fixed typos in oneapi Jupyter Notebooks (oneapi-src#936)

Author: krisrak

DirectProgramming/DPC++/Jupyter/oneapi-essentials-training/README.md

@@ -6,7 +6,7 @@
 |:---                               |:---
 | OS                                | Linux* Ubuntu 18.04, 20 Windows* 10
 | Hardware                          | Skylake with GEN9 or newer
-| Software                          | Intel® oneAPI DPC++ Compiler, Jupyter Notebooks, Intel Devcloud
+| Software                          | Intel® oneAPI DPC++ Compiler, Jupyter Notebooks, Intel DevCloud
 
 ## Purpose
 The Jupyter Notebooks in this training shows challenges of heterogenous programming and how SYCL programming language can solve application development across CPUs, GPUs and FPGAs. 
@@ -15,7 +15,7 @@ These training modules teach basics of SYCL programming to offload computation t
 
 Modules also teach usage of Intel oneAPI Data Parallel C++ Library to simplify heterogenous programming and tools usage. Debugger tools and Performance analysis tools like Intel VTune Profiler and Intel Advisor.
 
-Also, it familiarizes you with the use of Jupyter notebooks as a front-end for all training exercises. This workshop is designed to be used on the Devcloud and includes details on submitting batch jobs on the Devcloud environment.
+Also, it familiarizes you with the use of Jupyter notebooks as a front-end for all training exercises. This workshop is designed to be used on the DevCloud and includes details on submitting batch jobs on the DevCloud environment.
 
 At the end of this course you will be able to:
 
@@ -40,9 +40,9 @@ Third party program Licenses can be found here: [third-party-programs.txt](https
 |[oneAPI Introduction](01_oneAPI_Intro/oneAPI_Intro.ipynb)| + Introduction and Motivation for SYCL.<br>+ SYCL __Hello World__<br>+ Compiling SYCL and __DevCloud__ Usage
 |[SYCL Program Structure](02_DPCPP_Program_Structure/DPCPP_Program_Structure.ipynb)| + __SYCL Classes__ - device, device_selector, queue, basic kernels and ND-Range kernels, Buffers-Accessor memory model<br>+ SYCL __Code Anatomy__<br>+ Implicit __Dependency__ with Accessors, __Synchronization__ with Host Accessor and Buffer Destruction<br>+ Creating __Custom__ Device Selector<br>+ ___Lab Exercise___: Vector Increment to Vector Add
 |[SYCL Unified Shared Memory](03_DPCPP_Unified_Shared_Memory/Unified_Shared_Memory.ipynb)|+ What is Unified Shared Memory(USM) and Motivation<br>+ __Implicit and Explicit USM__ code example<br>+ Handling __data dependency__ using depends_on() and ordered queues<br>+ ___Lab Exercise___: Unified Shared Memory
-|[SYCL Sub Groups](04_DPCPP_Sub_Groups/Sub_Groups.ipynb)| + What is Sub-Goups and Motivation<br>+ Quering for __sub-group info__<br>+ Sub-group __shuffle algorithms__<br>+ Sub-group __group algorithms__<br>+ ___Lab Exercise___: Sub-Groups | 90 min |
+|[SYCL Sub Groups](04_DPCPP_Sub_Groups/Sub_Groups.ipynb)| + What is Sub-Groups and Motivation<br>+ Querying for __sub-group info__<br>+ Sub-group __shuffle algorithms__<br>+ Sub-group __group algorithms__<br>+ ___Lab Exercise___: Sub-Groups | 90 min |
 |[SYCL Kernel Reductions](08_DPCPP_Reduction/Reductions.ipynb)|+ What are Reductions<br>+ Challenges with parallelizing reductions<br>+ __sycl::reduce_over_group__ function for sub-groups and work-groups<br>+ __sycl::reduction__ object in parallel_for<br>+ ___Lab Exercise___: Kernel Reductions 
-|[SYCL Buffers and Accessors in depth](09_DPCPP_Buffers_And_Accessors_Indepth/DPCPP_Buffers_accessors.ipynb)| + Bufers and Accessors<br>+ Buffer properties and usecases<br>+ Create Sub-buffers<br>+ Host accessors and usecases<br>+ ___Lab Exercise___: Buffers and Accessors
+|[SYCL Buffers and Accessors in depth](09_DPCPP_Buffers_And_Accessors_Indepth/DPCPP_Buffers_accessors.ipynb)| + Buffers and Accessors<br>+ Buffer properties and usecases<br>+ Create Sub-buffers<br>+ Host accessors and usecases<br>+ ___Lab Exercise___: Buffers and Accessors
 |[SYCL Task Scheduling and Data Dependency](10_DPCPP_Graphs_Scheduling_Data_management/DPCPP_Task_Scheduling_Data_dependency.ipynb)| + Different types of data dependency handling<br>+ Execution of graph scheduling<br>+ modes of dependencies in Graphs scheduling<br>+ ___Lab Exercise___: Task Scheduling
 |[Intel® oneAPI DPC++ Library (oneDPL)](07_DPCPP_Library/oneDPL_Introduction.ipynb)| + Introduction to Intel oneAPI DPC++ Library (oneDPL)<br>+ ___Lab Exercise___: Gamma Correction with oneDPL
 |[Intel® Advisor](05_Intel_Advisor/offload_advisor.ipynb)| + __Offload Advisor__ Tool usage and command-line options<br>+ ___Lab Exercise___: Generate Offload Advisor Report<br>+ __Roofline Analysis__ and command-line options<br>+ ___Lab Exercise___: Generate Roofline Report
@@ -67,8 +67,8 @@ The Jupyter Notebooks can be downloaded locally to computer and accessed:
 
