This document discusses parallel processing and different types of multiprocessor systems. It describes tightly and loosely coupled systems, as well as coarse-grained, medium-grained, and fine-grained parallelism. Shared memory and distributed memory architectures are covered, along with interconnection structures like buses, crossbar switches, and multistage networks. Memory organization and communication in parallel systems concludes the document.
This slide contain the description about the various technique related to parallel Processing(vector Processing and array processor), Arithmetic pipeline, Instruction Pipeline, SIMD processor, Attached array processor
This slide contain the description about the various technique related to parallel Processing(vector Processing and array processor), Arithmetic pipeline, Instruction Pipeline, SIMD processor, Attached array processor
3D X Point Innovation by Intel Corporation incSooraj Vasudev
It is a new technology developing by Intel, one of the worlds semiconductor manufacturing company.
3D X Point is a new memory technology which would emerge soon. It is fast and efficient.
Hyper-threading or Hyper-Threading Technology(HTT), is actually Intel’s
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MODULE III Parallel Processors and Memory Organization 15 Hours
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Case Study: Instruction sets of some common CPUs - Design of a simple hypothetical CPU- A
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LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
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Bob Boule
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GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
Lecture 47
1. Parallel Processing 1 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
Overview
Parallel Processing
Pipelining
Characteristics of Multiprocessors
Interconnection Structures
Inter processor Arbitration
Inter processor Communication and Synchronization
2. Parallel Processing 2 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
Coupling of Processors
Tightly Coupled System
- Tasks and/or processors communicate in a highly synchronized fashion
- Communicates through a common shared memory
- Shared memory system
Loosely Coupled System
- Tasks or processors do not communicate in a synchronized fashion
- Communicates by message passing packets
- Overhead for data exchange is high
- Distributed memory system
3. Parallel Processing 3 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
Granularity of Parallelism
Granularity of Parallelism
Coarse-grain
- A task is broken into a handful of pieces, each of which is executed by a powerful
processor
- Processors may be heterogeneous
- Computation/communication ratio is very high
Medium-grain
- Tens to few thousands of pieces
- Processors typically run the same code
- Computation/communication ratio is often hundreds or more
Fine-grain
- Thousands to perhaps millions of small pieces, executed by very
small, simple processors or through pipelines
- Processors typically have instructions broadcasted to them
- Compute/communicate ratio often near unity
4. Parallel Processing 4 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
Memory
Network
Processors
Memory
SHARED MEMORY
Network
Processors/Memory
DISTRIBUTED MEMORY
Shared (Global) Memory
- A Global Memory Space accessible by all processors
- Processors may also have some local memory
Distributed (Local, Message-Passing) Memory
- All memory units are associated with processors
- To retrieve information from another processor's memory a message must be sent there
Uniform Memory
- All processors take the same time to reach all memory locations
Nonuniform (NUMA) Memory
- Memory access is not uniform
5. Parallel Processing 5 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
Shared Memory Multiprocessors
Interconnection Network
. . .
. . .P PP
M MM
Buses,
Multistage IN,
Crossbar Switch
Characteristics
All processors have equally direct access to one large memory address space
Example systems
- Bus and cache-based systems: Sequent Balance, Encore Multimax
- Multistage IN-based systems: Ultracomputer, Butterfly, RP3, HEP
- Crossbar switch-based systems: C.mmp, Alliant FX/8
Limitations
Memory access latency; Hot spot problem
6. Parallel Processing 6 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
Message Passing MultiProcessors
Characteristics
- Interconnected computers
- Each processor has its own memory, and communicate via message-passing
Example systems
- Tree structure: Teradata, DADO
- Mesh-connected: Rediflow, Series 2010, J-Machine
- Hypercube: Cosmic Cube, iPSC, NCUBE, FPS T Series, Mark III
Limitations
- Communication overhead; Hard to programming
Message-Passing Network
. . .P PP
M M M. . .
Point-to-point connections
7. Parallel Processing 7 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
Interconnection Structure
* Time-Shared Common Bus
* Multiport Memory
* Crossbar Switch
* Multistage Switching Network
* Hypercube System
Bus
All processors (and memory) are connected to a common bus or busses
- Memory access is fairly uniform, but not very scalable
8. Parallel Processing 8 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
BUS
- A collection of signal lines that carry module-to-module communication
- Data highways connecting several digital system elements
Operations of Bus
M3 wishes to communicate with S5
[1] M3 sends signals (address) on the bus that causes
S5 to respond
[2] M3 sends data to S5 or S5 sends data to
M3(determined by the command line)
Master Device: Device that initiates and controls the communication
Slave Device: Responding device
Multiple-master buses
-> Bus conflict
-> need bus arbitration
Devices
M3 S7 M6 S5 M4
S2
9. Parallel Processing 9 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
System Bus Structure for Multiprocessor
Common
Shared
Memory
System
Bus
Controller
CPU IOP
Local
Memory
System
Bus
Controller
CPU
Local
Memory
System
Bus
Controller
CPU IOP
Local
Memory
Local Bus
SYSTEM BUS
Local Bus Local Bus
10. Parallel Processing 10 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
Multi Port Memory
Multiport Memory Module
- Each port serves a CPU
Memory Module Control Logic
- Each memory module has control logic
- Resolve memory module conflicts Fixed priority among CPUs
Advantages
- Multiple paths -> high transfer rate
Disadvantages
- Memory control logic
- Large number of cables and
connections
MM 1 MM 2 MM 3 MM 4
CPU 1
CPU 2
CPU 3
CPU 4
Memory Modules
12. Parallel Processing 12 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
Multi Stage Switching Network
A
B
0
1
A connected to 0
A
B
0
1
A connected to 1
A
B
0
1
B connected to 0
A
B
0
1
B connected to 1
Interstage Switch
14. Parallel Processing 14 Lecture 47
CSE 211, Computer Organization and Architecture Harjeet Kaur, CSE/IT
HyperCube Interconnection
- p = 2n
- processors are conceptually on the corners of a
n-dimensional hypercube, and each is directly
connected to the n neighboring nodes
- Degree = n
One-cube Two-cube Three-cube
11010
1 00 10
010
110
011 111
101
100
001
000
n-dimensional hypercube (binary n-cube)