4. Instruction Tables Lists of Instruction Latencies, Throughputs and Micro-Operation Breakdowns for Intel, AMD and VIA Cpus
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07 Vectorization for Intel C++ & Fortran Compiler .Pdf
Vectorization for Intel® C++ & Fortran Compiler Presenter: Georg Zitzlsberger Date: 10-07-2015 1 Agenda • Introduction to SIMD for Intel® Architecture • Compiler & Vectorization • Validating Vectorization Success • Reasons for Vectorization Fails • Intel® Cilk™ Plus • Summary 2 Optimization Notice Copyright © 2015, Intel Corporation. All rights reserved. *Other names and brands may be claimed as the property of others. Vectorization • Single Instruction Multiple Data (SIMD): . Processing vector with a single operation . Provides data level parallelism (DLP) . Because of DLP more efficient than scalar processing • Vector: . Consists of more than one element . Elements are of same scalar data types (e.g. floats, integers, …) • Vector length (VL): Elements of the vector A B AAi i BBi i A B Ai i Bi i Scalar Vector Processing + Processing + C CCi i C Ci i VL 3 Optimization Notice Copyright © 2015, Intel Corporation. All rights reserved. *Other names and brands may be claimed as the property of others. Evolution of SIMD for Intel Processors Present & Future: Goal: Intel® MIC Architecture, 8x peak FLOPs (FMA) over 4 generations! Intel® AVX-512: • 512 bit Vectors • 2x FP/Load/FMA 4th Generation Intel® Core™ Processors Intel® AVX2 (256 bit): • 2x FMA peak Performance/Core • Gather Instructions 2nd Generation 3rd Generation Intel® Core™ Processors Intel® Core™ Processors Intel® AVX (256 bit): • Half-float support • 2x FP Throughput • Random Numbers • 2x Load Throughput Since 1999: Now & 2010 2012 2013 128 bit Vectors Future Time 4 Optimization Notice -
AMD Athlon™ Processor X86 Code Optimization Guide
AMD AthlonTM Processor x86 Code Optimization Guide © 2000 Advanced Micro Devices, Inc. All rights reserved. The contents of this document are provided in connection with Advanced Micro Devices, Inc. (“AMD”) products. AMD makes no representations or warranties with respect to the accuracy or completeness of the contents of this publication and reserves the right to make changes to specifications and product descriptions at any time without notice. No license, whether express, implied, arising by estoppel or otherwise, to any intellectual property rights is granted by this publication. Except as set forth in AMD’s Standard Terms and Conditions of Sale, AMD assumes no liability whatsoever, and disclaims any express or implied warranty, relating to its products including, but not limited to, the implied warranty of merchantability, fitness for a particular purpose, or infringement of any intellectual property right. AMD’s products are not designed, intended, authorized or warranted for use as components in systems intended for surgical implant into the body, or in other applications intended to support or sustain life, or in any other applica- tion in which the failure of AMD’s product could create a situation where per- sonal injury, death, or severe property or environmental damage may occur. AMD reserves the right to discontinue or make changes to its products at any time without notice. Trademarks AMD, the AMD logo, AMD Athlon, K6, 3DNow!, and combinations thereof, AMD-751, K86, and Super7 are trademarks, and AMD-K6 is a registered trademark of Advanced Micro Devices, Inc. Microsoft, Windows, and Windows NT are registered trademarks of Microsoft Corporation. -
Effective Virtual CPU Configuration with QEMU and Libvirt
Effective Virtual CPU Configuration with QEMU and libvirt Kashyap Chamarthy <[email protected]> Open Source Summit Edinburgh, 2018 1 / 38 Timeline of recent CPU flaws, 2018 (a) Jan 03 • Spectre v1: Bounds Check Bypass Jan 03 • Spectre v2: Branch Target Injection Jan 03 • Meltdown: Rogue Data Cache Load May 21 • Spectre-NG: Speculative Store Bypass Jun 21 • TLBleed: Side-channel attack over shared TLBs 2 / 38 Timeline of recent CPU flaws, 2018 (b) Jun 29 • NetSpectre: Side-channel attack over local network Jul 10 • Spectre-NG: Bounds Check Bypass Store Aug 14 • L1TF: "L1 Terminal Fault" ... • ? 