Itanium Processor Microarchitecture
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Memory Consistency
Lecture 9: Memory Consistency Parallel Computing Stanford CS149, Winter 2019 Midterm ▪ Feb 12 ▪ Open notes ▪ Practice midterm Stanford CS149, Winter 2019 Shared Memory Behavior ▪ Intuition says loads should return latest value written - What is latest? - Coherence: only one memory location - Consistency: apparent ordering for all locations - Order in which memory operations performed by one thread become visible to other threads ▪ Affects - Programmability: how programmers reason about program behavior - Allowed behavior of multithreaded programs executing with shared memory - Performance: limits HW/SW optimizations that can be used - Reordering memory operations to hide latency Stanford CS149, Winter 2019 Today: what you should know ▪ Understand the motivation for relaxed consistency models ▪ Understand the implications of relaxing W→R ordering Stanford CS149, Winter 2019 Today: who should care ▪ Anyone who: - Wants to implement a synchronization library - Will ever work a job in kernel (or driver) development - Seeks to implement lock-free data structures * - Does any of the above on ARM processors ** * Topic of a later lecture ** For reasons to be described later Stanford CS149, Winter 2019 Memory coherence vs. memory consistency ▪ Memory coherence defines requirements for the observed Observed chronology of operations on address X behavior of reads and writes to the same memory location - All processors must agree on the order of reads/writes to X P0 write: 5 - In other words: it is possible to put all operations involving X on a timeline such P1 read (5) that the observations of all processors are consistent with that timeline P2 write: 10 ▪ Memory consistency defines the behavior of reads and writes to different locations (as observed by other processors) P2 write: 11 - Coherence only guarantees that writes to address X will eventually propagate to other processors P1 read (11) - Consistency deals with when writes to X propagate to other processors, relative to reads and writes to other addresses Stanford CS149, Winter 2019 Coherence vs. -
Inside Intel® Core™ Microarchitecture Setting New Standards for Energy-Efficient Performance
White Paper Inside Intel® Core™ Microarchitecture Setting New Standards for Energy-Efficient Performance Ofri Wechsler Intel Fellow, Mobility Group Director, Mobility Microprocessor Architecture Intel Corporation White Paper Inside Intel®Core™ Microarchitecture Introduction Introduction 2 The Intel® Core™ microarchitecture is a new foundation for Intel®Core™ Microarchitecture Design Goals 3 Intel® architecture-based desktop, mobile, and mainstream server multi-core processors. This state-of-the-art multi-core optimized Delivering Energy-Efficient Performance 4 and power-efficient microarchitecture is designed to deliver Intel®Core™ Microarchitecture Innovations 5 increased performance and performance-per-watt—thus increasing Intel® Wide Dynamic Execution 6 overall energy efficiency. This new microarchitecture extends the energy efficient philosophy first delivered in Intel's mobile Intel® Intelligent Power Capability 8 microarchitecture found in the Intel® Pentium® M processor, and Intel® Advanced Smart Cache 8 greatly enhances it with many new and leading edge microar- Intel® Smart Memory Access 9 chitectural innovations as well as existing Intel NetBurst® microarchitecture features. What’s more, it incorporates many Intel® Advanced Digital Media Boost 10 new and significant innovations designed to optimize the Intel®Core™ Microarchitecture and Software 11 power, performance, and scalability of multi-core processors. Summary 12 The Intel Core microarchitecture shows Intel’s continued Learn More 12 innovation by delivering both greater energy efficiency Author Biographies 12 and compute capability required for the new workloads and usage models now making their way across computing. With its higher performance and low power, the new Intel Core microarchitecture will be the basis for many new solutions and form factors. In the home, these include higher performing, ultra-quiet, sleek and low-power computer designs, and new advances in more sophisticated, user-friendly entertainment systems. -
Computer Science 246 Computer Architecture Spring 2010 Harvard University
