3. Parallel Processing
• Simultaneous use of multiple computing resources to solve a
computational problem by the use of multiple CPUs
• Problem is broken down into discrete parts that can be solve
concurrently
• Use to fulfill increasing demands for higher performance
5. Examples of Parallel Processing
• An Operating System running on the multicore processor is
an example of the parallel operating system
• Windows 7, 8, 10 are examples of operating systems which
do parallel processing
• Most modern CPUs exhibit parallel processing via the
concept of hyper-threading
6. Why Use Parallel Computing
• Saves Time
• Solves Larger Problems
• Cost Saving
• Provides Concurrency
7. Vector Processing
• In Computing, a vector processor or array processor is a central
processing unit (CPU) that implements an instruction set containing
instructions that operate on one-dimensional array of data called
vectors
• Vector Processors can greatly improve performance on certain
workloads, notably numerical simulation
• Two Popular Architectures :
SIMD & MIMD
8. SIMD (Single Instruction Multiple Data Stream)
• All Processing units execute the same instruction at any given
clock cycle
• Each processing unit operates on a different data element
• They have multiple processing/execution units and one control
unit
10. SIMD & INTEL
• MMX is a single-instruction, multiple data (SIMD) instruction set
designed by Intel
• Introduced in 1997 with its P5-Based Pentium line of microprocessors,
designated as “Pentium with MMX Technology”
INTEL MMX
PROCESSOR
11. Advantages of SIMD
• The main advantage of SIMD is that processing multiple data
elements at the same time, with a single instruction, can
dramatically improve performance
• If the SIMD system works by loading up eight data points at
once, the add operation being applied to the data will
happen to all eight values at the same time.
12. Disadvantages of SIMD
• Major Disadvantages of SIMD are as follows:-
1. Large Register Size
2. More Powerful Consumption
3. Requires Large Chip Area