London - London City Centre

380 Wellington Street, London, Canada, N6A 5B5

The centre occupies the 6th floor of City Centre Building a conveniently-located corner complex in downtown London, Ontario.

West Toronto - Etobicoke

10 Four Seasons Place, Toronto, Canada, M9B 6H7

Etobicoke is a prestigious area located on the western fringe of Toronto, and is the cushion between Toronto and Mississauga. Easily accessible by public transportation (bus) and is 5 minutes from the local subway station.

Scarborough – 10 Milner Business Court

10 Milner Business Court, Scarborough, Canada, M1B 3C6

The Milner Court Centre occupies the third floor of a corner property. It is easily accessible by public transport, both by bus and the rapid transit system.

Oakville - Winston Park

2010 Winston Park Drive, Oakville, Canada, L6H 5R7

The Winston Park centre is located close to both the Queen Elizabeth Way and Ontario 403 giving easy access for Burlington and Hamilton to the west and Mississauga and Toronto to the East.

Brampton - Brampton County Court

2 County Court Blvd, Brampton, Canada, L6W 3W

The Brampton County Court business centre in Ontario is located in a modern building in the downtown business district, near the Grenville and William Davis Court House.

Barrie - 49 High Street

49 High Street, Barrie, Canada, L4N 5J4

Balance work and leisure from our office space at 49 High Street. Barrie has a bustling commercial heart and enjoys great connectivity – our central office space is just a few minutes’ drive from Highway 400

Waterloo - 180 Northfield Drive West

180 Northfield Drive West, Waterloo, Canada, N2L 0C7

Maximise opportunities in this forward-thinking city, a knowledge center home to several tech giants. Our well-connected 180 Northfield Drive West centre is on the city's Corporate Campus near the prestigious University of Waterloo.

Kitchener - 22 Frederick Street

22 Frederick Street, Kitchener, canada, N2H 6M6

Prominent office space in downtown location Establish your business in the heart of downtown Kitchener. Work alongside leading finance and insurance companies at our 22 Frederick Street offices on the corner of Frederick Street, giving you easy access to local amenities.

Brampton - 2 County Court

2 County Court Boulevard, Brampton, Canada, L6W 3W8

Look to the future with an office space at 2 County Court, a building with outstanding sustainability credentials. The third largest city in Greater Toronto enjoys great transport links, while Toronto’s international airport is under 10 miles away.

Richmond Hill - The Business Exchange

9225 Leslie Street, Richmond Hill, Canada, L4B 3H6

Place your business in the peaceful surroundings of Richmond Hill, home to leading global brands. Located in the northern suburbs, our The Business Exchange workspace is just a 30-minute drive from central Toronto and the International Airport.

Ottawa - Albert & Metcalfe

116 Albert Street, Ottawa, Canada, K1P 5G3

Across the street from the World Exchange Plaza. The Ottawa Shaw Centre and CF Rideau Centre shopping mall 10 minutes away.

49 High Street

3rd floor, Dunlop Street West​, Barrie, Canada, L4N 1A8

A Perfect Balance of Work and Leisure by Lake Simcoe Combine productivity with relaxation in our office space at 49 High Street. Located in the vibrant commercial center of Barrie, this office offers excellent connectivity, with Highway 400 just a short drive away. Work efficiently in a modern brick building featuring a glass-fronted entrance, beautifully designed workspaces, and curated artwork in every meeting room. After a productive day, enjoy the nearby restaurants or take a leisurely walk to Heritage Park by the waterfront for some fresh air and relaxation.

Toronto - Toronto Street

36 Toronto Street, Toronto, Canada, M5C 2C5

Steps away from Toronto's prestigious financial core. Fast link to Pearson International Airport - less than 30 minutes away.

Ottawa - 343 Preston

Regus, 343 Preston Street, Ottawa, Canada, K1S 1N4

On the top floor of a distinctive office tower that's highly visible from Highway 417, you will find Regus 343 Preston Centre in Ottawa. Only a 10 minute drive from downtown Ottawa, a short stroll away from Downs Lake, and located near the lively intersection of Preston Gladstone in Little Italy.

