Olete.in – MCQs, Mock Tests & Government Job Prep | High Performance Computing (HPC) High Performance Computing (HPC) MCQ Set 1

A CUDA program is comprised of two primary components: a host and a _____.

1. gpu??kernel
2. cpu??kernel
3. os
4. none of above

✅ Correct Answer: 1

The kernel code is dentified by the ________qualifier with void return type

1. _host_
2. __global__??
3. _device_
4. void

✅ Correct Answer: 2

Calling a kernel is typically referred to as _________.

1. kernel thread
2. kernel initialization
3. kernel termination
4. kernel invocation

✅ Correct Answer: 4

the BlockPerGrid and ThreadPerBlock parameters are related to the ________ model supported by CUDA.

1. host
2. kernel
3. thread??abstraction
4. None of the above

✅ Correct Answer: 3

_______ is Callable from the device only

1. _host_
2. __global__?? C.
3. _device_
4. None of the above

✅ Correct Answer: 3

____ is Callable from the host

1. _host_
2. __global__??
3. _device_
4. none of above

✅ Correct Answer: 2

______ is Callable from the host

1. _host_ B. C.
2. __global__??
3. _device_
4. None of the above

✅ Correct Answer: 1

CUDA supports ____________ in which code in a single thread is executed by all other threads.

1. tread division
2. tread termination
3. thread abstraction
4. None of the above

✅ Correct Answer: 3

. In CUDA, a single invoked kernel is referred to as a _____.

1. block
2. tread
3. grid
4. None of the above

✅ Correct Answer: 3

A grid is comprised of ________ of threads.

1. block
2. bunch
3. host
4. None of the above

✅ Correct Answer: 1

A block is comprised of multiple _______.

1. treads
2. bunch
3. host
4. None of the above

✅ Correct Answer: 1

a solution of the problem in representing the parallelismin algorithm is

1. cud
2. pta
3. cda
4. cuda

✅ Correct Answer: 4

Host codes in a CUDA application can not Reset a device

1. true
2. false
3. all
4. None of These

✅ Correct Answer: 2

Any condition that causes a processor to stall is called as _____.

1. hazard
2. page fault
3. system error
4. none of the above

✅ Correct Answer: 1

The time lost due to branch instruction is often referred to as _____.

1. latency
2. delay
3. branch penalty
4. None of the above

✅ Correct Answer: 3

___ method is used in centralized systems to perform out of order execution.

1. scorecard
2. score boarding
3. optimizing
4. redundancy

✅ Correct Answer: 2

The computer cluster architecture emerged as an alternative for ____.

1. isa
2. workstation
3. super computers
4. distributed systems

✅ Correct Answer: 3

NVIDIA CUDA Warp is made up of how many threads?

1. 512
2. 1024
3. 312
4. 32

✅ Correct Answer: 4

Out-of-order instructions is not possible on GPUs.

1. true
2. false
3. --
4. --

✅ Correct Answer: 2

CUDA supports programming in ....

1. c or c++ only
2. java, python, and more
3. c, c++, third party wrappers for java, python, and more
4. pascal

✅ Correct Answer: 3

FADD, FMAD, FMIN, FMAX are ----- supported by Scalar Processors of NVIDIA GPU.

1. 32-bit ieee floating point instructions
2. 32-bit integer instructions
3. both
4. none of the above

✅ Correct Answer: 1

Each streaming multiprocessor (SM) of CUDA herdware has ------ scalar processors (SP).

1. 1024
2. 128
3. 512
4. 8

✅ Correct Answer: 4

Each NVIDIA GPU has ------ Streaming Multiprocessors

1. 8
2. 1024
3. 512
4. 16

✅ Correct Answer: 4

CUDA provides ------- warp and thread scheduling. Also, the overhead of thread creation is on the order of ----.

1. programming-overhead”, 2 clock
2. zero-overhead”, 1 clock
3. 64, 2 clock
4. 32, 1 clock

✅ Correct Answer: 2

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

1. simd (single instruction multiple data)
2. simt (single instruction multiple thread)
3. sisd (single instruction single data)
4. sist (single instruction single thread)

✅ Correct Answer: 2

Limitations of CUDA Kernel

1. recursion, call stack, static variable declaration
2. no recursion, no call stack, no static variable declarations
3. recursion, no call stack, static variable declaration
4. no recursion, call stack, no static variable declarations

✅ Correct Answer: 2

What is Unified Virtual Machine

1. it is a technique that allow both cpu and gpu to read from single virtual machine, simultaneously.
2. it is a technique for managing separate host and device memory spaces.
3. it is a technique for executing device code on host and host code on device.
4. it is a technique for executing general purpose programs on device instead of host.

✅ Correct Answer: 1

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

1. python, gpus.
2. c, cpus.
3. cuda c, gpus.
4. java, cpus.

✅ Correct Answer: 3

The CUDA architecture consists of --------- for parallel computing kernels and functions.

1. risc instruction set architecture
2. cisc instruction set architecture
3. zisc instruction set architecture
4. ptx instruction set architecture

✅ Correct Answer: 4

CUDA stands for --------, designed by NVIDIA.

