4 Questions
What is Intel DL Boost?
A feature that accelerates workloads when moving from 32-bit to 8-bit compute
What is the best instance to use for deep learning training on AWS?
Habana Gaudi DL1
What is an important factor to consider when choosing a model?
Data
What is the command to check whether an existing instance has Intel DL boost exposed?
lscpu
Study Notes
- Public cloud providers, such as Amazon Web Services, Microsoft Azure, and Google Cloud, offer different services that allow users to request instances on a pay-as-you-go basis.
- Users can choose between EC2 and Azure Virtual machines, or SageMaker, a fully managed machine learning service.
- The second option, AI-as-a-Service, uses services provided by Amazon that do not require the user to create any models or algorithms.
- The third option is to use Amazon's AI-as-a-Service, which offers the user access to predefined functions and services.
- Users can choose between different processors and software, depending on their needs.
- Hardware requirements for AI workloads depend on the specific instruction set that the processor supports.
- Intel DL Boost is a feature that is available on certain 2nd and 3rd Gen Intel Xeon Scalable processors.
- It enables you to achieve a four times speedup for any workload when you move from 32-bit to 8-bit compute.
- This instruction set is only available in 2nd and 3rd Gen Intel Xeon Scalable processors.
- You can check whether an existing instance has Intel DL boost exposed by running a command called lscpu.
- If you only need small to medium machine learning inference-based workloads, you don't need more than four virtual CPUs.
- For anything involving training, Intel offers the Habana Gaudi DL1 instances, which is specific to deep learning training on AWS.
- Different models have different requirements on resources, which impacts how you choose the cloud instance.
- On the left is CNN, which is computation intensive. On the right is the operational intensity, which is measured in flops per byte. CNN is the highest.
- There are different types of deep learning models with different characteristics.
- GPUs have more compute resources, but fewer memory resources.
- A CPU has much larger memory space than a GPU, and a CPU bus has much higher bandwidth and lower latency than a PCIe bus.
- Data is another important factor to consider when choosing a model.
- Real-time inference is important for applications where data movement is expensive.
Test your knowledge on cloud computing services, AI-as-a-Service, hardware requirements for AI workloads, and deep learning model characteristics. This quiz covers topics such as public cloud providers, machine learning services, processor features, and resource considerations for different models.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
