NVIDIA Software Stack & Developer Tools Flashcards

What distinguishes NVIDIA Nsight Compute from NVIDIA Nsight Systems?

Answer: Nsight Compute provides deep per-kernel GPU metrics; Nsight Systems delivers system-wide CPU+GPU timeline analysis

Nsight Compute is a GPU kernel profiler providing detailed hardware counter metrics per kernel, while Nsight Systems is a system-wide performance analyzer showing CPU, GPU, and memory activity over time.

Which of the following is included in the NVIDIA CUDA Toolkit?

Answer: The nvcc compiler, cuBLAS, cuDNN, Nsight tools, and CUDA runtime libraries

The CUDA Toolkit is a comprehensive development environment that includes the nvcc compiler, CUDA runtime, math libraries (cuBLAS, cuFFT, etc.), debugging and profiling tools, and sample code.

What type of operations does the cuFFT library accelerate on NVIDIA GPUs?

Answer: Fast Fourier Transform computations

cuFFT provides GPU-accelerated Fast Fourier Transform (FFT) routines compatible with the FFTW API, enabling signal processing and scientific computing workloads at high throughput.

What is the role of nvcc in NVIDIA GPU development?

Answer: The NVIDIA CUDA compiler that compiles CUDA C/C++ source into GPU-executable binaries

nvcc (NVIDIA CUDA Compiler) is the primary compilation tool in the CUDA Toolkit that separates device (GPU) code from host (CPU) code and compiles each with appropriate backends.

Which capability makes NVIDIA Triton Inference Server particularly valuable for production AI deployments?

Answer: It serves models from multiple frameworks (TensorRT, ONNX, PyTorch, TF) under a single standardized API

Triton Inference Server supports multiple model backends including TensorRT, ONNX Runtime, PyTorch TorchScript, TensorFlow, and Python, providing a single HTTP/gRPC serving API for all of them.

What types of errors does the NVIDIA compute-sanitizer tool (formerly cuda-memcheck) detect?

Answer: GPU memory access violations, race conditions, and initialization errors in CUDA applications

compute-sanitizer is a run-time error checking tool that detects out-of-bounds memory accesses, race conditions (via racecheck), memory leaks (memcheck), and uninitialized variable usage in CUDA kernels.

What is CUDA-GDB primarily used for in GPU application development?

Answer: Interactive debugging of CUDA applications at the thread and warp level

CUDA-GDB is an extension of the GNU Debugger (GDB) that allows developers to set breakpoints, inspect variables, and step through GPU kernel code at the thread and warp granularity.