Speculative Execution Side Channel Mitigations
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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. -
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. -
2. Instruction Set Architecture
!1 2. ISA Gebotys ECE 222 2. Instruction Set Architecture “Ideally, your initial instruction set should be an exemplar, …” " Instruction set architecture (ISA) defines the interface between the hardware and software# " instruction set is the language of the computer# " RISCV instructions are 32-bits, instruction[31:0]# " RISC-V assembly1 language notation # " uses 64-bit registers, 64-bits refer to double word, 32-bits refers to word (8-bits is byte).# " there are 32 registers, namely x0-x31, where x0 is always zero # " to perform arithmetic operations (add, sub, shift, logical) data must always be in registers # " the number of variables in programs is typically larger than 32, hence ‘less frequently used’ [or those used later] variables are ‘spilled’ into memory [spilling registers]# " registers are faster and more energy e$cient than memory# " for embedded applications where code size is important, a 16-bit instruction set exists, RISC-V compressed (e.g. others exist also ARM Thumb and Thumb2)# " byte addressing is used, little endian (where address of 64-bit word refers to address of ‘little' or rightmost byte, [containing bit 0 of word]) so sequential double word accesses di%er by 8 e.g. byte address 0 holds the first double word and byte address 8 holds next double word. (Byte addressing allows the supports of two byte instructions)# " memory contains 261 memory words - using load/store instructions e.g. 64-bits available (bits 63 downto 0, 3 of those bits are used for byte addressing, leaving 61 bits)# " Program counter register (PC) -
18-741 Advanced Computer Architecture Lecture 1: Intro And
Computer Architecture Lecture 10: Branch Prediction Prof. Onur Mutlu ETH Zürich Fall 2017 25 October 2017 Mid-Semester Exam November 30 In class Questions similar to homework questions 2 High-Level Summary of Last Week SIMD Processing Array Processors Vector Processors SIMD Extensions Graphics Processing Units GPU Architecture GPU Programming 3 Agenda for Today & Tomorrow Control Dependence Handling Problem Six solutions Branch Prediction Other Methods of Control Dependence Handling 4 Required Readings McFarling, “Combining Branch Predictors,” DEC WRL Technical Report, 1993. Required T. Yeh and Y. Patt, “Two-Level Adaptive Training Branch Prediction,” Intl. Symposium on Microarchitecture, November 1991. MICRO Test of Time Award Winner (after 24 years) Required 5 Recommended Readings Smith and Sohi, “The Microarchitecture of Superscalar Processors,” Proceedings of the IEEE, 1995 More advanced pipelining Interrupt and exception handling Out-of-order and superscalar execution concepts Recommended Kessler, “The Alpha 21264 Microprocessor,” IEEE Micro 1999. Recommended 6 Control Dependence Handling 7 Control Dependence Question: What should the fetch PC be in the next cycle? Answer: The address of the next instruction All instructions are control dependent on previous ones. Why? If the fetched instruction is a non-control-flow instruction: Next Fetch PC is the address of the next-sequential instruction Easy to determine if we know the size of the fetched instruction If the instruction that is fetched is a control-flow -
OS and Compiler Considerations in the Design of the IA-64 Architecture
OS and Compiler Considerations in the Design of the IA-64 Architecture Rumi Zahir (Intel Corporation) Dale Morris, Jonathan Ross (Hewlett-Packard Company) Drew Hess (Lucasfilm Ltd.) This is an electronic reproduction of “OS and Compiler Considerations in the Design of the IA-64 Architecture” originally published in ASPLOS-IX (the Ninth International Conference on Architectural Support for Programming Languages and Operating Systems) held in Cambridge, MA in November 2000. Copyright © A.C.M. 2000 1-58113-317-0/00/0011...$5.00 Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full cita- tion on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permis- sion and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or [email protected]. ASPLOS 2000 Cambridge, MA Nov. 12-15 , 2000 212 OS and Compiler Considerations in the Design of the IA-64 Architecture Rumi Zahir Jonathan Ross Dale Morris Drew Hess Intel Corporation Hewlett-Packard Company Lucas Digital Ltd. 2200 Mission College Blvd. 19447 Pruneridge Ave. P.O. Box 2459 Santa Clara, CA 95054 Cupertino, CA 95014 San Rafael, CA 94912 [email protected] [email protected] [email protected] [email protected] ABSTRACT system collaborate to deliver higher-performance systems. -
Selective Eager Execution on the Polypath Architecture
