COSC 6385 Computer Architecture. - Thread Level Parallelism (III)

Size: px
Start display at page:

Download "COSC 6385 Computer Architecture. - Thread Level Parallelism (III)"

Transcription

1 OS 6385 omputer Architecture - Thread Level Parallelism (III) Spring 2013 Some slides are based on a lecture by David uller, University of alifornia, Berkley Larger Shared Memory Systems Typically Distributed Shared Memory Systems Local or remote memory access via memory controller Directory per cache that tracks state of every block in every cache Which caches have a copy of block, dirty vs. clean,... Info per memory block vs. per cache block? PLUS: In memory => simpler protocol (centralized/one location) MINUS: In memory => directory is ƒ(memory size) vs. ƒ(cache size) Prevent directory as bottleneck? distribute directory entries with memory, each keeping track of which Procs have copies of their blocks 1

2 Distributed Directory MPs Distributed Shared Memory Systems 2

3 Memory Memory AMD 8350 quad-core Opteron process Single processor configuration Private L1 cache: 32 KB data, 32 KB instruction Private L2 cache: 512 KB unified Shared L3 cache: 2 MB unified entralized shared memory system ore ore ore ore L1 L2 3 Hypertransports L1 L1 L2 L2 shared L3 crossbar L1 L2 2 Mem. ontroller AMD 8350 quad-core Opteron Multi-processor configuration Distributed shared memory system 0 1 Socket 0 Socket 1 2 L3 3 HT HT HT 8 GB/s L3 7 HT HT HT Memory 8 GB/s 8 GB/s HT HT HT 8 9 L GB/s HT HT HT L Memory Socket 2 Socket 3 3

4 Programming distributed shared memory systems Programmers must use threads or processes Spread the workload across multiple cores Write parallel algorithms OS will map threads/processes to cores True concurrency, not just uni-processor time-slicing Pre-emptive context switching: context switch can happen at any time oncurrency bugs exposed much faster with multi-core Slide based on a lecture of Jernej Barbic, MIT, Programming distributed shared memory systems Each thread/process has an affinity mask Specifies what cores the thread is allowed to run on Different threads can have different masks Affinities are inherited across fork() Example: 4-way multi-core, without SMT core 3 core 2 core 1 core 0 Process/thread is allowed to run on cores 0,2,3, but not on core 1 Slide based on a lecture of Jernej Barbic, MIT, 4

5 Process migration is costly Default Affinities Default affinity mask is all 1s: all threads can run on all processors and cores OS scheduler decides which thread runs on which core OS scheduler detects skewed workloads, migrating threads to less busy processors Soft affinity: Tendency of a scheduler to try to keep processes on the same PU as long as possible Hard affinity: Affinity information has been explicitly set by application OS has to adhere to this setting Linux Kernel scheduler API Retrieve the current affinity mask of a process #include <sys/types.h> #include <sched.h> #include <unistd.h> #include <errno.h> unsigned int len = sizeof(cpu_set_t); cpu_set_t mask; pid_t pid = getpid();/* get the process id of this app */ ret = sched_getaffinity (pid, len, &mask); if ( ret!= 0 ) printf( Error in getaffinity %d (%s)\n, errno, strerror(errno); for (i=0; i<numpus; i++) { if ( PU_ISSET(i, &mask) ) printf( Process could run on PU %d\n, i); } 5

6 Linux Kernel scheduler API (II) Set the affinity mask of a process unsigned int len = sizeof(cpu_set_t); cpu_set_t mask; pid_t pid = getpid();/* get the process id of this app */ /* clear the mask */ PU_ZERO (&mask); /* set the mask such that the process is only allowed to execute on the desired PU */ PU_SET ( cpu_id, &mask); ret = sched_setaffinity (pid, len, &mask); if ( ret!= 0 ) { printf( Error in setaffinity %d (%s)\n, errno, strerror(errno); } Linux Kernel scheduler API (III) Setting thread-related affinity information Use sched_setaffinity with a pid = 0 hanges the affinity settings for this thread only Use libnuma functionality numa_run_on_node(); numa_run_on_node_mask(); Modifying affinity information based on PU sockets, not on cores Use pthread functions on most linux systems #define USE_GNU pthread_setaffinity_np(thread_t t, len, mask); pthread_attr_setaffinity_np ( thread_attr_t a, len, mask); 6

7 Directory based ache oherence Protocol Similar to Snoopy Protocol: Three states Shared: 1 processors have data, memory up-to-date Uncached (no processor has it; not valid in any cache) Exclusive: 1 processor (owner) has data; memory out-of-date In addition to cache state, must track which processors have data when in the shared state (usually bit vector, 1 if processor has copy) Assumptions: Writes to non-exclusive data => write miss Processor blocks until access completes Assume messages received and acted upon in order sent Directory Protocol No bus and don t want to broadcast: interconnect no longer single arbitration point all messages have explicit responses Terms: typically 3 processors involved Local node where a request originates Home node where the memory location of an address resides Remote node has a copy of a cache block, whether exclusive or shared Example messages on next slide: P = processor number, A = address 7

8 Directory Protocol Messages Message type Source Destination Msg ontent Read miss Local cache Home directory P, A Processor P reads data at address A; make P a read sharer and arrange to send data back Write miss Local cache Home directory P, A Processor P writes data at address A; make P the exclusive owner and arrange to send data back Invalidate Home directory Remote caches A Invalidate a shared copy at address A. Fetch Home directory Remote cache A Fetch the block at address A and send it to its home directory Fetch/Invalidate Home directory Remote cache A Fetch the block at address A and send it to its home directory; invalidate the block in the cache Data value reply Home directory Local cache Data Return a data value from the home memory (read miss response) Data write-back Remote cache Home directory A, Data Write-back a data value for address A (invalidate response) State Transition Diagram for an Individual ache Block in a Directory Based System States identical to snoopy case; transactions very similar. Transitions caused by read misses, write misses, invalidates, data fetch requests Generates read miss & write miss msg to home directory. Write misses that were broadcast on the bus for snooping => explicit invalidate & data fetch requests. Note: on a write, a cache block is bigger, so need to read the full cache block 8

9 PU -ache State Machine PU Read hit State machine for PU requests for each memory block Invalid state if in memory Fetch/Invalidate send Data Write Back message to home directory PU read hit PU write hit Invalid Exclusive (read/writ) Invalidate PU Read Send Read Miss message PU Write: Send Write Miss msg to h.d. Shared (read/only) PU Write:Send Write Miss message to home directory Fetch: send Data Write Back message to home directory PU read miss: send Data Write Back message and read miss to home directory PU write miss: send Data Write Back message and Write Miss to home directory State Transition Diagram for the Directory Same states & structure as the transition diagram for an individual cache 2 actions: update of directory state & send msgs to satisfy requests Tracks all copies of memory block. Also indicates an action that updates the sharing set, Sharers, as well as sending a message. 9