1. common union discrete architecture
2. complex unidentified device architecture
3. compute unified device architecture
4. complex unstructured distributed architecture

✅ Correct Answer: 3

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

1. true
2. false
3. ---
4. ---

✅ Correct Answer: 1

The NVIDIA G80 is a ---- CUDA core device, the NVIDIA G200 is a ---- CUDA core device, and the NVIDIA Fermi is a ---- CUDA core device

1. 28, 256, 512
2. 32, 64, 128
3. 64, 128, 256
4. 256, 512, 1024

✅ Correct Answer: 1

NVIDIA 8-series GPUs offer -------- .

1. 50-200 gflops
2. 200-400 gflops
3. 400-800 gflops
4. 800-1000 gflops

✅ Correct Answer: 1

IADD, IMUL24, IMAD24, IMIN, IMAX are ----------- supported by Scalar Processors of NVIDIA GPU.

1. 32-bit ieee floating point instructions
2. 32-bit integer instructions
3. both
4. none of the above

✅ Correct Answer: 2

CUDA Hardware programming model supports: a) fully generally data-parallel archtecture; b) General thread launch; c) Global load-store; d) Parallel data cache; e) Scalar architecture; f) Integers, bit operation

1. a,c,d,f
2. b,c,d,e
3. a,d,e,f
4. a,b,c,d,e,f

✅ Correct Answer: 4

In CUDA memory model there are following memory types available: a) Registers; b) Local Memory; c) Shared Memory; d) Global Memory; e) Constant Memory; f) Texture Memory.

1. a, b, d, f
2. a, c, d, e, f
3. a, b, c, d, e, f
4. b, c, e, f

✅ Correct Answer: 3

What is the equivalent of general C program with CUDA C: int main(void) { printf("Hello, World! "); return 0; }

1. int main ( void ) { kernel <<<1,1>>>(); printf("hello, world!\n"); return 0; }
2. __global__ void kernel( void ) { } int main ( void ) { kernel <<<1,1>>>(); printf("hello, world!\n"); return 0; }
3. __global__ void kernel( void ) { kernel <<<1,1>>>(); printf("hello, world!\n"); return 0; }
4. _global__ int main ( void ) { kernel <<<1,1>>>(); printf("hello, world!\n"); return 0; }

✅ Correct Answer: 2

Which function runs on Device (i.e. GPU): a) __global__ void kernel (void ) { } b) int main ( void ) { ... return 0; }

1. a
2. s
3. both a,b
4. ---

✅ Correct Answer: 1

If variable a is host variable and dev_a is a device (GPU) variable, to allocate memory to dev_a select correct statement:

1. cudamalloc( &dev_a, sizeof( int ) )
2. malloc( &dev_a, sizeof( int ) )
3. cudamalloc( (void**) &dev_a, sizeof( int ) )
4. malloc( (void**) &dev_a, sizeof( int ) )

✅ Correct Answer: 3

If variable a is host variable and dev_a is a device (GPU) variable, to copy input from variable a to variable dev_a select correct statement:

1. memcpy( dev_a, &a, size);
2. cudamemcpy( dev_a, &a, size, cudamemcpyhosttodevice );
3. memcpy( (void*) dev_a, &a, size);
4. cudamemcpy( (void*) &dev_a, &a, size, cudamemcpydevicetohost );

✅ Correct Answer: 2

Triple angle brackets mark in a statement inside main function, what does it indicates?

1. a call from host code to device code
2. a call from device code to host code
3. less than comparison
4. greater than comparison

✅ Correct Answer: 1

What makes a CUDA code runs in parallel

1. __global__ indicates parallel execution of code
2. main() function indicates parallel execution of code
3. kernel name outside triple angle bracket indicates excecution of kernel n times in parallel
4. . first parameter value inside triple angle bracket (n) indicates excecution of kernel n times in parallel

✅ Correct Answer: 4

In ___________, the number of elements to be sorted is small enough to fit into the process's main memory.

1. internal sorting
2. internal searching
3. external sorting
4. external searching

✅ Correct Answer: 1

_____________ algorithms use auxiliary storage (such as tapes and hard disks) for sorting because the number of elements to be sorted is too large to fit into memory.

1. internal sorting
2. internal searching
3. external sorting
4. external searching

✅ Correct Answer: 3

____ can be comparison-based or noncomparison-based.

1. searching
2. sorting
3. both a and b
4. none of above

✅ Correct Answer: 2

The fundamental operation of comparison-based sorting is ________.

1. compare-exchange
2. searching
3. sorting
4. swapping

✅ Correct Answer: 1

The performance of quicksort depends critically on the quality of the ______-.

1. non-pivote
2. pivot
3. center element
4. len of array

✅ Correct Answer: 2

The main advantage of ______ is that its storage requirement is linear in the depth of the state space being searched.

