1.
질문 1By comparison, integrated GPUs use less heat than dedicated GPUs and share system memory directly with the CPU.
True
Integrated GPUs are less powerful and use a lower wattage. Another feature of integrated GPUs is that they share system memory with the host machine’s CPU.
CUDA is developed for Nvidia hardware.
3.
질문 3There is no way in the Windows OS to determine which type of GPUs are installed on the current machine.
False
There are numerous applications for Windows OS.
4.
질문 4The general pace of new Nvidia GPU architectures is which of the following?
Every 2 years
New GPU architectures are released every two years.
5.
질문 5Which measure is consistently improving each generation of Nvidia GPU?
GigaFLOPs per watt
It is Nvidia’s constant goal to lower wattage while maintaining or increasing the computational power, measured in Giga FlOating Point Operations (GigaFLOPs).
6.
질문 6
How can the communications between layers be characterized?
Applications and Libraries can communicate with Runtime and Driver APIs
This statement is correct, because different layers communicate bidirectionally.
7.
질문 7Which of these is not a compiled formats of CUDA code?
.cu
Feedback: .cu is a file extension, which is the same as .cpp or .c except that it indicates that it holds CUDA code. Therefore, this is a correct answer.
8.
질문 8
Using the nvcc command with the -h flag, does which of the following?
It shows help
9.
질문 9
The CUDA Framework’s Runtime API is written to be used directly in many programming languages.
False
This is the correct answer because CUDA Runtime API code needs to be written in C/C++.
10.
질문 10
Using the CUDA Driver API will require the developer to manage which of the following?
Contexts, devices, and programming modules
Feedback: Writing Driver API code requires developers to manage the three important components in order to execute code on Nvidia GPUs.
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