Computer Science 246 Computer Architecture Spring 2010 Harvard University Instructor: Prof. David Brooks [email protected] Dynamic Branch Prediction, Speculation, and Multiple Issue Computer Science 246 David Brooks Lecture Outline • Tomasulo’s Algorithm Review (3.1-3.3) • Pointer-Based Renaming (MIPS R10000) • Dynamic Branch Prediction (3.4) • Other Front-end Optimizations (3.5) – Branch Target Buffers/Return Address Stack Computer Science 246 David Brooks Tomasulo Review • Reservation Stations – Distribute RAW hazard detection – Renaming eliminates WAW hazards – Buffering values in Reservation Stations removes WARs – Tag match in CDB requires many associative compares • Common Data Bus – Achilles heal of Tomasulo – Multiple writebacks (multiple CDBs) expensive • Load/Store reordering – Load address compared with store address in store buffer Computer Science 246 David Brooks Tomasulo Organization From Mem FP Op FP Registers Queue Load Buffers Load1 Load2 Load3 Load4 Load5 Store Load6 Buffers Add1 Add2 Mult1 Add3 Mult2 Reservation To Mem Stations FP adders FP multipliers Common Data Bus (CDB) Tomasulo Review 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 LD F0, 0(R1) Iss M1 M2 M3 M4 M5 M6 M7 M8 Wb MUL F4, F0, F2 Iss Iss Iss Iss Iss Iss Iss Iss Iss Ex Ex Ex Ex Wb SD 0(R1), F0 Iss Iss Iss Iss Iss Iss Iss Iss Iss Iss Iss Iss Iss M1 M2 M3 Wb SUBI R1, R1, 8 Iss Ex Wb BNEZ R1, Loop Iss Ex Wb LD F0, 0(R1) Iss Iss Iss Iss M Wb MUL F4, F0, F2 Iss Iss Iss Iss Iss Ex Ex Ex Ex Wb SD 0(R1), F0 Iss Iss Iss Iss Iss Iss Iss Iss Iss M1 M2 -
Branch Prediction Side Channel Attacks
Predicting Secret Keys via Branch Prediction Onur Ac³i»cmez1, Jean-Pierre Seifert2;3, and C»etin Kaya Ko»c1;4 1 Oregon State University School of Electrical Engineering and Computer Science Corvallis, OR 97331, USA 2 Applied Security Research Group The Center for Computational Mathematics and Scienti¯c Computation Faculty of Science and Science Education University of Haifa Haifa 31905, Israel 3 Institute for Computer Science University of Innsbruck 6020 Innsbruck, Austria 4 Information Security Research Center Istanbul Commerce University EminÄonÄu,Istanbul 34112, Turkey [email protected], [email protected], [email protected] Abstract. This paper presents a new software side-channel attack | enabled by the branch prediction capability common to all modern high-performance CPUs. The penalty payed (extra clock cycles) for a mispredicted branch can be used for cryptanalysis of cryptographic primitives that employ a data-dependent program flow. Analogous to the recently described cache-based side-channel attacks our attacks also allow an unprivileged process to attack other processes running in parallel on the same processor, despite sophisticated partitioning methods such as memory protection, sandboxing or even virtualization. We will discuss in detail several such attacks for the example of RSA, and experimentally show their applicability to real systems, such as OpenSSL and Linux. More speci¯cally, we will present four di®erent types of attacks, which are all derived from the basic idea underlying our novel side-channel attack. Moreover, we also demonstrate the strength of the branch prediction side-channel attack by rendering the obvious countermeasure in this context (Montgomery Multiplication with dummy-reduction) as useless. -
1 Introduction
Cambridge University Press 978-0-521-76992-1 - Microprocessor Architecture: From Simple Pipelines to Chip Multiprocessors Jean-Loup Baer Excerpt More information 1 Introduction Modern computer systems built from the most sophisticated microprocessors and extensive memory hierarchies achieve their high performance through a combina- tion of dramatic improvements in technology and advances in computer architec- ture. Advances in technology have resulted in exponential growth rates in raw speed (i.e., clock frequency) and in the amount of logic (number of transistors) that can be put on a chip. Computer architects have exploited these factors in order to further enhance performance using architectural techniques, which are the main subject of this book. Microprocessors are over 30 years old: the Intel 4004 was introduced in 1971. The functionality of the 4004 compared to that of the mainframes of that period (for example, the IBM System/370) was minuscule. Today, just over thirty years later, workstations powered by engines such as (in alphabetical order and without specific processor numbers) the AMD Athlon, IBM PowerPC, Intel Pentium, and Sun UltraSPARC can rival or surpass in both performance and functionality the few remaining mainframes and at a much lower cost. Servers and supercomputers are more often than not made up of collections of microprocessor systems. It would be wrong to assume, though, that the three tenets that computer archi- tects have followed, namely pipelining, parallelism, and the principle of locality, were discovered with the birth of microprocessors. They were all at the basis of the design of previous (super)computers. The advances in technology made their implementa- tions more practical and spurred further refinements. -
