Mexico City - Mariano Escobedo

Mariano Escobedo 510, Ciudad de Mexico, mexico, 11590

The Mexico City Mariano Escobedo Center is on the 12th floor and penthouse of a tall, slimline commercial building with bold vertical detailing giving it instant kerb-appeal.

Mexico City - Cygni Santa Fe

Alfonso Nápoles Gandara 50, Mexico City, mexico, 1210

The Mexico City Cygni Santa Fé Center is on the top floor of a four-story building that is one of Mexico City's foremost business addresses. It has landscaped grounds and an imposing entrance, and the center enjoys incredible views across to the high-rise skyline of Santa Fé, a leading district for financial services businesses.

Mexico City - Spaces Santa Fé

Antonio Dovalí Jaime #70, Santa Fe, MEXICO CITY, Mexico, 05300

Position your business at Antonio Dovali Jaime 70, Santa Fe, a prime commercial spot in Mexico City. This mixed-use building offers easy access to a hotel, a shopping mall, and even a heliport. Enjoy ample room for expansion in this flexible, spacious modern office space, located in the city's central business district.

Mexico City - Colonia Del Valle

Av. Insurgentes Sur N° 800 , Mexico City, Mexico, 3100

The Colonia Del Valle (HQ) Center is on the eighth floor of an attractive, 20-story steel-gray building on the Avenida de los Insurgentes. The landmark Mexicana de Aviatión Tower is nearby, and the World Trade Center (WTC) is only two blocks away.

Mexico City - Torre Angel

Paseo de la Reforma 350, Mexico City, mexico, 6600

The Mexico City Torre Angel Center is on the 10th and 11th floors of a prestigious curved, reflective high-rise building with magnificent views to The Angel, the iconic monument to independence on the Paseo de la Reforma.

Mexico City-Magenta Tower

17th floor, Paseo de la Reforma, Mexico City, Mexico, 06600

Elevate Your Business in a Premier Location with Breathtaking Views Establish your presence in the prestigious Magenta Tower, just steps from the Mexican Stock Exchange and surrounded by top-tier investment banks and Fortune 500 companies. Work with panoramic views of Mexico City from the 17th floor in a sleek, modern space designed for productivity and comfort. Impress your clients with upscale hospitality at nearby luxury hotels like the Marriott or Sheraton. Enjoy casual lunches at the on-site sandwich bar or explore gourmet dining options in the vibrant neighborhood.
Image of NobleProg Training Place, City Mexico City - Vasco de Quiroga Image of NobleProg Training Place, City Mexico City - Vasco de Quiroga Image of NobleProg Training Place, City Mexico City - Vasco de Quiroga

Mexico City - Vasco de Quiroga

Av. Vasco de Quiroga #4973 , Mexico City, Mexico, 05300

Easily access your workspace via the Terminal Centro Comercial Santa Fé Bus Stop, conveniently situated nearby. Additionally, greet visiting clients effortlessly at the Mexico City International Airport, located just over 26 kilometers away.

Mexico City-Calle Arquimedes 15

Arquímedes 15 Street, Mexico City, Mexico, 11560

Work your way in a premium business environment Discover a modern, comfortable, and adaptable workspace at our Arquímedes 15 location, strategically situated in the heart of the prestigious Polanco business district. Enjoy proximity to luxury hotels, upscale shopping malls, and gourmet restaurants — all just a short walk away. Commuting is easy with multiple transport options nearby, including the Auditorio subway station, dedicated bike lanes, and bus routes along the Reforma corridor, just one block from the center.

Mexico City-New York Life Tower

26th floor, Avenue Paseo de la Reforma 342, Mexico City, Mexico, 11560

Take in panoramic city views from a sleek, modern workspace Soar above central Mexico City from the 26th floor of the iconic 500-foot New York Life Tower. Set your business in motion with stunning views overlooking the vibrant Paseo de la Reforma. Unwind in the spacious lounge or connect with others at the on-site coffee bar over a quick bite. Once the day’s work is done, you’ll be in the heart of one of the city’s liveliest districts — surrounded by countless dining, entertainment, and nightlife options.

Subcategories (1)

CUDA (Compute Unified Device Architecture)

CUDA (Compute Unified Device Architecture)

Explore Our Courses

GPU Programming with OpenACC

 28 Hours
This instructor-led, live training in Mexico City (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 Mexico City (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 Mexico City (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 Mexico City (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 Mexico City (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 Mexico City (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 Mexico City (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 Mexico City (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 Mexico City (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 Mexico City 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

2025-05-19 09:30
28 hours
Mexico City-Magenta Tower
112,500 MXN (Online)
152,100 MXN (Classroom)

ROCm for Windows

2025-06-02 09:30
21 hours
Mexico City - Vasco de Quiroga
85,000 MXN (Online)
99,100 MXN (Classroom)

NVIDIA GPU Programming - Extended

2025-06-16 09:30
21 hours
Mexico City-Calle Arquimedes 15
99,900 MXN (Online)
153,900 MXN (Classroom)

GPU Programming - OpenCL vs CUDA vs ROCm

2025-06-30 09:30
28 hours
Mexico City-New York Life Tower
112,500 MXN (Online)
169,300 MXN (Classroom)

Introduction to GPU Programming

2025-07-14 09:30
21 hours
Mexico City - Mariano Escobedo
85,000 MXN (Online)
91,000 MXN (Classroom)

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