Question 1

Each warp of GPU receives a single instruction and "broadcasts" it to all of its threads. It is a ---- operation.

Accepted Answer

A) simd (single instruction multiple data) 
B) simt (single instruction multiple thread) 
C) sisd (single instruction single data) 
D) sist (single instruction single thread) 
A) simd (single instruction multiple data) 
B) simt (single instruction multiple thread) 
C) sisd (single instruction single data) 
D) sist (single instruction single thread)

Question 2

_______ became the first language specifically designed by a GPU Company to facilitate general purpose computing on ____.

Accepted Answer

A) python, gpus. 
B) c, cpus. 
C) cuda c, gpus. 
D) java, cpus. 
A) python, gpus. 
B) c, cpus. 
C) cuda c, gpus. 
D) java, cpus.

Question 3

Limitations of CUDA Kernel

Accepted Answer

A) recursion, call stack, static variable declaration 
B) no recursion, no call stack, no static variable declarations 
C) recursion, no call stack, static variable declaration 
D) no recursion, call stack, no static variable declarations 
A) recursion, call stack, static variable declaration 
B) no recursion, no call stack, no static variable declarations 
C) recursion, no call stack, static variable declaration 
D) no recursion, call stack, no static variable declarations

Question 4

The host processor spawns multithread tasks (or kernels as they are known in CUDA) onto the GPU device.

Accepted Answer

A) True 
 B)False

Each warp of GPU receives a single instruction and "broadcasts" it to all of its threads. It is a ---- operation.

___ became the first language specifically designed by a GPU Company to facilitate general purpose computing on .

Limitations of CUDA Kernel

The host processor spawns multithread tasks (or kernels as they are known in CUDA) onto the GPU device.

Understanding Cuda Kernel Code and Host GPU Interactions

Parallel Execution in CUDA, Sorting Algorithms, and Search Techniques

Characteristics and Operations in Parallel Programming

Communication Patterns and Algorithms in Distributed Systems

Communication Operations and Algorithms in Parallel Computing

Parallel Computing and Graph Algorithms

Parallel Processing and GPU Architecture

Computer Architecture and Multiprocessor Systems

Sorting Algorithms and Pipelined Systems

Algorithms and Parallel Formulations

Cuda Model, Parallelism, Memory System, and Communication Models

Parallel Communication and Runtime Analysis

Parallel Computing and GPU Architecture

Exploring Multiprocessor Systems and Parallel Algorithms

Parallel Processing and Algorithms

Distributed Systems and Computing

Filters

Exam 2: Nvidia CUDA and GPU Programming

Each warp of GPU receives a single instruction and "broadcasts" it to all of its threads. It is a ---- operation.

_______ became the first language specifically designed by a GPU Company to facilitate general purpose computing on ____.

Limitations of CUDA Kernel

The host processor spawns multithread tasks (or kernels as they are known in CUDA) onto the GPU device.

Understanding Cuda Kernel Code and Host GPU Interactions

Parallel Execution in CUDA, Sorting Algorithms, and Search Techniques

Characteristics and Operations in Parallel Programming

Communication Patterns and Algorithms in Distributed Systems

Communication Operations and Algorithms in Parallel Computing

Parallel Computing and Graph Algorithms

Parallel Processing and GPU Architecture

Computer Architecture and Multiprocessor Systems

Sorting Algorithms and Pipelined Systems

Algorithms and Parallel Formulations

Cuda Model, Parallelism, Memory System, and Communication Models

Parallel Communication and Runtime Analysis

Parallel Computing and GPU Architecture

Exploring Multiprocessor Systems and Parallel Algorithms

Parallel Processing and Algorithms

Distributed Systems and Computing

Filters

___ became the first language specifically designed by a GPU Company to facilitate general purpose computing on .