BRANCH PREDICTORS Mahdi Nazm Bojnordi Assistant Professor School of Computing University of Utah
BRANCH PREDICTORS Mahdi Nazm Bojnordi Assistant Professor School of Computing University of Utah CS/ECE 6810: Computer Architecture Overview ¨ Announcements ¤ Homework 2 release: Sept. 26th ¨ This lecture ¤ Dynamic branch prediction ¤ Counter based branch predictor ¤ Correlating branch predictor ¤ Global vs. local branch predictors Big Picture: Why Branch Prediction? ¨ Problem: performance is mainly limited by the number of instructions fetched per second ¨ Solution: deeper and wider frontend ¨ Challenge: handling branch instructions Big Picture: How to Predict Branch? ¨ Static prediction (based on direction or profile) ¨ Always not-taken ¨ Target = next PC ¨ Always taken ¨ Target = unknown clk direction target ¨ Dynamic prediction clk PC + ¨ Special hardware using PC NPC 4 Inst. Memory Instruction Recall: Dynamic Branch Prediction ¨ Hardware unit capable of learning at runtime ¤ 1. Prediction logic n Direction (taken or not-taken) n Target address (where to fetch next) ¤ 2. Outcome validation and training n Outcome is computed regardless of prediction ¤ 3. Recovery from misprediction n Nullify the effect of instructions on the wrong path Branch Prediction ¨ Goal: avoiding stall cycles caused by branches ¨ Solution: static or dynamic branch predictor ¤ 1. prediction ¤ 2. validation and training ¤ 3. recovery from misprediction ¨ Performance is influenced by the frequency of branches (b), prediction accuracy (a), and misprediction cost (c) Branch Prediction ¨ Goal: avoiding stall cycles caused by branches ¨ Solution: static or dynamic branch predictor ¤ 1. prediction ¤ 2. validation and training ¤ 3. recovery from misprediction ¨ Performance is influenced by the frequency of branches (b), prediction accuracy (a), and misprediction cost (c) ��� ���� ��� 1 + �� ������� = = 234 = ��� ���� ���567 1 + 1 − � �� Problem ¨ A pipelined processor requires 3 stall cycles to compute the outcome of every branch before fetching next instruction; due to perfect forwarding/bypassing, no stall cycles are required for data/structural hazards; every 5th instruction is a branch. -
Instruction Latencies and Throughput for AMD and Intel X86 Processors
Instruction latencies and throughput for AMD and Intel x86 processors Torbj¨ornGranlund 2019-08-02 09:05Z Copyright Torbj¨ornGranlund 2005{2019. Verbatim copying and distribution of this entire article is permitted in any medium, provided this notice is preserved. This report is work-in-progress. A newer version might be available here: https://gmplib.org/~tege/x86-timing.pdf In this short report we present latency and throughput data for various x86 processors. We only present data on integer operations. The data on integer MMX and SSE2 instructions is currently limited. We might present more complete data in the future, if there is enough interest. There are several reasons for presenting this report: 1. Intel's published data were in the past incomplete and full of errors. 2. Intel did not publish any data for 64-bit operations. 3. To allow straightforward comparison of an important aspect of AMD and Intel pipelines. The here presented data is the result of extensive timing tests. While we have made an effort to make sure the data is accurate, the reader is cautioned that some errors might have crept in. 1 Nomenclature and notation LNN means latency for NN-bit operation.TNN means throughput for NN-bit operation. The term throughput is used to mean number of instructions per cycle of this type that can be sustained. That implies that more throughput is better, which is consistent with how most people understand the term. Intel use that same term in the exact opposite meaning in their manuals. The notation "P6 0-E", "P4 F0", etc, are used to save table header space. -
POWER-AWARE MICROARCHITECTURE: Design and Modeling Challenges for Next-Generation Microprocessors
