Google Compute Engine
Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS).
Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.
Learn more
RunPod
RunPod provides a cloud infrastructure that enables seamless deployment and scaling of AI workloads with GPU-powered pods. By offering access to a wide array of NVIDIA GPUs, such as the A100 and H100, RunPod supports training and deploying machine learning models with minimal latency and high performance. The platform emphasizes ease of use, allowing users to spin up pods in seconds and scale them dynamically to meet demand. With features like autoscaling, real-time analytics, and serverless scaling, RunPod is an ideal solution for startups, academic institutions, and enterprises seeking a flexible, powerful, and affordable platform for AI development and inference.
Learn more
NVIDIA HPC SDK
The NVIDIA HPC Software Development Kit (SDK) offers a comprehensive suite of reliable compilers, libraries, and software tools that are crucial for enhancing developer efficiency as well as the performance and adaptability of HPC applications. This SDK includes C, C++, and Fortran compilers that facilitate GPU acceleration for HPC modeling and simulation applications through standard C++ and Fortran, as well as OpenACC® directives and CUDA®. Additionally, GPU-accelerated mathematical libraries boost the efficiency of widely used HPC algorithms, while optimized communication libraries support standards-based multi-GPU and scalable systems programming. The inclusion of performance profiling and debugging tools streamlines the process of porting and optimizing HPC applications, and containerization tools ensure straightforward deployment whether on-premises or in cloud environments. Furthermore, with compatibility for NVIDIA GPUs and various CPU architectures like Arm, OpenPOWER, or x86-64 running on Linux, the HPC SDK equips developers with all the necessary resources to create high-performance GPU-accelerated HPC applications effectively. Ultimately, this robust toolkit is indispensable for anyone looking to push the boundaries of high-performance computing.
Learn more
Mojo
Mojo 🔥 is an innovative programming language designed specifically for AI developers. It merges the simplicity of Python with the efficiency of C, enabling users to maximize the programmability of various AI hardware and expand AI models seamlessly. Developers can write in Python or delve deep into low-level programming without needing to work with C++ or CUDA. This allows for direct programming of diverse AI hardware components. Take full advantage of hardware capabilities, encompassing multiple cores, vector units, and specialized accelerator units, all thanks to a cutting-edge compiler and heterogeneous runtime. Experience performance levels comparable to C++ and CUDA while avoiding unnecessary complexity in your coding process. With Mojo, the future of AI development becomes more accessible and efficient than ever before.
Learn more
