CS621 Current Paper 2024 Solved by Izhar

Cs621 current paper 2024.solved by Izhar from swat mng01 campus.

MapReduce has three main phases:

1. Map
2. Sort
3. Reduce

MapReduce Example (based on Three Phases)

The canonical MapReduce Example: Word Count • Example corpus: Jane likes toast with jam Joe likes toast Joe burnt the toas

Decomposition Techniques:

i. Recursive Decomposition ii. Data Decomposition iii. Exploratory Decomposition iv. Speculative Decomposition

Static topology Connection Networks:

I. • RingHypercube (Loop) networks II. • Mesh III. • Torus IV. • Tree networks V. • Hypercubenetwork.

Introduction to GPU:

“Graphics Processing Unit ()GPU) is a chip or electrnic circuict capable of rendering graphics for

Display on an electronic device. GPUs work by using a method called parallel processing, where

Multiple processors handle seprate parts separate parts of the same task.” The world’s first GPU, the GeForce 256, was marketed by NVIDIA in 1999. These GPU chips can process a minimum of 10 million polygons per second and are used in nearly every computer on the market today.

Client-Centric Consistency Models Types:Names

i. Eventual Consistency ii. Monotonic Writes iii. Read Your Writes iv. Writes Follow Reads.

Data-centric Consistency Models Types Names:

I. Continuous Consistency II. Consistent Ordering of Operations III. Causal Consistency IV. Grouping Operations

Types of mutex

1. A normal mutex 2. A recursive mutex 3. Error check mutex.

Architecture of GPU

Parallel coprocessor to conventional CPUs Implement a SIMD structure, multiple threads running the same code.

• Thread local rigister
• Block local memory and control
• Global memory

Gris of Block of Threat

Global memory The CPU is the conventional multi-core processor with limited parallelism to exploit. The GPU has a many-core architecture that has hundreds of simple processing cores organized as multiprocessors. Each core can have one or more threads. Essentially, the CPU’s floating-point kernel computation role is largely offloaded to the manycore GPU. The CPU instructs the GPU to perform massive data processing.

• Scale code to hundreds of cores running thousands
• The task runs on the GPU independendly from the CPU.

MPI Basics:

Many parallel programs can be written using just these six functions, only two of which are nontrivial;

–MPI_INIT MPI_FINALIZE –MPI_COMM_SIZE –MPI_COMM_RANK –MPI_SEND –MPI_RECV