POWER-AWARE MICROARCHITECTURE: Design and Modeling Challenges for Next-Generation Microprocessors THE ABILITY TO ESTIMATE POWER CONSUMPTION DURING EARLY-STAGE DEFINITION AND TRADE-OFF STUDIES IS A KEY NEW METHODOLOGY ENHANCEMENT. OPPORTUNITIES FOR SAVING POWER CAN BE EXPOSED VIA MICROARCHITECTURE-LEVEL MODELING, PARTICULARLY THROUGH CLOCK- GATING AND DYNAMIC ADAPTATION. Power dissipation limits have Thus far, most of the work done in the area David M. Brooks emerged as a major constraint in the design of high-level power estimation has been focused of microprocessors. At the low end of the per- at the register-transfer-level (RTL) description Pradip Bose formance spectrum, namely in the world of in the processor design flow. Only recently have handheld and portable devices or systems, we seen a surge of interest in estimating power Stanley E. Schuster power has always dominated over perfor- at the microarchitecture definition stage, and mance (execution time) as the primary design specific work on power-efficient microarchi- Hans Jacobson issue. Battery life and system cost constraints tecture design has been reported.2-8 drive the design team to consider power over Here, we describe the approach of using Prabhakar N. Kudva performance in such a scenario. energy-enabled performance simulators in Increasingly, however, power is also a key early design. We examine some of the emerg- Alper Buyuktosunoglu design issue in the workstation and server mar- ing paradigms in processor design and com- kets (see Gowan et al.)1 In this high-end arena ment on their inherent power-performance John-David Wellman the increasing microarchitectural complexities, characteristics. clock frequencies, and die sizes push the chip- Victor Zyuban level—and hence the system-level—power Power-performance efficiency consumption to such levels that traditionally See the “Power-performance fundamentals” Manish Gupta air-cooled multiprocessor server boxes may box. -
The Intel Microprocessors: Architecture, Programming and Interfacing Introduction to the Microprocessor and Computer
Microprocessors (0630371) Fall 2010/2011 – Lecture Notes # 1 The Intel Microprocessors: Architecture, Programming and Interfacing Introduction to the Microprocessor and computer Outline of the Lecture Evolution of programming languages. Microcomputer Architecture. Instruction Execution Cycle. Evolution of programming languages: Machine language - the programmer had to remember the machine codes for various operations, and had to remember the locations of the data in the main memory like: 0101 0011 0111… Assembly Language - an instruction is an easy –to- remember form called a mnemonic code . Example: Assembly Language Machine Language Load 100100 ADD 100101 SUB 100011 We need a program called an assembler that translates the assembly language instructions into machine language. High-level languages Fortran, Cobol, Pascal, C++, C# and java. We need a compiler to translate instructions written in high-level languages into machine code. Microprocessor-based system (Micro computer) Architecture Data Bus, I/O bus Memory Storage I/O I/O Registers Unit Device Device Central Processing Unit #1 #2 (CPU ) ALU CU Clock Control Unit Address Bus The figure shows the main components of a microprocessor-based system: CPU- Central Processing Unit , where calculations and logic operations are done. CPU contains registers , a high-frequency clock , a control unit ( CU ) and an arithmetic logic unit ( ALU ). o Clock : synchronizes the internal operations of the CPU with other system components using clock pulsing at a constant rate (the basic unit of time for machine instructions is a machine cycle or clock cycle) One cycle A machine instruction requires at least one clock cycle some instruction require 50 clocks. o Control Unit (CU) - generate the needed control signals to coordinate the sequencing of steps involved in executing machine instructions: (fetches data and instructions and decodes addresses for the ALU). -
UNIT 8B a Full Adder