3 / 38 Related talks in the ‘References’ section Out of scope: Internals of various side-channel attacks How to exploit Meltdown & Spectre variants Details of performance implications What this talk is not about 4 / 38 Related talks in the ‘References’ section What this talk is not about Out of scope: Internals of various side-channel attacks How to exploit Meltdown & Spectre variants Details of performance implications 4 / 38 What this talk is not about Out of scope: Internals of various side-channel attacks How to exploit Meltdown & Spectre variants Details of performance implications Related talks in the ‘References’ section 4 / 38 OpenStack, et al. libguestfs Virt Driver (guestfish) libvirtd QMP QMP QEMU QEMU VM1 VM2 Custom Disk1 Disk2 Appliance ioctl() KVM-based virtualization components Linux with KVM 5 / 38 OpenStack, et al. libguestfs Virt Driver (guestfish) libvirtd QMP QMP Custom Appliance KVM-based virtualization components QEMU QEMU VM1 VM2 Disk1 Disk2 ioctl() Linux with KVM 5 / 38 OpenStack, et al. libguestfs Virt Driver (guestfish) Custom Appliance KVM-based virtualization components libvirtd QMP QMP QEMU QEMU VM1 VM2 Disk1 Disk2 ioctl() Linux with KVM 5 / 38 libguestfs (guestfish) Custom Appliance KVM-based virtualization components OpenStack, et al. -
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. -
New Instruction Set Extensions
New Instruction Set Extensions Instruction Set Innovation in Intels Processor Code Named Haswell [email protected] Agenda • Introduction - Overview of ISA Extensions • Haswell New Instructions • New Instructions Overview • Intel® AVX2 (256-bit Integer Vectors) • Gather • FMA: Fused Multiply-Add • Bit Manipulation Instructions • TSX/HLE/RTM • Tools Support for New Instruction Set Extensions • Summary/References Copyright© 2012, Intel Corporation. All rights reserved. Partially Intel Confidential Information. 2 *Other brands and names are the property of their respective owners. Instruction Set Architecture (ISA) Extensions 199x MMX, CMOV, Multiple new instruction sets added to the initial 32bit instruction PAUSE, set of the Intel® 386 processor XCHG, … 1999 Intel® SSE 70 new instructions for 128-bit single-precision FP support 2001 Intel® SSE2 144 new instructions adding 128-bit integer and double-precision FP support 2004 Intel® SSE3 13 new 128-bit DSP-oriented math instructions and thread synchronization instructions 2006 Intel SSSE3 16 new 128-bit instructions including fixed-point multiply and horizontal instructions 2007 Intel® SSE4.1 47 new instructions improving media, imaging and 3D workloads 2008 Intel® SSE4.2 7 new instructions improving text processing and CRC 2010 Intel® AES-NI 7 new instructions to speedup AES 2011 Intel® AVX 256-bit FP support, non-destructive (3-operand) 2012 Ivy Bridge NI RNG, 16 Bit FP 2013 Haswell NI AVX2, TSX, FMA, Gather, Bit NI A long history of ISA Extensions ! Copyright© 2012, Intel Corporation. All rights reserved. Partially Intel Confidential Information. 3 *Other brands and names are the property of their respective owners. Instruction Set Architecture (ISA) Extensions • Why new instructions? • Higher absolute performance • More energy efficient performance • New application domains • Customer requests • Fill gaps left from earlier extensions • For a historical overview see http://en.wikipedia.org/wiki/X86_instruction_listings Copyright© 2012, Intel Corporation. -
A Superscalar Out-Of-Order X86 Soft Processor for FPGA
A Superscalar Out-of-Order x86 Soft Processor for FPGA Henry Wong University of Toronto, Intel [email protected] June 5, 2019 Stanford University EE380 1 Hi! ● CPU architect, Intel Hillsboro ● Ph.D., University of Toronto ● Today: x86 OoO processor for FPGA (Ph.D. work) – Motivation – High-level design and results – Microarchitecture details and some circuits 2 FPGA: Field-Programmable Gate Array ● Is a digital circuit (logic gates and wires) ● Is field-programmable (at power-on, not in the fab) ● Pre-fab everything you’ll ever need – 20x area, 20x delay cost – Circuit building blocks are somewhat bigger than logic gates 6-LUT6-LUT 6-LUT6-LUT 3 6-LUT 6-LUT FPGA: Field-Programmable Gate Array ● Is a digital circuit (logic gates and wires) ● Is field-programmable (at power-on, not in the fab) ● Pre-fab everything you’ll ever need – 20x area, 20x delay cost – Circuit building blocks are somewhat bigger than logic gates 6-LUT 6-LUT 6-LUT 6-LUT 4 6-LUT 6-LUT FPGA Soft Processors ● FPGA systems often have software components – Often running on a soft processor ● Need more performance? – Parallel code and hardware accelerators need effort – Less effort if soft processors got faster 5 FPGA Soft Processors ● FPGA systems often have software components – Often running on a soft processor ● Need more performance? – Parallel code and hardware accelerators need effort – Less effort if soft processors got faster 6 FPGA Soft Processors ● FPGA systems often have software components – Often running on a soft processor ● Need more performance? – Parallel -