10 State machine for Directory requests for each memory block Uncached state if in memory Write Miss: Sharers = {P}; send Fetch/Invalidate; send Data Value Reply Directory State Machine Data Write Back: Sharers = {} (Write back block) msg to remote cache Uncached Exclusive (read/writ) Read miss: Sharers = {P} send Data Value Reply Write Miss: Sharers = {P}; send Data Value Reply msg Shared (read only) Read miss: Sharers += {P}; send Fetch; send Data Value Reply msg to remote cache (Write back block) Write Miss: send Invalidate to Sharers; then Sharers = {P}; send Data Value Reply msg Example Directory Protocol Message sent to directory causes two actions: Update the directory More messages to satisfy request Block is in Uncached state: the copy in memory is the current value; only possible requests for that block are: Read miss: requesting processor sent data from memory &requestor made only sharing node; state of block made Shared. Write miss: requesting processor is sent the value & becomes the Sharing node. The block is made Exclusive to indicate that the only valid copy is cached. Sharers indicates the identity of the owner. Block is Shared => the memory value is up-to-date: Read miss: requesting processor is sent back the data from memory & requesting processor is added to the sharing set. Write miss: requesting processor is sent the value. All processors in the set Sharers are sent invalidate messages, & Sharers is set to identity of requesting processor. The state of the block is made Exclusive. 10

11 Example Directory Protocol Block is Exclusive: current value of the block is held in the cache of the processor identified by the set Sharers (the owner) => three possible directory requests: Read miss: owner processor sent data fetch message, causing state of block in owner s cache to transition to Shared and causes owner to send data to directory, where it is written to memory & sent back to requesting processor. Identity of requesting processor is added to set Sharers, which still contains the identity of the processor that was the owner (since it still has a readable copy). State is shared. Data write-back: owner processor is replacing the block and hence must write it back, making memory copy up-to-date (the home directory essentially becomes the owner), the block is now Uncached, and the Sharer set is empty. Write miss: block has a new owner. A message is sent to old owner causing the cache to send the value of the block to the directory from which it is sent to the requesting processor, which becomes the new owner. Sharers is set to identity of new owner, and state of block is made Exclusive. Example Processor 1 Processor 2 Interconnect Directory Memory step P1: Write 10 to A1 P1 P2 Bus Directory Memory State Addr ValueState Addr ValueAction Proc. Addr Value Addr State {Procs} Value P1: Read A1 P2: Read A1 P2: Write 20 to A1 P2: Write 40 to A2 A1 and A2 map to the same cache block 11

12 Example Processor 1 Processor 2 Interconnect Directory Memory P1 P2 Bus Directory Memory step State Addr ValueState Addr ValueAction Proc. Addr Value Addr State {Procs} Value P1: Write 10 to A1 WrMs P1 A1 A1 Ex {P1} Excl. A1 10 DaRp P1 A1 0 P1: Read A1 P2: Read A1 P2: Write 20 to A1 P2: Write 40 to A2 A1 and A2 map to the same cache block Example Processor 1 Processor 2 Interconnect Directory Memory P1 P2 Bus Directory Memory step State Addr ValueState Addr ValueAction Proc. Addr Value Addr State {Procs} Value P1: Write 10 to A1 WrMs P1 A1 A1 Ex {P1} Excl. A1 10 DaRp P1 A1 0 P1: Read A1 Excl. A1 10 P2: Read A1 P2: Write 20 to A1 P2: Write 40 to A2 A1 and A2 map to the same cache block 12

13 Example Processor 1 Processor 2 Interconnect Directory Memory P1 P2 Bus Directory Memory step State Addr ValueState Addr ValueAction Proc. Addr Value Addr State {Procs} Value P1: Write 10 to A1 WrMs P1 A1 A1 Ex {P1} Excl. A1 10 DaRp P1 A1 0 P1: Read A1 Excl. A1 10 P2: Read A1 Shar. A1 RdMs P2 A1 Shar. A1 10 Ftch P1 A Shar. A1 10 DaRp P2 A1 10 A1 Shar. P1,P2} 10 P2: Write 20 to A P2: Write 40 to A2 10 Write Back A1 and A2 map to the same cache block Example Processor 1 Processor 2 Interconnect Directory Memory P1 P2 Bus Directory Memory step State Addr ValueState Addr ValueAction Proc. Addr Value Addr State {Procs} Value P1: Write 10 to A1 WrMs P1 A1 A1 Ex {P1} Excl. A1 10 DaRp P1 A1 0 P1: Read A1 Excl. A1 10 P2: Read A1 Shar. A1 RdMs P2 A1 Shar. A1 10 Ftch P1 A Shar. A1 10 DaRp P2 A1 10 A1 Shar. P1,P2} 10 P2: Write 20 to A1 Excl. A1 20 WrMs P2 A1 10 Inv. Inval. P1 A1 A1 Excl. {P2} 10 P2: Write 40 to A2 10 A1 and A2 map to the same cache block 13

14 Example Processor 1 Processor 2 Interconnect Directory Memory P1 P2 Bus Directory Memory step State Addr ValueState Addr ValueAction Proc. Addr Value Addr State {Procs} Value P1: Write 10 to A1 WrMs P1 A1 A1 Ex {P1} Excl. A1 10 DaRp P1 A1 0 P1: Read A1 Excl. A1 10 P2: Read A1 Shar. A1 RdMs P2 A1 Shar. A1 10 Ftch P1 A1 10 A1 10 Shar. A1 10 DaRp P2 A1 10 A1 Shar. P1,P2} 10 P2: Write 20 to A1 Excl. A1 20 WrMs P2 A1 10 Inv. Inval. P1 A1 A1 Excl. {P2} 10 P2: Write 40 to A2 WrMs P2 A2 A2 Excl. {P2} 0 WrBk P2 A1 20 A1 Unca. {} 20 Excl. A2 40 DaRp P2 A2 0 A2 Excl. {P2} 0 A1 and A2 map to the same cache block Implementing a Directory We assume operations atomic, but they are not; reality is much harder; must avoid deadlock when run out of buffers in network Optimizations: read miss or write miss in Exclusive: send data directly to requestor from owner vs. 1st to memory and then from memory to requestor 14

15 Intel Sandy Bridge Architecture Newest generation of Intel Architecture Desktop version integrates regular processor and graphics cards on one chip Intel Sandy-Bridge Sandy Bridge now contains mem. ontroller, QTI, and graphics processor on chip AMD first integrated memory controller and HTI on the chip Instruction fetch: decoding variable length uops is complex and expensive Sandy Bridge introduces a uops cache: a hit in the uop cache will bypass decoding logic Uop cache is organized into 32sets, each 8 way, 6 uops per set Included physically in the L1 cache Predicted address will probe uop cache: if found, instruction bypass decoding step 15