 #### Access using Intel DevCloud
 
-The Jupyter notebooks are tested and can be run on Intel Devcloud without any installation necessary, below are the steps to access these Jupyter notebooks on Intel Devcloud:
-1. Register on [Intel Devcloud](https://devcloud.intel.com/oneapi)
+The Jupyter notebooks are tested and can be run on Intel DevCloud without any installation necessary, below are the steps to access these Jupyter notebooks on Intel DevCloud:
+1. Register on [Intel DevCloud](https://devcloud.intel.com/oneapi)
 2. Login, Get Started and Launch Jupyter Lab
 3. Open Terminal in Jupyter Lab and git clone the repo and access the Notebooks
 

DirectProgramming/DPC++/Jupyter/oneapi-essentials-training/TeacherKit.ipynb

@@ -94,9 +94,9 @@
     "|[Challenges in Heterogenous Computing](01_oneAPI_Intro/oneAPI_Intro.ipynb)| + Introduction and Motivation for SYCL.<br>+ SYCL __Hello World__<br>+ Compiling SYCL and __DevCloud__ Usage | 60 min |\n",
     "|[SYCL Program Structure](02_DPCPP_Program_Structure/DPCPP_Program_Structure.ipynb)| + __SYCL Classes__ - device, device_selector, queue, basic kernels and ND-Range kernels, Buffers-Accessor memory model<br>+ SYCL __Code Anatomy__<br>+ Implicit __Dependency__ with Accessors, __Synchronization__ with Host Accessor and Buffer Destruction<br>+ Creating __Custom__ Device Selector<br>+ ___Lab Exercise___: Vector Increment to Vector Add | 120 min |\n",
     "|[SYCL Unified Shared Memory](03_DPCPP_Unified_Shared_Memory/Unified_Shared_Memory.ipynb)|+ What is Unified Shared Memory(USM) and Motivation<br>+ __Implicit and Explicit USM__ code example<br>+ Handling __data dependency__ using depends_on() and ordered queues<br>+ ___Lab Exercise___: Unified Shared Memory | 90 min |\n",
-    "|[SYCL Sub Groups](04_DPCPP_Sub_Groups/Sub_Groups.ipynb)| + What is Sub-Goups and Motivation<br>+ Quering for __sub-group info__<br>+ Sub-group __shuffle algorithms__<br>+ Sub-group __group algorithms__<br>+ ___Lab Exercise___: Sub-Groups | 90 min |\n",
+    "|[SYCL Sub Groups](04_DPCPP_Sub_Groups/Sub_Groups.ipynb)| + What is Sub-Groups and Motivation<br>+ Querying for __sub-group info__<br>+ Sub-group __shuffle algorithms__<br>+ Sub-group __group algorithms__<br>+ ___Lab Exercise___: Sub-Groups | 90 min |\n",
     "|[SYCL Kernel Reductions](08_DPCPP_Reduction/Reductions.ipynb)|+ What are Reductions<br>+ Challenges with parallelizing reductions<br>+ __sycl::reduce_over_group__ function for sub-groups and work-groups<br>+ __sycl::reduction__ object in parallel_for<br>+ ___Lab Exercise___: Kernel Reductions | 90 min|\n",
-    "|[SYCL Buffers and Accessors in depth](09_DPCPP_Buffers_And_Accessors_Indepth/DPCPP_Buffers_accessors.ipynb)| + Bufers and Accessors<br>+ Buffer properties and usecases<br>+ Create Sub-buffers<br>+ Host accessors and usecases<br>+ ___Lab Exercise___: Buffers and Accessors | 120 min |\n",
+    "|[SYCL Buffers and Accessors in depth](09_DPCPP_Buffers_And_Accessors_Indepth/DPCPP_Buffers_accessors.ipynb)| + Buffers and Accessors<br>+ Buffer properties and usecases<br>+ Create Sub-buffers<br>+ Host accessors and usecases<br>+ ___Lab Exercise___: Buffers and Accessors | 120 min |\n",
     "|[SYCL Task Scheduling and Data Dependency](10_DPCPP_Graphs_Scheduling_Data_management/DPCPP_Task_Scheduling_Data_dependency.ipynb)| + Different types of data dependency handling<br>+ Execution of graph scheduling<br>+ modes of dependencies in Graphs scheduling<br>+ ___Lab Exercise___: Task Scheduling | 120 min|\n",
     "|[Intel® oneAPI DPC++ Library (oneDPL)](07_DPCPP_Library/oneDPL_Introduction.ipynb)| + Introduction to Intel oneAPI DPC++ Library (oneDPL)<br>+ ___Lab Exercise___: Gamma Correction with oneDPL | 120 min |\n",
     "|[Intel® Advisor](05_Intel_Advisor/offload_advisor.ipynb)| + __Offload Advisor__ Tool usage and command-line options<br>+ ___Lab Exercise___: Generate Offload Advisor Report<br>+ __Roofline Analysis__ and command-line options<br>+ ___Lab Exercise___: Generate Roofline Report | 120 min |\n",