Mississauga - Airways

5925 Airport Road, Mississauga, Canada, L4V 1W1

Airways is a beautiful center located at 5925 Airport Road, directly across from Toronto Pearson International Airport offering shuttle services. Adjacent to Highways 409 and 427, our center is easily accessible.

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CUDA (Compute Unified Device Architecture)

Explore Our Courses

GPU Programming with OpenACC

 28 Hours
This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use OpenACC to program heterogeneous devices and exploit their parallelism. By the end of this training, participants will be able to:
  • Set up an OpenACC development environment.
  • Write and run a basic OpenACC program.
  • Annotate code with OpenACC directives and clauses.
  • Use OpenACC API and libraries.
  • Profile, debug, and optimize OpenACC programs.
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Introduction to GPU Programming

 21 Hours
This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to learn the basics of GPU programming and the main frameworks and tools for developing GPU applications.
  • By the end of this training, participants will be able to:
    Understand the difference between CPU and GPU computing and the benefits and challenges of GPU programming.
  • Choose the right framework and tool for their GPU application.
  • Create a basic GPU program that performs vector addition using one or more of the frameworks and tools.
  • Use the respective APIs, languages, and libraries to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
  • Use the respective memory spaces, such as global, local, constant, and private, to optimize data transfers and memory accesses.
  • Use the respective execution models, such as work-items, work-groups, threads, blocks, and grids, to control the parallelism.
  • Debug and test GPU programs using tools such as CodeXL, CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
  • Optimize GPU programs using techniques such as coalescing, caching, prefetching, and profiling.
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GPU Programming - OpenCL vs CUDA vs ROCm

 28 Hours
This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use different frameworks for GPU programming and compare their features, performance, and compatibility. By the end of this training, participants will be able to:
  • Set up a development environment that includes OpenCL SDK, CUDA Toolkit, ROCm Platform, a device that supports OpenCL, CUDA, or ROCm, and Visual Studio Code.
  • Create a basic GPU program that performs vector addition using OpenCL, CUDA, and ROCm, and compare the syntax, structure, and execution of each framework.
  • Use the respective APIs to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
  • Use the respective languages to write kernels that execute on the device and manipulate data.
  • Use the respective built-in functions, variables, and libraries to perform common tasks and operations.
  • Use the respective memory spaces, such as global, local, constant, and private, to optimize data transfers and memory accesses.
  • Use the respective execution models to control the threads, blocks, and grids that define the parallelism.
  • Debug and test GPU programs using tools such as CodeXL, CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
  • Optimize GPU programs using techniques such as coalescing, caching, prefetching, and profiling.
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ROCm for Windows

 21 Hours
This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to install and use ROCm on Windows to program AMD GPUs and exploit their parallelism. By the end of this training, participants will be able to:
  • Set up a development environment that includes ROCm Platform, a AMD GPU, and Visual Studio Code on Windows.
  • Create a basic ROCm program that performs vector addition on the GPU and retrieves the results from the GPU memory.
  • Use ROCm API to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
  • Use HIP language to write kernels that execute on the GPU and manipulate data.
  • Use HIP built-in functions, variables, and libraries to perform common tasks and operations.
  • Use ROCm and HIP memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory accesses.
  • Use ROCm and HIP execution models to control the threads, blocks, and grids that define the parallelism.
  • Debug and test ROCm and HIP programs using tools such as ROCm Debugger and ROCm Profiler.
  • Optimize ROCm and HIP programs using techniques such as coalescing, caching, prefetching, and profiling.
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AMD GPU Programming

 28 Hours
This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use ROCm and HIP to program AMD GPUs and exploit their parallelism. By the end of this training, participants will be able to:
  • Set up a development environment that includes ROCm Platform, a AMD GPU, and Visual Studio Code.
  • Create a basic ROCm program that performs vector addition on the GPU and retrieves the results from the GPU memory.
  • Use ROCm API to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
  • Use HIP language to write kernels that execute on the GPU and manipulate data.
  • Use HIP built-in functions, variables, and libraries to perform common tasks and operations.
  • Use ROCm and HIP memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory accesses.
  • Use ROCm and HIP execution models to control the threads, blocks, and grids that define the parallelism.
  • Debug and test ROCm and HIP programs using tools such as ROCm Debugger and ROCm Profiler.
  • Optimize ROCm and HIP programs using techniques such as coalescing, caching, prefetching, and profiling.
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GPU Programming with CUDA