16 Intel Sandy Bridge All 256bit AVX instructions can execute as a single uop In contrary to AMD, where they are broken down to bit AVX instructions FP data path is however only 128 bits wide on SB Functional units are grouped into three domain: Integer, SIMD integer and FP Free bypassing within each domain, but a 1-2 cc penalty for instructions bypassing between the different domains Simplifies the forwarding logic between the domains for rarely used situations Intel Sandy Bridge A ring interconnects the cores, graphics, and L3 cache composed of four different rings: request, snoop, acknowledge and a 32B wide data ring. responsible for a distributed communication protocol that enforces coherency and ordering. Source: 16

17 AMD Istanbul/Magny-ours processor Source: AMD Interlagos Processor First generation of the new Bulldozer architecture Two cores form a module Each module share an L1I cache, floating point unit (FPU) and L2 cache, saves area and power to pack in more cores and attain higher throughput Leads to degradation in terms of per-core performance. All modules in a chip share the L3 cache 17

18 AMD Interlagos Processor Source: 18

COSC 6385 Computer Architecture - Thread Level Parallelism (III)

COSC 6385 Computer Architecture - Thread Level Parallelism (III) OS 6385 omputer Architecture - Thread Level Parallelism (III) Edgar Gabriel Spring 2018 Some slides are based on a lecture by David uller, University of alifornia, Berkley http://www.eecs.berkeley.edu/~culler/courses/cs252-s05

More information

COSC 6385 Computer Architecture. - Multi-Processors (IV) Simultaneous multi-threading and multi-core processors

COSC 6385 Computer Architecture. - Multi-Processors (IV) Simultaneous multi-threading and multi-core processors OS 6385 omputer Architecture - Multi-Processors (IV) Simultaneous multi-threading and multi-core processors Spring 2012 Long-term trend on the number of transistor per integrated circuit Number of transistors

More information

Lecture 24: Thread Level Parallelism -- Distributed Shared Memory and Directory-based Coherence Protocol

Lecture 24: Thread Level Parallelism -- Distributed Shared Memory and Directory-based Coherence Protocol Lecture 24: Thread Level Parallelism -- Distributed Shared Memory and Directory-based Coherence Protocol CSE 564 Computer Architecture Fall 2016 Department of Computer Science and Engineering Yonghong

More information

Shared Memory SMP and Cache Coherence (cont) Adapted from UCB CS252 S01, Copyright 2001 USB

Shared Memory SMP and Cache Coherence (cont) Adapted from UCB CS252 S01, Copyright 2001 USB Shared SMP and Cache Coherence (cont) Adapted from UCB CS252 S01, Copyright 2001 USB 1 Review: Snoopy Cache Protocol Write Invalidate Protocol: Multiple readers, single writer Write to shared data: an

More information

CMSC 611: Advanced. Distributed & Shared Memory

CMSC 611: Advanced. Distributed & Shared Memory CMSC 611: Advanced Computer Architecture Distributed & Shared Memory Centralized Shared Memory MIMD Processors share a single centralized memory through a bus interconnect Feasible for small processor

More information

COEN-4730 Computer Architecture Lecture 08 Thread Level Parallelism and Coherence

COEN-4730 Computer Architecture Lecture 08 Thread Level Parallelism and Coherence 1 COEN-4730 Computer Architecture Lecture 08 Thread Level Parallelism and Coherence Cristinel Ababei Dept. of Electrical and Computer Engineering Marquette University Credits: Slides adapted from presentations

More information

Review: Multiprocessor. CPE 631 Session 21: Multiprocessors (Part 2) Potential HW Coherency Solutions. Bus Snooping Topology

Review: Multiprocessor. CPE 631 Session 21: Multiprocessors (Part 2) Potential HW Coherency Solutions. Bus Snooping Topology Review: Multiprocessor CPE 631 Session 21: Multiprocessors (Part 2) Department of Electrical and Computer Engineering University of Alabama in Huntsville Basic issues and terminology Communication: share

More information

CMSC 611: Advanced Computer Architecture

CMSC 611: Advanced Computer Architecture CMSC 611: Advanced Computer Architecture Shared Memory Most slides adapted from David Patterson. Some from Mohomed Younis Interconnection Networks Massively processor networks (MPP) Thousands of nodes

More information

Page 1. Lecture 12: Multiprocessor 2: Snooping Protocol, Directory Protocol, Synchronization, Consistency. Bus Snooping Topology

Page 1. Lecture 12: Multiprocessor 2: Snooping Protocol, Directory Protocol, Synchronization, Consistency. Bus Snooping Topology CS252 Graduate Computer Architecture Lecture 12: Multiprocessor 2: Snooping Protocol, Directory Protocol, Synchronization, Consistency Review: Multiprocessor Basic issues and terminology Communication:

More information

Aleksandar Milenkovic, Electrical and Computer Engineering University of Alabama in Huntsville. Review: Small-Scale Shared Memory

Aleksandar Milenkovic, Electrical and Computer Engineering University of Alabama in Huntsville. Review: Small-Scale Shared Memory Lecture 20: Multiprocessors Aleksandar Milenkovic, milenka@ece.uah.edu Electrical and Computer Engineering University of Alabama in Huntsville Review: Small-Scale Shared Memory Caches serve to: Increase

More information

CPE 631 Lecture 21: Multiprocessors

CPE 631 Lecture 21: Multiprocessors Lecture 2: Multiprocessors Aleksandar Milenković, milenka@ece.uah.edu Electrical and Computer Engineering University of Alabama in Huntsville Review: Small-Scale Shared Memory Caches serve to: Increase

More information

Multi-core Architectures. Dr. Yingwu Zhu

Multi-core Architectures. Dr. Yingwu Zhu Multi-core Architectures Dr. Yingwu Zhu Outline Parallel computing? Multi-core architectures Memory hierarchy Vs. SMT Cache coherence What is parallel computing? Using multiple processors in parallel to

More information

CMSC 411 Computer Systems Architecture Lecture 21 Multiprocessors 3

CMSC 411 Computer Systems Architecture Lecture 21 Multiprocessors 3 MS 411 omputer Systems rchitecture Lecture 21 Multiprocessors 3 Outline Review oherence Write onsistency dministrivia Snooping Building Blocks Snooping protocols and examples oherence traffic and performance

