302 },
+
+    /**
+     * This indicates that initialization of a shared object failed.
+     */
+    { "CUDA_ERROR_SHARED_OBJECT_INIT_FAILED", 303 },
+
+    /**
+     * This indicates that an OS call failed.
+     */
+    { "CUDA_ERROR_OPERATING_SYSTEM", 304 },
+
+
+    /**
+     * This indicates that a resource handle passed to the API call was not
+     * valid. Resource handles are opaque types like ::CUstream and ::CUevent.
+     */
+    { "CUDA_ERROR_INVALID_HANDLE", 400 },
+
+
+    /**
+     * This indicates that a named symbol was not found. Examples of symbols
+     * are global/constant variable names, texture names }, and surface names.
+     */
+    { "CUDA_ERROR_NOT_FOUND", 500 },
+
+
+    /**
+     * This indicates that asynchronous operations issued previously have not
+     * completed yet. This result is not actually an error, but must be indicated
+     * differently than ::CUDA_SUCCESS (which indicates completion). Calls that
+     * may return this value include ::cuEventQuery() and ::cuStreamQuery().
+     */
+    { "CUDA_ERROR_NOT_READY", 600 },
+
+
+    /**
+     * An exception occurred on the device while executing a kernel. Common
+     * causes include dereferencing an invalid device pointer and accessing
+     * out of bounds shared memory. The context cannot be used }, so it must
+     * be destroyed (and a new one should be created). All existing device
+     * memory allocations from this context are invalid and must be
+     * reconstructed if the program is to continue using CUDA.
+     */
+    { "CUDA_ERROR_LAUNCH_FAILED", 700 },
+
+    /**
+     * This indicates that a launch did not occur because it did not have
+     * appropriate resources. This error usually indicates that the user has
+     * attempted to pass too many arguments to the device kernel, or the
+     * kernel launch specifies too many threads for the kernel's register
+     * count. Passing arguments of the wrong size (i.e. a 64-bit pointer
+     * when a 32-bit int is expected) is equivalent to passing too many
+     * arguments and can also result in this error.
+     */
+    { "CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES", 701 },
+
+    /**
+     * This indicates that the device kernel took too long to execute. This can
+     * only occur if timeouts are enabled - see the device attribute
+     * ::CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT for more information. The
+     * context cannot be used (and must be destroyed similar to
+     * ::CUDA_ERROR_LAUNCH_FAILED). All existing device memory allocations from
+     * this context are invalid and must be reconstructed if the program is to
+     * continue using CUDA.
+     */
+    { "CUDA_ERROR_LAUNCH_TIMEOUT", 702 },
+
+    /**
+     * This error indicates a kernel launch that uses an incompatible texturing
+     * mode.
+     */
+    { "CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING", 703 },
+    
+    /**
+     * This error indicates that a call to ::cuCtxEnablePeerAccess() is
+     * trying to re-enable peer access to a context which has already
+     * had peer access to it enabled.
+     */
+    { "CUDA_ERROR_PEER_ACCESS_ALREADY_ENABLED", 704 },
+
+    /**
+     * This error indicates that ::cuCtxDisablePeerAccess() is 
+     * trying to disable peer access which has not been enabled yet 
+     * via ::cuCtxEnablePeerAccess(). 
+     */
+    { "CUDA_ERROR_PEER_ACCESS_NOT_ENABLED", 705 },
+
+    /**
+     * This error indicates that the primary context for the specified device
+     * has already been initialized.
+     */
+    { "CUDA_ERROR_PRIMARY_CONTEXT_ACTIVE", 708 },
+
+    /**
+     * This error indicates that the context current to the calling thread
+     * has been destroyed using ::cuCtxDestroy }, or is a primary context which
+     * has not yet been initialized.
+     */
+    { "CUDA_ERROR_CONTEXT_IS_DESTROYED", 709 },
+
+    /**
+     * A device-side assert triggered during kernel execution. The context
+     * cannot be used anymore, and must be destroyed. All existing device 
+     * memory allocations from this context are invalid and must be 
+     * reconstructed if the program is to continue using CUDA.
+     */
+    { "CUDA_ERROR_ASSERT", 710 },
+
+        /**
+     * This error indicates that the hardware resources required to enable
+     * peer access have been exhausted for one or more of the devices 
+     * passed to ::cuCtxEnablePeerAccess().
+     */
+    { "CUDA_ERROR_TOO_MANY_PEERS", 711 },
+
+    /**
+     * This error indicates that the memory range passed to ::cuMemHostRegister()
+     * has already been registered.
+     */
+    { "CUDA_ERROR_HOST_MEMORY_ALREADY_REGISTERED", 712 },
+
+    /**
+     * This error indicates that the pointer passed to ::cuMemHostUnregister()
+     * does not correspond to any currently registered memory region.
+     */
+    { "CUDA_ERROR_HOST_MEMORY_NOT_REGISTERED", 713 },
+
+    /**
+     * This error indicates that the attempted operation is not permitted.
+     */
+    { "CUDA_ERROR_NOT_PERMITTED", 800 },
+
+    /**
+     * This error indicates that the attempted operation is not supported
+     * on the current system or device.
+     */
+    { "CUDA_ERROR_NOT_SUPPORTED", 801 },
+
+    /**
+     * This indicates that an unknown internal error has occurred.
+     */
+    { "CUDA_ERROR_UNKNOWN", 999 },
+    { NULL, -1 }
+};
+
+// This is just a linear search through the array, since the error_id's are not
+// always ocurring consecutively
+const char * getCudaDrvErrorString(CUresult error_id)
+{
+    int index = 0;
+    while (sCudaDrvErrorString[index].error_id != error_id && 
+           sCudaDrvErrorString[index].error_id != -1)
+    {
+        index++;
+    }
+    if (sCudaDrvErrorString[index].error_id == error_id)
+        return (const char *)sCudaDrvErrorString[index].error_string;
+    else
+        return (const char *)"CUDA_ERROR not found!";
+}
+
+#endif