 28 Hours
This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use CUDA to program NVIDIA GPUs and exploit their parallelism. By the end of this training, participants will be able to:
  • Set up a development environment that includes CUDA Toolkit, a NVIDIA GPU, and Visual Studio Code.
  • Create a basic CUDA program that performs vector addition on the GPU and retrieves the results from the GPU memory.
  • Use CUDA API to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
  • Use CUDA C/C++ language to write kernels that execute on the GPU and manipulate data.
  • Use CUDA built-in functions, variables, and libraries to perform common tasks and operations.
  • Use CUDA memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory accesses.
  • Use CUDA execution model to control the threads, blocks, and grids that define the parallelism.
  • Debug and test CUDA programs using tools such as CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
  • Optimize CUDA programs using techniques such as coalescing, caching, prefetching, and profiling.
97% de clients satisfaits. 
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Administration of CUDA

 35 Hours
This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level system administrators and IT professionals who wish to install, configure, manage, and troubleshoot CUDA environments. By the end of this training, participants will be able to:
  • Understand the architecture, components, and capabilities of CUDA.
  • Install and configure CUDA environments.
  • Manage and optimize CUDA resources.
  • Debug and troubleshoot common CUDA issues.
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GPU Programming with OpenCL

 28 Hours
This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use OpenCL to program heterogeneous devices and exploit their parallelism. By the end of this training, participants will be able to:
  • Set up a development environment that includes OpenCL SDK, a device that supports OpenCL, and Visual Studio Code.
  • Create a basic OpenCL program that performs vector addition on the device and retrieves the results from the device memory.
  • Use OpenCL API to query device information, create contexts, command queues, buffers, kernels, and events.
  • Use OpenCL C language to write kernels that execute on the device and manipulate data.
  • Use OpenCL built-in functions, extensions, and libraries to perform common tasks and operations.
  • Use OpenCL host and device memory models to optimize data transfers and memory accesses.
  • Use OpenCL execution model to control the work-items, work-groups, and ND-ranges.
  • Debug and test OpenCL programs using tools such as CodeXL, Intel VTune, and NVIDIA Nsight.
  • Optimize OpenCL programs using techniques such as vectorization, loop unrolling, local memory, and profiling.
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GPU Programming with CUDA and Python

 14 Hours
This instructor-led, live training in Ontario (online or onsite) is aimed at intermediate-level developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs. By the end of this training, participants will be able to:
  • Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
  • Create, compile and launch custom CUDA kernels.
  • Manage GPU memory.
  • Convert a CPU based application into a GPU-accelerated application.
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NVIDIA GPU Programming - Extended

 21 Hours
This instructor-led, live training course in Ontario covers how to program GPUs for parallel computing, how to use various platforms, how to work with the CUDA platform and its features, and how to perform various optimization techniques using CUDA. Some of the applications include deep learning, analytics, image processing and engineering applications.
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Testimonials (2)

Very interactive with various examples, with a good progression in complexity between the start and the end of the training.

Jenny - Andheo

Course - GPU Programming with CUDA and Python

Trainers energy and humor.

Tadeusz Kaluba - Nokia Solutions and Networks Sp. z o.o.

Course - NVIDIA GPU Programming - Extended

Upcoming Courses

GPU Programming with CUDA and Python

2025-05-28 09:30
14 hours
49 High Street
CA$ 3,514 (Online)
CA$ 5,514 (Classroom)

Administration of CUDA

2025-06-16 09:30
35 hours
49 High Street
CA$ 8,784 (Online)
CA$ 13,784 (Classroom)

GPU Programming - OpenCL vs CUDA vs ROCm

2025-06-30 09:30
28 hours
49 High Street
CA$ 7,027 (Online)
CA$ 11,027 (Classroom)

Introduction to GPU Programming

2025-07-09 09:30
21 hours
49 High Street
CA$ 5,270 (Online)
CA$ 8,270 (Classroom)

GPU Programming with OpenCL

2025-07-28 09:30
28 hours
49 High Street
CA$ 7,027 (Online)
CA$ 11,027 (Classroom)

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