More information

5008: Computer Architecture

5008: Computer Architecture 5008: Computer Architecture Chapter 4 Multiprocessors and Thread-Level Parallelism --II CA Lecture08 - multiprocessors and TLP (cwliu@twins.ee.nctu.edu.tw) 09-1 Review Caches contain all information on

More information

ECSE 425 Lecture 30: Directory Coherence

ECSE 425 Lecture 30: Directory Coherence ECSE 425 Lecture 30: Directory Coherence H&P Chapter 4 Last Time Snoopy Coherence Symmetric SMP Performance 2 Today Directory- based Coherence 3 A Scalable Approach: Directories One directory entry for

More information

Introduction to Multiprocessors (Part II) Cristina Silvano Politecnico di Milano

Introduction to Multiprocessors (Part II) Cristina Silvano Politecnico di Milano Introduction to Multiprocessors (Part II) Cristina Silvano Politecnico di Milano Outline The problem of cache coherence Snooping protocols Directory-based protocols Prof. Cristina Silvano, Politecnico

More information

Computer Architecture Lecture 10: Thread Level Parallelism II (Chapter 5) Chih Wei Liu 劉志尉 National Chiao Tung University

Computer Architecture Lecture 10: Thread Level Parallelism II (Chapter 5) Chih Wei Liu 劉志尉 National Chiao Tung University Computer Architecture Lecture 10: Thread Level Parallelism II (Chapter 5) Chih Wei Liu 劉志尉 National Chiao Tung University cwliu@twins.ee.nctu.edu.tw Review Caches contain all information on state of cached

More information

Aleksandar Milenkovich 1

Aleksandar Milenkovich 1 Parallel Computers Lecture 8: Multiprocessors Aleksandar Milenkovic, milenka@ece.uah.edu Electrical and Computer Engineering University of Alabama in Huntsville Definition: A parallel computer is a collection

More information

Multi-core Architectures. Dr. Yingwu Zhu

Multi-core Architectures. Dr. Yingwu Zhu Multi-core Architectures Dr. Yingwu Zhu What is parallel computing? Using multiple processors in parallel to solve problems more quickly than with a single processor Examples of parallel computing A cluster

More information

Computer Architecture. A Quantitative Approach, Fifth Edition. Chapter 5. Multiprocessors and Thread-Level Parallelism

Computer Architecture. A Quantitative Approach, Fifth Edition. Chapter 5. Multiprocessors and Thread-Level Parallelism Computer Architecture A Quantitative Approach, Fifth Edition Chapter 5 Multiprocessors and Thread-Level Parallelism 1 Introduction Thread-Level parallelism Have multiple program counters Uses MIMD model

More information

CS654 Advanced Computer Architecture Lec 14 Directory Based Multiprocessors

CS654 Advanced Computer Architecture Lec 14 Directory Based Multiprocessors CS654 Advanced Computer Architecture Lec 14 Directory Based Multiprocessors Peter Kemper Adapted from the slides of EECS 252 by Prof. David Patterson Electrical Engineering and Computer Sciences University

More information

Aleksandar Milenkovic, Electrical and Computer Engineering University of Alabama in Huntsville

Aleksandar Milenkovic, Electrical and Computer Engineering University of Alabama in Huntsville Lecture 18: Multiprocessors Aleksandar Milenkovic, milenka@ece.uah.edu Electrical and Computer Engineering University of Alabama in Huntsville Parallel Computers Definition: A parallel computer is a collection

More information

Thread- Level Parallelism. ECE 154B Dmitri Strukov

Thread- Level Parallelism. ECE 154B Dmitri Strukov Thread- Level Parallelism ECE 154B Dmitri Strukov Introduc?on Thread- Level parallelism Have mul?ple program counters and resources Uses MIMD model Targeted for?ghtly- coupled shared- memory mul?processors

More information

Lecture 17: Multiprocessors: Size, Consitency. Review: Networking Summary

Lecture 17: Multiprocessors: Size, Consitency. Review: Networking Summary Lecture 17: Multiprocessors: Size, Consitency Professor David A. Patterson Computer Science 252 Spring 1998 DAP Spr. 98 UCB 1 Review: Networking Summary Protocols allow hetereogeneous networking Protocols

More information

Multiprocessor Cache Coherence. Chapter 5. Memory System is Coherent If... From ILP to TLP. Enforcing Cache Coherence. Multiprocessor Types

Multiprocessor Cache Coherence. Chapter 5. Memory System is Coherent If... From ILP to TLP. Enforcing Cache Coherence. Multiprocessor Types Chapter 5 Multiprocessor Cache Coherence Thread-Level Parallelism 1: read 2: read 3: write??? 1 4 From ILP to TLP Memory System is Coherent If... ILP became inefficient in terms of Power consumption Silicon

More information

ESE 545 Computer Architecture Symmetric Multiprocessors and Snoopy Cache Coherence Protocols CA SMP and cache coherence

ESE 545 Computer Architecture Symmetric Multiprocessors and Snoopy Cache Coherence Protocols CA SMP and cache coherence Computer Architecture ESE 545 Computer Architecture Symmetric Multiprocessors and Snoopy Cache Coherence Protocols 1 Shared Memory Multiprocessor Memory Bus P 1 Snoopy Cache Physical Memory P 2 Snoopy

More information

Directory Implementation. A High-end MP

Directory Implementation. A High-end MP ectory Implementation Distributed memory each processor (or cluster of processors) has its own memory processor-memory pairs are connected via a multi-path interconnection network snooping with broadcasting

More information

Chapter 6: Multiprocessors and Thread-Level Parallelism

Chapter 6: Multiprocessors and Thread-Level Parallelism Chapter 6: Multiprocessors and Thread-Level Parallelism 1 Parallel Architectures 2 Flynn s Four Categories SISD (Single Instruction Single Data) Uniprocessors MISD (Multiple Instruction Single Data)???;

More information

CISC 662 Graduate Computer Architecture Lectures 15 and 16 - Multiprocessors and Thread-Level Parallelism

CISC 662 Graduate Computer Architecture Lectures 15 and 16 - Multiprocessors and Thread-Level Parallelism CISC 662 Graduate Computer Architecture Lectures 15 and 16 - Multiprocessors and Thread-Level Parallelism Michela Taufer http://www.cis.udel.edu/~taufer/teaching/cis662f07 Powerpoint Lecture Notes from

More information

CSE 502 Graduate Computer Architecture Lec 19 Directory-Based Shared-Memory Multiprocessors & MP Synchronization

CSE 502 Graduate Computer Architecture Lec 19 Directory-Based Shared-Memory Multiprocessors & MP Synchronization CSE 502 Graduate Computer Architecture Lec 19 Directory-Based Shared-Memory Multiprocessors & MP Synchronization Larry Wittie Computer Science, StonyBrook University http://www.cs.sunysb.edu/~cse502 and