Selective Eager Execution on the PolyPath Architecture Artur Klauser, Abhijit Paithankar, Dirk Grunwald [klauser,pvega,grunwald]@cs.colorado.edu University of Colorado, Department of Computer Science Boulder, CO 80309-0430 Abstract average misprediction latency is the sum of the architected latency (pipeline depth) and a variable latency, which depends on data de- Control-flow misprediction penalties are a major impediment pendencies of the branch instruction. The overall cycles lost due to high performance in wide-issue superscalar processors. In this to branch mispredictions are the product of the total number of paper we present Selective Eager Execution (SEE), an execution mispredictions incurred during program execution and the average model to overcome mis-speculation penalties by executing both misprediction latency. Thus, reduction of either component helps paths after diffident branches. We present the micro-architecture decrease performance loss due to control mis-speculation. of the PolyPath processor, which is an extension of an aggressive In this paper we propose Selective Eager Execution (SEE) and superscalar, out-of-order architecture. The PolyPath architecture the PolyPath architecture model, which help to overcome branch uses a novel instruction tagging and register renaming mechanism misprediction latency. SEE recognizes the fact that some branches to execute instructions from multiple paths simultaneously in the are predicted more accurately than others, where it draws from re- same processor pipeline, while retaining maximum resource avail- search in branch confidence estimation [4, 6]. SEE behaves like ability for single-path code sequences. a normal monopath speculative execution architecture for highly Results of our execution-driven, pipeline-level simulations predictable branches; it predicts the most likely successor path of a show that SEE can improve performance by as much as 36% for branch, and evaluates instructions only along this path. -
State of the Art Regarding Both Compiler Optimizations for Instruction Fetch, and the Fetch Architectures for Which We Try to Optimize Our Applications
¢¡¤£¥¡§¦ ¨ © ¡§ ¦ £ ¡ In this work we are trying to increase fetch performance using both software and hardware tech- niques, combining them to obtain maximum performance at the minimum cost and complexity. In this chapter we introduce the state of the art regarding both compiler optimizations for instruction fetch, and the fetch architectures for which we try to optimize our applications. The first section introduces code layout optimizations. The compiler can influence instruction fetch performance by selecting the layout of instructions in memory. This determines both the conflict rate of the instruction cache, and the behavior (taken or not taken) of conditional branches. We present an overview of the different layout algorithms proposed in the literature, and how our own algorithm relates to them. The second section shows how instruction fetch architectures have evolved from pipelined processors to the more aggressive wide issue superscalars. This implies increasing fetch perfor- mance from a single instruction every few cycles, to one instruction per cycle, to a full basic block per cycle, and finally to multiple basic blocks per cycle. We emphasize the description of the trace cache, as it will be the reference architecture in most of our work. 2.1 Code layout optimizations The mapping of instruction to memory is determined by the compiler. This mapping determines not only the code page where an instruction is found, but also the cache line (or which set in a set associative cache) it will map to. Furthermore, a branch will be taken or not taken depending on the placement of the successor basic blocks. By mapping instructions in a different order, the compiler has a direct impact on the fetch engine performance. -
Exploiting Branch Target Injection Jann Horn, Google Project Zero
Exploiting Branch Target Injection Jann Horn, Google Project Zero 1 Outline ● Introduction ● Reverse-engineering branch prediction ● Leaking host memory from KVM 2 Disclaimer ● I haven't worked in CPU design ● I don't really understand how CPUs work ● Large parts of this talk are based on guesses ● This isn't necessarily how all CPUs work 3 Variants overview Spectre Meltdown ● CVE-2017-5753 ● CVE-2017-5715 ● CVE-2017-5754 ● Variant 1 ● Variant 2 ● Variant 3 ● Bounds Check ● Branch Target ● Rogue Data Cache Bypass Injection Load ● Primarily affects ● Primarily affects ● Affects kernels (and interpreters/JITs kernels/hypervisors architecturally equivalent software) 4 Performance ● Modern consumer CPU clock rates: ~4GHz ● Memory is slow: ~170 clock cycles latency on my machine ➢ CPU needs to work around high memory access latencies ● Adding parallelism is easier than making processing faster ➢ CPU needs to do things in parallel for performance ● Performance optimizations can lead to security issues! 5 Performance Optimization Resources ● everyone wants programs to run fast ➢ processor vendors want application authors to be able to write fast code ● architectural behavior requires architecture documentation; performance optimization requires microarchitecture documentation ➢ if you want information about microarchitecture, read performance optimization guides ● Intel: https://software.intel.com/en-us/articles/intel-sdm#optimization ("optimization reference manual") ● AMD: https://developer.amd.com/resources/developer-guides-manuals/ ("Software Optimization Guide") 6 (vaguely based on optimization manuals) Out-of-order execution front end out-of-order engine port (scheduler, renaming, ...) port instruction stream add rax, 9 add rax, 8 inc rbx port inc rbx sub rax, rbx mov [rcx], rax port cmp rax, 16 .. -