1. bfs
2. dfs
3. a and b
4. None of the above

✅ Correct Answer: 2

___ algorithms use a heuristic to guide search.

1. bfs
2. dfs
3. a and b
4. none of above

✅ Correct Answer: 1

Graph search involves a closed list, where the major operation is a _______

1. sorting
2. searching
3. lookup
4. None of the above

✅ Correct Answer: 3

Breadth First Search is equivalent to which of the traversal in the Binary Trees?

1. pre-order traversal
2. post-order traversal
3. level-order traversal
4. in-order traversal

✅ Correct Answer: 3

Time Complexity of Breadth First Search is? (V – number of vertices, E – number of edges)

1. o(v + e)
2. o(v)
3. o(e)
4. o(v*e)

✅ Correct Answer: 1

Which of the following is not an application of Breadth First Search?

1. when the graph is a binary tree
2. when the graph is a linked list
3. when the graph is a n-ary tree
4. when the graph is a ternary tree

✅ Correct Answer: 2

In BFS, how many times a node is visited?

1. once
2. twice
3. equivalent to number of indegree of the node
4. thrice

✅ Correct Answer: 3

Which of the following is not a stable sorting algorithm in its typical implementation.

1. insertion sort
2. merge sort
3. quick sort
4. bubble sort

✅ Correct Answer: 3

Which of the following is not true about comparison based sorting algorithms?

1. the minimum possible time complexity of a comparison based sorting algorithm is o(nlogn) for a random input array
2. any comparison based sorting algorithm can be made stable by using position as a criteria when two elements are compared
3. counting sort is not a comparison based sorting algortihm
4. heap sort is not a comparison based sorting algorithm.

✅ Correct Answer: 4

mathematically efficiency is

1. e=s/p
2. e=p/s
3. e*s=p/2
4. e=p+e/e

✅ Correct Answer: 1

Cost of a parallel system is sometimes referred to____ of product

1. work
2. processor time
3. both
4. None of the above

✅ Correct Answer: 3

Scaling Characteristics of Parallel Programs Ts is

1. increase
2. constant
3. decreases
4. none

✅ Correct Answer: 2

Speedup tends to saturate and efficiency _____ as a consequence of Amdahl’s law.

1. increase
2. constant
3. decreases
4. none

✅ Correct Answer: 3

Speedup obtained when the problem size is _______ linearlywith the number of processing elements.

1. increase
2. constant
3. decreases
4. depend on problem size

✅ Correct Answer: 1

The n × n matrix is partitioned among n processors, with each processor storing complete ___ of the matrix.

1. row
2. column
3. both
4. depend on processor

✅ Correct Answer: 1

cost-optimal parallel systems have an efficiency of ___

1. . 1
2. n
3. logn
4. complex

✅ Correct Answer: 1

The n × n matrix is partitioned among n2 processors such that each processor owns a _____ element.

1. n
2. 2n
3. single
4. double

✅ Correct Answer: 3

how many basic communication operations are used in matrix vector multiplication

1. 1
2. 2
3. 3
4. 4

✅ Correct Answer: 3

In DNS algorithm of matrix multiplication it used

1. 1d partition
2. 2d partition
3. 3d partition
4. both a,b

✅ Correct Answer: 3

In the Pipelined Execution, steps contain

1. normalization
2. communication
3. elimination
4. all

✅ Correct Answer: 4

the cost of the parallel algorithm is higher than the sequential run time by a factor of __

1. 2020-03-02 00:00:00
2. 2020-02-03 00:00:00
3. 3*2
4. 2/3+3/2

✅ Correct Answer: 1

The load imbalance problem in Parallel Gaussian Elimination: can be alleviated by using a ____ mapping

1. acyclic
2. cyclic
3. both
4. none

✅ Correct Answer: 2

A parallel algorithm is evaluated by its runtime in function of

1. the input size,
2. the number of processors
3. the communication parameters.
4. all

✅ Correct Answer: 4

For a problem consisting of W units of work, p__W processors can be used optimally.

1. <=
2. >=
3. <
4. >

✅ Correct Answer: 1

C(W)__Θ(W) for optimality (necessary condition).

1. >
2. <
3. <=
4. equals

✅ Correct Answer: 4

many interactions in oractical parallel programs occur in _____ pattern

1. well defined
2. zig-zac
3. reverse
4. straight

✅ Correct Answer: 1

efficient implementation of basic communication operation can improve

1. performance
2. communication
3. algorithm
4. all

✅ Correct Answer: 1

efficient use of basic communication operations can reduce

1. development effort and
2. software quality
3. both
4. none

✅ Correct Answer: 1

Group communication operations are built using_____ Messenging primitives.

1. point-to-point
2. one-to-all
3. all-to-one
4. none

✅ Correct Answer: 1

one processor has a piece of data and it need to send to everyone is

1. one -to-all
2. all-to-one
3. point -to-point
4. all of above

✅ Correct Answer: 1

the dual of one -to-all is

1. all-to-one reduction
2. one -to-all reduction
3. pnoint -to-point reducntion
4. none

✅ Correct Answer: 1

Data items must be combined piece-wise and the result made available at

1. target processor finally
2. target variable finatlalyrget receiver finally
3. both (a) and (b)
4. None of these

✅ Correct Answer: 1