More information

Lecture 30: Multiprocessors Flynn Categories, Large vs. Small Scale, Cache Coherency Professor Randy H. Katz Computer Science 252 Spring 1996

Lecture 30: Multiprocessors Flynn Categories, Large vs. Small Scale, Cache Coherency Professor Randy H. Katz Computer Science 252 Spring 1996 Lecture 30: Multiprocessors Flynn Categories, Large vs. Small Scale, Cache Coherency Professor Randy H. Katz Computer Science 252 Spring 1996 RHK.S96 1 Flynn Categories SISD (Single Instruction Single

More information

Page 1. Instruction-Level Parallelism (ILP) CISC 662 Graduate Computer Architecture Lectures 16 and 17 - Multiprocessors and Thread-Level Parallelism

Page 1. Instruction-Level Parallelism (ILP) CISC 662 Graduate Computer Architecture Lectures 16 and 17 - Multiprocessors and Thread-Level Parallelism CISC 662 Graduate Computer Architecture Lectures 16 and 17 - Multiprocessors and Thread-Level Parallelism Michela Taufer Powerpoint Lecture Notes from John Hennessy and David Patterson s: Computer Architecture,

More information

Flynn s Classification

Flynn s Classification Flynn s Classification SISD (Single Instruction Single Data) Uniprocessors MISD (Multiple Instruction Single Data) No machine is built yet for this type SIMD (Single Instruction Multiple Data) Examples:

More information

EC 513 Computer Architecture

EC 513 Computer Architecture EC 513 Computer Architecture Cache Coherence - Directory Cache Coherence Prof. Michel A. Kinsy Shared Memory Multiprocessor Processor Cores Local Memories Memory Bus P 1 Snoopy Cache Physical Memory P

More information

Parallel Computers. CPE 631 Session 20: Multiprocessors. Flynn s Tahonomy (1972) Why Multiprocessors?

Parallel Computers. CPE 631 Session 20: Multiprocessors. Flynn s Tahonomy (1972) Why Multiprocessors? Parallel Computers CPE 63 Session 20: Multiprocessors Department of Electrical and Computer Engineering University of Alabama in Huntsville Definition: A parallel computer is a collection of processing

More information

CSE 392/CS 378: High-performance Computing - Principles and Practice

CSE 392/CS 378: High-performance Computing - Principles and Practice CSE 392/CS 378: High-performance Computing - Principles and Practice Parallel Computer Architectures A Conceptual Introduction for Software Developers Jim Browne browne@cs.utexas.edu Parallel Computer

More information

Chapter 5. Multiprocessors and Thread-Level Parallelism

Chapter 5. Multiprocessors and Thread-Level Parallelism Computer Architecture A Quantitative Approach, Fifth Edition Chapter 5 Multiprocessors and Thread-Level Parallelism 1 Introduction Thread-Level parallelism Have multiple program counters Uses MIMD model

More information

Lecture 8: Snooping and Directory Protocols. Topics: split-transaction implementation details, directory implementations (memory- and cache-based)

Lecture 8: Snooping and Directory Protocols. Topics: split-transaction implementation details, directory implementations (memory- and cache-based) Lecture 8: Snooping and Directory Protocols Topics: split-transaction implementation details, directory implementations (memory- and cache-based) 1 Split Transaction Bus So far, we have assumed that a

More information

Computer Architecture

Computer Architecture Jens Teubner Computer Architecture Summer 2016 1 Computer Architecture Jens Teubner, TU Dortmund jens.teubner@cs.tu-dortmund.de Summer 2016 Jens Teubner Computer Architecture Summer 2016 83 Part III Multi-Core

More information

Parallel Architecture. Hwansoo Han

Parallel Architecture. Hwansoo Han Parallel Architecture Hwansoo Han Performance Curve 2 Unicore Limitations Performance scaling stopped due to: Power Wire delay DRAM latency Limitation in ILP 3 Power Consumption (watts) 4 Wire Delay Range

More information

Review. EECS 252 Graduate Computer Architecture. Lec 13 Snooping Cache and Directory Based Multiprocessors. Outline. Challenges of Parallel Processing

Review. EECS 252 Graduate Computer Architecture. Lec 13 Snooping Cache and Directory Based Multiprocessors. Outline. Challenges of Parallel Processing EEC 252 Graduate Computer Architecture Lec 13 nooping Cache and Directory Based Multiprocessors David atterson Electrical Engineering and Computer ciences University of California, Berkeley http://www.eecs.berkeley.edu/~pattrsn

More information

Lecture 5: Directory Protocols. Topics: directory-based cache coherence implementations

Lecture 5: Directory Protocols. Topics: directory-based cache coherence implementations Lecture 5: Directory Protocols Topics: directory-based cache coherence implementations 1 Flat Memory-Based Directories Block size = 128 B Memory in each node = 1 GB Cache in each node = 1 MB For 64 nodes

More information

Multiprocessor Cache Coherency. What is Cache Coherence?

Multiprocessor Cache Coherency. What is Cache Coherence? Multiprocessor Cache Coherency CS448 1 What is Cache Coherence? Two processors can have two different values for the same memory location 2 1 Terminology Coherence Defines what values can be returned by

More information

Multiprocessors & Thread Level Parallelism

Multiprocessors & Thread Level Parallelism Multiprocessors & Thread Level Parallelism COE 403 Computer Architecture Prof. Muhamed Mudawar Computer Engineering Department King Fahd University of Petroleum and Minerals Presentation Outline Introduction

More information

Parallel Computer Architecture Spring Distributed Shared Memory Architectures & Directory-Based Memory Coherence

Parallel Computer Architecture Spring Distributed Shared Memory Architectures & Directory-Based Memory Coherence Parallel Computer Architecture Spring 2018 Distributed Shared Memory Architectures & Directory-Based Memory Coherence Nikos Bellas Computer and Communications Engineering Department University of Thessaly

More information

3/13/2008 Csci 211 Lecture %/year. Manufacturer/Year. Processors/chip Threads/Processor. Threads/chip 3/13/2008 Csci 211 Lecture 8 4

3/13/2008 Csci 211 Lecture %/year. Manufacturer/Year. Processors/chip Threads/Processor. Threads/chip 3/13/2008 Csci 211 Lecture 8 4 Outline CSCI Computer System Architecture Lec 8 Multiprocessor Introduction Xiuzhen Cheng Department of Computer Sciences The George Washington University MP Motivation SISD v. SIMD v. MIMD Centralized

More information

Multiprocessors: Basics, Cache coherence, Synchronization, and Memory consistency