UNIT 8B Computer Organization: Levels of Abstraction 15110 Principles of Computing, 1 Carnegie Mellon University - CORTINA A Full Adder C ABCin Cout S in 0 0 0 A 0 0 1 0 1 0 B 0 1 1 1 0 0 1 0 1 C S out 1 1 0 1 1 1 15110 Principles of Computing, 2 Carnegie Mellon University - CORTINA 1 A Full Adder C ABCin Cout S in 0 0 0 0 0 A 0 0 1 0 1 0 1 0 0 1 B 0 1 1 1 0 1 0 0 0 1 1 0 1 1 0 C S out 1 1 0 1 0 1 1 1 1 1 ⊕ ⊕ S = A B Cin ⊕ ∧ ∨ ∧ Cout = ((A B) C) (A B) 15110 Principles of Computing, 3 Carnegie Mellon University - CORTINA Full Adder (FA) AB 1-bit Cout Full Cin Adder S 15110 Principles of Computing, 4 Carnegie Mellon University - CORTINA 2 Another Full Adder (FA) http://students.cs.tamu.edu/wanglei/csce350/handout/lab6.html AB 1-bit Cout Full Cin Adder S 15110 Principles of Computing, 5 Carnegie Mellon University - CORTINA 8-bit Full Adder A7 B7 A2 B2 A1 B1 A0 B0 1-bit 1-bit 1-bit 1-bit ... Cout Full Full Full Full Cin Adder Adder Adder Adder S7 S2 S1 S0 AB 8 ⁄ ⁄ 8 C 8-bit C out FA in ⁄ 8 S 15110 Principles of Computing, 6 Carnegie Mellon University - CORTINA 3 Multiplexer (MUX) • A multiplexer chooses between a set of inputs. D1 D 2 MUX F D3 D ABF 4 0 0 D1 AB 0 1 D2 1 0 D3 1 1 D4 http://www.cise.ufl.edu/~mssz/CompOrg/CDAintro.html 15110 Principles of Computing, 7 Carnegie Mellon University - CORTINA Arithmetic Logic Unit (ALU) OP 1OP 0 Carry In & OP OP 0 OP 1 F 0 0 A ∧ B 0 1 A ∨ B 1 0 A 1 1 A + B http://cs-alb-pc3.massey.ac.nz/notes/59304/l4.html 15110 Principles of Computing, 8 Carnegie Mellon University - CORTINA 4 Flip Flop • A flip flop is a sequential circuit that is able to maintain (save) a state. -
Intel® Processor Graphics: Architecture & Programming
Intel® Processor Graphics: Architecture & Programming Jason Ross – Principal Engineer, GPU Architect Ken Lueh – Sr. Principal Engineer, Compiler Architect Subramaniam Maiyuran – Sr. Principal Engineer, GPU Architect Agenda 1. Introduction (Jason) 2. Compute Architecture Evolution (Jason) 3. Chip Level Architecture (Jason) Subslices, slices, products 4. Gen Compute Architecture (Maiyuran) Execution units 5. Instruction Set Architecture (Ken) 6. Memory Sharing Architecture (Jason) 7. Mapping Programming Models to Architecture (Jason) 8. Summary 2 Compute Applications * “The Intel® Iris™ Pro graphics and the Intel® Core™ i7 processor are … allowing me to do all of this while the graphics and video * never stopping” Dave Helmly, Solution Consulting Pro Video/Audio, Adobe Adobe Premiere Pro demonstration: http://www.youtube.com/watch?v=u0J57J6Hppg “We are very pleased that Intel is fully supporting OpenCL. DirectX11.2 We think there is a bright future for this technology.” Michael Compute Shader Bryant, Director of Marketing, Sony Creative Software Vegas* Software Family by Sony* * Optimized with OpenCL and Intel® Processor Graphics http://www.youtube.com/watch?v=_KHVOCwTdno * “Implementing [OpenCL] in our award-winning video editor, * PowerDirector, has created tremendous value for our customers by enabling big gains in video processing speed and, consequently, a significant reduction in total video editing time.” Louis Chen, Assistant Vice President, CyberLink Corp. * "Capture One Pro introduces …optimizations for Haswell, enabling remarkably -
Memory Ordering: a Value-Based Approach
Memory Ordering: A Value-Based Approach Harold W. Cain Mikko H. Lipasti Computer Sciences Dept. Dept. of Elec. and Comp. Engr. Univ. of Wisconsin-Madison Univ. of Wisconsin-Madison [email protected] [email protected] Abstract queues, etc.) used to find independent operations and cor- rectly execute them out of program order are often con- Conventional out-of-order processors employ a multi- strained by clock cycle time. In order to decrease clock ported, fully-associative load queue to guarantee correct cycle time, the size of these conventional structures must memory reference order both within a single thread of exe- usually decrease, also decreasing IPC. Conversely, IPC cution and across threads in a multiprocessor system. As may be increased by increasing their size, but this also improvements in process technology and pipelining lead to increases their access time and may degrade clock fre- higher clock frequencies, scaling this complex structure to quency. accommodate a larger number of in-flight loads becomes There has been much recent research on mitigating this difficult if not impossible. Furthermore, each access to this negative feedback loop by scaling structures in ways that complex structure consumes excessive amounts of energy. are amenable to high clock frequencies without negatively In this paper, we solve the associative load queue scalabil- affecting IPC. Much of this work has focused on the ity problem by completely eliminating the associative load instruction issue queue, physical register file, and bypass queue. Instead, data dependences and memory consistency paths, but very little has focused on the load queue or store constraints are enforced by simply re-executing load queue [1][18][21].