Igpu: Exception Support and Speculative Execution on Gpus
Appears in the 39th International Symposium on Computer Architecture, 2012 iGPU: Exception Support and Speculative Execution on GPUs Jaikrishnan Menon, Marc de Kruijf, Karthikeyan Sankaralingam Department of Computer Sciences University of Wisconsin-Madison {menon, dekruijf, karu}@cs.wisc.edu Abstract the evolution of traditional CPUs to illuminate why this pro- gression appears natural and imminent. Since the introduction of fully programmable vertex Just as CPU programmers were forced to explicitly man- shader hardware, GPU computing has made tremendous age CPU memories in the days before virtual memory, for advances. Exception support and speculative execution are almost a decade, GPU programmers directly and explicitly the next steps to expand the scope and improve the usabil- managed the GPU memory hierarchy. The recent release ity of GPUs. However, traditional mechanisms to support of NVIDIA’s Fermi architecture and AMD’s Fusion archi- exceptions and speculative execution are highly intrusive to tecture, however, has brought GPUs to an inflection point: GPU hardware design. This paper builds on two related in- both architectures implement a unified address space that sights to provide a unified lightweight mechanism for sup- eliminates the need for explicit memory movement to and porting exceptions and speculation on GPUs. from GPU memory structures. Yet, without demand pag- First, we observe that GPU programs can be broken into ing, something taken for granted in the CPU space, pro- code regions that contain little or no live register state at grammers must still explicitly reason about available mem- their entry point. We then also recognize that it is simple to ory. The drawbacks of exposing physical memory size to generate these regions in such a way that they are idempo- programmers are well known. -
Branch Prediction for Network Processors
BRANCH PREDICTION FOR NETWORK PROCESSORS by David Bermingham, B.Eng Submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy Dublin City University School of School of Electronic Engineering Supervisors: Dr. Xiaojun Wang Prof. Lingling Sun September 2010 I hereby certify that this material, which I now submit for assessment on the programme of study leading to the award of Doctor of Philosophy is entirely my own work, that I have exercised reasonable care to ensure that the work is original, and does not to the best of my knowledge breach any law of copy- right, and has not been taken from the work of others save and to the extent that such work has been cited and acknowledged within the text of my work. Signed: David Bermingham (Candidate) ID: Date: TABLE OF CONTENTS Abstract vii List of Figures ix List of Tables xii List of Acronyms xiv List of Peer-Reviewed Publications xvi Acknowledgements xviii 1 Introduction 1 1.1 Network Processors . 1 1.2 Trends Within Networks . 2 1.2.1 Bandwidth Growth . 2 1.2.2 Network Technologies . 3 1.2.3 Application and Service Demands . 3 1.3 Network Trends and Network Processors . 6 1.3.1 The Motivation for This Thesis . 7 1.4 Research Objectives . 9 1.5 Thesis Structure . 10 iii 2 Technical Background 12 2.1 Overview . 12 2.2 Networks . 13 2.2.1 Network Protocols . 13 2.2.2 Network Technologies . 14 2.2.3 Router Architecture . 17 2.3 Network Processors . 19 2.3.1 Intel IXP-28XX Network Processor . -
A Survey of Published Attacks on Intel
1 A Survey of Published Attacks on Intel SGX Alexander Nilsson∗y, Pegah Nikbakht Bideh∗, Joakim Brorsson∗zx falexander.nilsson,pegah.nikbakht_bideh,[email protected] ∗Lund University, Department of Electrical and Information Technology, Sweden yAdvenica AB, Sweden zCombitech AB, Sweden xHyker Security AB, Sweden Abstract—Intel Software Guard Extensions (SGX) provides a Unfortunately, a relatively large number of flaws and attacks trusted execution environment (TEE) to run code and operate against SGX have been published by researchers over the last sensitive data. SGX provides runtime hardware protection where few years. both code and data are protected even if other code components are malicious. However, recently many attacks targeting SGX have been identified and introduced that can thwart the hardware A. Contribution defence provided by SGX. In this paper we present a survey of all attacks specifically targeting Intel SGX that are known In this paper, we present the first comprehensive review to the authors, to date. We categorized the attacks based on that includes all known attacks specific to SGX, including their implementation details into 7 different categories. We also controlled channel attacks, cache-attacks, speculative execu- look into the available defence mechanisms against identified tion attacks, branch prediction attacks, rogue data cache loads, attacks and categorize the available types of mitigations for each presented attack. microarchitectural data sampling and software-based fault in- jection attacks. For most of the presented attacks, there are countermeasures and mitigations that have been deployed as microcode patches by Intel or that can be employed by the I. INTRODUCTION application developer herself to make the attack more difficult (or impossible) to exploit.