Multiprocessors: Basics, Cache coherence, Synchronization, and Memory consistency Multiprocessors: Basics, Cache coherence, Synchronization, and Memory consistency Z. Jerry Shi Assistant Professor of Computer Science and Engineering University of Connecticut * Slides adapted from Blumrich&Gschwind/ELE475

More information

Lecture 2: Snooping and Directory Protocols. Topics: Snooping wrap-up and directory implementations

Lecture 2: Snooping and Directory Protocols. Topics: Snooping wrap-up and directory implementations Lecture 2: Snooping and Directory Protocols Topics: Snooping wrap-up and directory implementations 1 Split Transaction Bus So far, we have assumed that a coherence operation (request, snoops, responses,

More information

Chapter 5. Multiprocessors and Thread-Level Parallelism

Chapter 5. Multiprocessors and Thread-Level Parallelism Computer Architecture A Quantitative Approach, Fifth Edition Chapter 5 Multiprocessors and Thread-Level Parallelism 1 Introduction Thread-Level parallelism Have multiple program counters Uses MIMD model

More information

Multi-threaded processors. Hung-Wei Tseng x Dean Tullsen

Multi-threaded processors. Hung-Wei Tseng x Dean Tullsen Multi-threaded processors Hung-Wei Tseng x Dean Tullsen OoO SuperScalar Processor Fetch instructions in the instruction window Register renaming to eliminate false dependencies edule an instruction to

More information

Foundations of Computer Systems

Foundations of Computer Systems 18-600 Foundations of Computer Systems Lecture 21: Multicore Cache Coherence John P. Shen & Zhiyi Yu November 14, 2016 Prevalence of multicore processors: 2006: 75% for desktops, 85% for servers 2007:

More information

Lecture 23: Thread Level Parallelism -- Introduction, SMP and Snooping Cache Coherence Protocol

Lecture 23: Thread Level Parallelism -- Introduction, SMP and Snooping Cache Coherence Protocol Lecture 23: Thread Level Parallelism -- Introduction, SMP and Snooping Cache Coherence Protocol CSE 564 Computer Architecture Summer 2017 Department of Computer Science and Engineering Yonghong Yan yan@oakland.edu

More information

COMP Parallel Computing. CC-NUMA (1) CC-NUMA implementation

COMP Parallel Computing. CC-NUMA (1) CC-NUMA implementation COP 633 - Parallel Computing Lecture 10 September 27, 2018 CC-NUA (1) CC-NUA implementation Reading for next time emory consistency models tutorial (sections 1-6, pp 1-17) COP 633 - Prins CC-NUA (1) Topics

More information

??%/year. ! All microprocessor companies switch to MP (2X CPUs / 2 yrs) " Procrastination penalized: 2X sequential perf. / 5 yrs

??%/year. ! All microprocessor companies switch to MP (2X CPUs / 2 yrs)  Procrastination penalized: 2X sequential perf. / 5 yrs Outline EEL 5764 Graduate Computer Architecture Chapter 4 - Multiprocessors and TLP Ann Gordon-oss Electrical and Computer Engineering University of Florida MP Motivation ID v. IMD v. MIMD Centralized

More information

Lecture 25: Multiprocessors. Today s topics: Snooping-based cache coherence protocol Directory-based cache coherence protocol Synchronization

Lecture 25: Multiprocessors. Today s topics: Snooping-based cache coherence protocol Directory-based cache coherence protocol Synchronization Lecture 25: Multiprocessors Today s topics: Snooping-based cache coherence protocol Directory-based cache coherence protocol Synchronization 1 Snooping-Based Protocols Three states for a block: invalid,

More information

Lecture 10: Cache Coherence: Part I. Parallel Computer Architecture and Programming CMU , Spring 2013

Lecture 10: Cache Coherence: Part I. Parallel Computer Architecture and Programming CMU , Spring 2013 Lecture 10: Cache Coherence: Part I Parallel Computer Architecture and Programming Cache design review Let s say your code executes int x = 1; (Assume for simplicity x corresponds to the address 0x12345604

More information

Cache Coherence. CMU : Parallel Computer Architecture and Programming (Spring 2012)

Cache Coherence. CMU : Parallel Computer Architecture and Programming (Spring 2012) Cache Coherence CMU 15-418: Parallel Computer Architecture and Programming (Spring 2012) Shared memory multi-processor Processors read and write to shared variables - More precisely: processors issues

More information

Cache Coherence. Bryan Mills, PhD. Slides provided by Rami Melhem

Cache Coherence. Bryan Mills, PhD. Slides provided by Rami Melhem Cache Coherence Bryan Mills, PhD Slides provided by Rami Melhem Cache coherence Programmers have no control over caches and when they get updated. x = 2; /* initially */ y0 eventually ends up = 2 y1 eventually

More information

Multiprocessors. Flynn Taxonomy. Classifying Multiprocessors. why would you want a multiprocessor? more is better? Cache Cache Cache.

Multiprocessors. Flynn Taxonomy. Classifying Multiprocessors. why would you want a multiprocessor? more is better? Cache Cache Cache. Multiprocessors why would you want a multiprocessor? Multiprocessors and Multithreading more is better? Cache Cache Cache Classifying Multiprocessors Flynn Taxonomy Flynn Taxonomy Interconnection Network

More information

COSC 6374 Parallel Computation. Parallel Computer Architectures

COSC 6374 Parallel Computation. Parallel Computer Architectures OS 6374 Parallel omputation Parallel omputer Architectures Some slides on network topologies based on a similar presentation by Michael Resch, University of Stuttgart Edgar Gabriel Fall 2015 Flynn s Taxonomy

More information

COSC 6374 Parallel Computation. Parallel Computer Architectures

COSC 6374 Parallel Computation. Parallel Computer Architectures OS 6374 Parallel omputation Parallel omputer Architectures Some slides on network topologies based on a similar presentation by Michael Resch, University of Stuttgart Spring 2010 Flynn s Taxonomy SISD:

More information

Shared Memory Multiprocessors. Symmetric Shared Memory Architecture (SMP) Cache Coherence. Cache Coherence Mechanism. Interconnection Network

Shared Memory Multiprocessors. Symmetric Shared Memory Architecture (SMP) Cache Coherence. Cache Coherence Mechanism. Interconnection Network Shared Memory Multis Processor Processor Processor i Processor n Symmetric Shared Memory Architecture (SMP) cache cache cache cache Interconnection Network Main Memory I/O System Cache Coherence Cache

More information

Introducing Multi-core Computing / Hyperthreading

Introducing Multi-core Computing / Hyperthreading Introducing Multi-core Computing / Hyperthreading Clock Frequency with Time 3/9/2017 2 Why multi-core/hyperthreading? Difficult to make single-core clock frequencies even higher Deeply pipelined circuits:

