NCA CUDA Programming & Parallel Computing

Question 1

What programming language is commonly used for CUDA development?

Accepted Answer

CUDA C/C++

Answer

CUDA C/C++ is the most commonly used programming language for CUDA development. It extends standard C/C++ with keywords and APIs that allow developers to define and launch functions (kernels) to be executed on the GPU. This integration enables seamless interaction between CPU host code and GPU device code, making it accessible for C/C++ programmers to leverage GPU acceleration.

Question 2

Which CUDA memory type is shared between threads in the same block?

Accepted Answer

Shared memory

Answer

Shared memory is a fast, on-chip memory that is explicitly managed by the programmer and shared among all threads within the same thread block. It provides very low-latency access, significantly faster than global memory, and is used for inter-thread communication and data sharing within a block. This allows threads to cooperate efficiently by sharing intermediate results without accessing slower global memory.

Question 3

What is a CUDA kernel?

Accepted Answer

A GPU function executed in parallel

Answer

In CUDA, a kernel is a function written in CUDA C/C++ that is executed on the GPU device by many threads in parallel. When a kernel is launched from the CPU (host), it specifies how many threads and blocks should execute it. Each thread then executes the kernel function independently, often operating on a different piece of data.

Question 4

What does occupancy mean in CUDA programming?

Accepted Answer

Ratio of active warps to max warps

Answer

Occupancy in CUDA programming refers to the ratio of the number of active warps on a Streaming Multiprocessor (SM) to the maximum number of warps that the SM can support. High occupancy indicates that the SM is effectively utilized, as it has many warps ready to execute, which helps hide memory latency and keep the execution units busy. Achieving optimal occupancy is crucial for maximizing GPU performance.

Question 5

Which CUDA API function launches kernels?

Accepted Answer

kernel<<<grid, block>>>

Answer

In CUDA, kernels are launched using a special syntax called the "execution configuration" or "chevron syntax": `kernel_name<<>>(arguments)`. `gridDim` specifies the dimensions of the grid of thread blocks, and `blockDim` specifies the dimensions of each thread block. This syntax is fundamental for defining how a kernel will be executed across the GPU's parallel architecture.

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NCA CUDA Programming & Parallel Computing