More information

MULTIPROCESSORS AND THREAD-LEVEL. B649 Parallel Architectures and Programming

MULTIPROCESSORS AND THREAD-LEVEL. B649 Parallel Architectures and Programming MULTIPROCESSORS AND THREAD-LEVEL PARALLELISM B649 Parallel Architectures and Programming Motivation behind Multiprocessors Limitations of ILP (as already discussed) Growing interest in servers and server-performance

More information

MULTIPROCESSORS AND THREAD-LEVEL PARALLELISM. B649 Parallel Architectures and Programming

MULTIPROCESSORS AND THREAD-LEVEL PARALLELISM. B649 Parallel Architectures and Programming MULTIPROCESSORS AND THREAD-LEVEL PARALLELISM B649 Parallel Architectures and Programming Motivation behind Multiprocessors Limitations of ILP (as already discussed) Growing interest in servers and server-performance

More information

Scalable Cache Coherence

Scalable Cache Coherence Scalable Cache Coherence [ 8.1] All of the cache-coherent systems we have talked about until now have had a bus. Not only does the bus guarantee serialization of transactions; it also serves as convenient

More information

Multiprocessor Systems

Multiprocessor Systems Multiprocessor ystems 55:132/22C:160 pring2011 1 (vs. VAX-11/780) erformance 10000 1000 100 10 1 Uniprocessor erformance (ECint) From Hennessy and atterson, Computer Architecture: A Quantitative Approach,

More information

Lecture 10: Cache Coherence: Part I. Parallel Computer Architecture and Programming CMU /15-618, Spring 2015

Lecture 10: Cache Coherence: Part I. Parallel Computer Architecture and Programming CMU /15-618, Spring 2015 Lecture 10: Cache Coherence: Part I Parallel Computer Architecture and Programming CMU 15-418/15-618, Spring 2015 Tunes Marble House The Knife (Silent Shout) Before starting The Knife, we were working

More information

CS 152 Computer Architecture and Engineering. Lecture 19: Directory-Based Cache Protocols

CS 152 Computer Architecture and Engineering. Lecture 19: Directory-Based Cache Protocols CS 152 Computer Architecture and Engineering Lecture 19: Directory-Based Cache Protocols Krste Asanovic Electrical Engineering and Computer Sciences University of California, Berkeley http://www.eecs.berkeley.edu/~krste

More information

Lecture 3: Directory Protocol Implementations. Topics: coherence vs. msg-passing, corner cases in directory protocols

Lecture 3: Directory Protocol Implementations. Topics: coherence vs. msg-passing, corner cases in directory protocols Lecture 3: Directory Protocol Implementations Topics: coherence vs. msg-passing, corner cases in directory protocols 1 Future Scalable Designs Intel s Single Cloud Computer (SCC): an example prototype

More information

A Scalable SAS Machine

A Scalable SAS Machine arallel omputer Organization and Design : Lecture 8 er Stenström. 2008, Sally. ckee 2009 Scalable ache oherence Design principles of scalable cache protocols Overview of design space (8.1) Basic operation

More information

COSC4201 Multiprocessors

COSC4201 Multiprocessors COSC4201 Multiprocessors Prof. Mokhtar Aboelaze Parts of these slides are taken from Notes by Prof. David Patterson (UCB) Multiprocessing We are dedicating all of our future product development to multicore

More information

CSC 631: High-Performance Computer Architecture

CSC 631: High-Performance Computer Architecture CSC 631: High-Performance Computer Architecture Spring 2017 Lecture 10: Memory Part II CSC 631: High-Performance Computer Architecture 1 Two predictable properties of memory references: Temporal Locality:

More information

CS 152 Computer Architecture and Engineering

CS 152 Computer Architecture and Engineering CS 152 Computer Architecture and Engineering Lecture 18: Directory-Based Cache Protocols John Wawrzynek EECS, University of California at Berkeley http://inst.eecs.berkeley.edu/~cs152 Administrivia 2 Recap:

More information

Advanced Parallel Programming I

Advanced Parallel Programming I Advanced Parallel Programming I Alexander Leutgeb, RISC Software GmbH RISC Software GmbH Johannes Kepler University Linz 2016 22.09.2016 1 Levels of Parallelism RISC Software GmbH Johannes Kepler University

More information

Fall 2012 EE 6633: Architecture of Parallel Computers Lecture 4: Shared Address Multiprocessors Acknowledgement: Dave Patterson, UC Berkeley

Fall 2012 EE 6633: Architecture of Parallel Computers Lecture 4: Shared Address Multiprocessors Acknowledgement: Dave Patterson, UC Berkeley Fall 2012 EE 6633: Architecture of Parallel Computers Lecture 4: Shared Address Multiprocessors Acknowledgement: Dave Patterson, UC Berkeley Avinash Kodi Department of Electrical Engineering & Computer

More information

Thread-Level Parallelism

Thread-Level Parallelism Advanced Computer Architecture Thread-Level Parallelism Some slides are from the instructors resources which accompany the 6 th and previous editions. Some slides are from David Patterson, David Culler

More information

AMD Opteron 4200 Series Processor

AMD Opteron 4200 Series Processor What s new in the AMD Opteron 4200 Series Processor (Codenamed Valencia ) and the new Bulldozer Microarchitecture? Platform Processor Socket Chipset Opteron 4000 Opteron 4200 C32 56x0 / 5100 (codenamed

More information

Limitations of parallel processing

Limitations of parallel processing Your professor du jour: Steve Gribble gribble@cs.washington.edu 323B Sieg Hall all material in this lecture in Henessey and Patterson, Chapter 8 635-640 645, 646 654-665 11/8/00 CSE 471 Multiprocessors

More information

Multiprocessors and Thread Level Parallelism CS 282 KAUST Spring 2010 Muhamed Mudawar

Multiprocessors and Thread Level Parallelism CS 282 KAUST Spring 2010 Muhamed Mudawar Multiprocessors and Thread Level Parallelism CS 282 KAUST Spring 2010 Muhamed Mudawar Original slides created by: David Patterson Uniprocessor Performance (SPECint) 80) Performance (vs. VAX-11/78 10000

More information

Lecture 25: Multiprocessors

Lecture 25: Multiprocessors Lecture 25: Multiprocessors Today s topics: Virtual memory wrap-up Snooping-based cache coherence protocol Directory-based cache coherence protocol Synchronization 1 TLB and Cache Is the cache indexed

More information

Cache Coherence in Scalable Machines

Cache Coherence in Scalable Machines ache oherence in Scalable Machines SE 661 arallel and Vector Architectures rof. Muhamed Mudawar omputer Engineering Department King Fahd University of etroleum and Minerals Generic Scalable Multiprocessor

More information

Multiprocessors 1. Outline

Multiprocessors 1. Outline Multiprocessors 1 Outline Multiprocessing Coherence Write Consistency Snooping Building Blocks Snooping protocols and examples Coherence traffic and performance on MP Directory-based protocols and examples

More information

Scalable Multiprocessors

Scalable Multiprocessors Scalable Multiprocessors [ 11.1] scalable system is one in which resources can be added to the system without reaching a hard limit. Of course, there may still be economic limits. s the size of the system

More information

Computer Systems Architecture

Computer Systems Architecture Computer Systems Architecture Lecture 24 Mahadevan Gomathisankaran April 29, 2010 04/29/2010 Lecture 24 CSCE 4610/5610 1 Reminder ABET Feedback: http://www.cse.unt.edu/exitsurvey.cgi?csce+4610+001 Student

More information

CS 152 Computer Architecture and Engineering. Lecture 19: Directory-Based Cache Protocols

CS 152 Computer Architecture and Engineering. Lecture 19: Directory-Based Cache Protocols CS 152 Computer Architecture and Engineering Lecture 19: Directory-Based Protocols Dr. George Michelogiannakis EECS, University of California at Berkeley CRD, Lawrence Berkeley National Laboratory http://inst.eecs.berkeley.edu/~cs152

More information

Overview: Shared Memory Hardware. Shared Address Space Systems. Shared Address Space and Shared Memory Computers. Shared Memory Hardware

Overview: Shared Memory Hardware. Shared Address Space Systems. Shared Address Space and Shared Memory Computers. Shared Memory Hardware Overview: Shared Memory Hardware Shared Address Space Systems overview of shared address space systems example: cache hierarchy of the Intel Core i7 cache coherency protocols: basic ideas, invalidate and

More information

Overview: Shared Memory Hardware

Overview: Shared Memory Hardware Overview: Shared Memory Hardware overview of shared address space systems example: cache hierarchy of the Intel Core i7 cache coherency protocols: basic ideas, invalidate and update protocols false sharing

More information

Modern CPU Architectures

Modern CPU Architectures Modern CPU Architectures Alexander Leutgeb, RISC Software GmbH RISC Software GmbH Johannes Kepler University Linz 2014 16.04.2014 1 Motivation for Parallelism I CPU History RISC Software GmbH Johannes

More information

Module 9: Addendum to Module 6: Shared Memory Multiprocessors Lecture 17: Multiprocessor Organizations and Cache Coherence. The Lecture Contains:

Module 9: Addendum to Module 6: Shared Memory Multiprocessors Lecture 17: Multiprocessor Organizations and Cache Coherence. The Lecture Contains: The Lecture Contains: Shared Memory Multiprocessors Shared Cache Private Cache/Dancehall Distributed Shared Memory Shared vs. Private in CMPs Cache Coherence Cache Coherence: Example What Went Wrong? Implementations

More information

Commercially Available Chip Mul3processors for Research. Welcome to the MulE core Era

Commercially Available Chip Mul3processors for Research. Welcome to the MulE core Era 4/2/11 ommercially Available hip Mul3processors for Research Bruce hilders University of Pi9sburgh h9p://www.cs.pi9.edu/~childers AAO h9p://www.cs.pi9.edu h9p://www.cacao team.org h9p://www.cs.pi9.edu/pm

More information

Lecture 18: Coherence and Synchronization. Topics: directory-based coherence protocols, synchronization primitives (Sections

Lecture 18: Coherence and Synchronization. Topics: directory-based coherence protocols, synchronization primitives (Sections Lecture 18: Coherence and Synchronization Topics: directory-based coherence protocols, synchronization primitives (Sections 5.1-5.5) 1 Cache Coherence Protocols Directory-based: A single location (directory)

More information

Scalable Cache Coherent Systems

Scalable Cache Coherent Systems NUM SS Scalable ache oherent Systems Scalable distributed shared memory machines ssumptions: rocessor-ache-memory nodes connected by scalable network. Distributed shared physical address space. ommunication

More information

Handout 3 Multiprocessor and thread level parallelism

Handout 3 Multiprocessor and thread level parallelism Handout 3 Multiprocessor and thread level parallelism Outline Review MP Motivation SISD v SIMD (SIMT) v MIMD Centralized vs Distributed Memory MESI and Directory Cache Coherency Synchronization and Relaxed

More information

Lecture 18: Coherence Protocols. Topics: coherence protocols for symmetric and distributed shared-memory multiprocessors (Sections

Lecture 18: Coherence Protocols. Topics: coherence protocols for symmetric and distributed shared-memory multiprocessors (Sections Lecture 18: Coherence Protocols Topics: coherence protocols for symmetric and distributed shared-memory multiprocessors (Sections 4.2-4.4) 1 SMP/UMA/Centralized Memory Multiprocessor Main Memory I/O System

More information

FinisTerrae: Memory Hierarchy and Mapping

FinisTerrae: Memory Hierarchy and Mapping galicia supercomputing center Applications & Projects Department FinisTerrae: Memory Hierarchy and Mapping Technical Report CESGA-2010-001 Juan Carlos Pichel Tuesday 12 th January, 2010 Contents Contents

More information

Parallel Computer Architecture Spring Shared Memory Multiprocessors Memory Coherence

Parallel Computer Architecture Spring Shared Memory Multiprocessors Memory Coherence Parallel Computer Architecture Spring 2018 Shared Memory Multiprocessors Memory Coherence Nikos Bellas Computer and Communications Engineering Department University of Thessaly Parallel Computer Architecture

More information

Comp. Org II, Spring

Comp. Org II, Spring Lecture 11 Parallel Processor Architectures Flynn s taxonomy from 1972 Parallel Processing & computers 8th edition: Ch 17 & 18 Earlier editions contain only Parallel Processing (Sta09 Fig 17.1) 2 Parallel

More information

Parallel Processing & Multicore computers

Parallel Processing & Multicore computers Lecture 11 Parallel Processing & Multicore computers 8th edition: Ch 17 & 18 Earlier editions contain only Parallel Processing Parallel Processor Architectures Flynn s taxonomy from 1972 (Sta09 Fig 17.1)

More information

Chapter 6. Parallel Processors from Client to Cloud Part 2 COMPUTER ORGANIZATION AND DESIGN. Homogeneous & Heterogeneous Multicore Architectures

Chapter 6. Parallel Processors from Client to Cloud Part 2 COMPUTER ORGANIZATION AND DESIGN. Homogeneous & Heterogeneous Multicore Architectures COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface 5 th Edition Chapter 6 Parallel Processors from Client to Cloud Part 2 Homogeneous & Heterogeneous Multicore Architectures Intel XEON 22nm

More information