SIMD Extensions
SIMD Extensions PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Sat, 12 May 2012 17:14:46 UTC Contents Articles SIMD 1 MMX (instruction set) 6 3DNow! 8 Streaming SIMD Extensions 12 SSE2 16 SSE3 18 SSSE3 20 SSE4 22 SSE5 26 Advanced Vector Extensions 28 CVT16 instruction set 31 XOP instruction set 31 References Article Sources and Contributors 33 Image Sources, Licenses and Contributors 34 Article Licenses License 35 SIMD 1 SIMD Single instruction Multiple instruction Single data SISD MISD Multiple data SIMD MIMD Single instruction, multiple data (SIMD), is a class of parallel computers in Flynn's taxonomy. It describes computers with multiple processing elements that perform the same operation on multiple data simultaneously. Thus, such machines exploit data level parallelism. History The first use of SIMD instructions was in vector supercomputers of the early 1970s such as the CDC Star-100 and the Texas Instruments ASC, which could operate on a vector of data with a single instruction. Vector processing was especially popularized by Cray in the 1970s and 1980s. Vector-processing architectures are now considered separate from SIMD machines, based on the fact that vector machines processed the vectors one word at a time through pipelined processors (though still based on a single instruction), whereas modern SIMD machines process all elements of the vector simultaneously.[1] The first era of modern SIMD machines was characterized by massively parallel processing-style supercomputers such as the Thinking Machines CM-1 and CM-2. These machines had many limited-functionality processors that would work in parallel. -
Operating Guide
Operating Guide EPIA-P830 Mainboard EPIA-P830 Operating Guide Table of Contents Table of Contents .......................................................................................................................................................................................... i VIA EPIA-P830 overview.............................................................................................................................................................................1 VIA EPIA-P830 layout ..................................................................................................................................................................................2 VIA EPIA-P830 specifications ...................................................................................................................................................................3 VIA EPIA-P830 processor SKUs ...............................................................................................................................................................4 VIA VX900 chipset overview.....................................................................................................................................................................5 VIA EPIA-P830 and P830-A board dimensions.................................................................................................................................6 VIA P830-B board dimensions.................................................................................................................................................................7 -
Apparecchiature Medicali: Il Ruolo Delle Nanotecnologie
EO Medical APPAreCCHIAture MeDICALI: IL ruoLo DeLLe NANoteCNoLoGIe IN queSto NuMero III Mercati/Attualità VIII Stanford, in fase di sviluppo una ‘pelle elettronica’ X Dialisi direttamente a casa XII Affrontare richieste ad alte prestazioni per la visualizzazione di immagini mediche XIV Criteri di scelta per alimentatori conformi a Iec60601-1 3a edizione XVII News Foto: Future Electronics Murata MEMS Solutions for Medical and Healthcare Enabling MEMS Sensing Improved Care Elements (Dies) SCG12S and SCG14S In medical and healthcare applications Vertical Accelerometer Elements (Dies) Murata’s medical MEMS sensors enable • Size 3mm x 2.12mm x 1.95 or 1.25mm • Various measuring ranges possible (1 - 12g) improved care and a better quality of life • Proven capacitive 3D-MEMS Technology for patients and elderly people. Medical sensors increase the intelligence of life supporting SCG10X and SCG10Z Horizontal Accelerometer Elements (Dies) transplants, and they can be used in new types of patient • Size SCG10X: 2.55mm x 2.95mm x 1.91mm monitoring applications that allow patients to lead more • Size SCG10Z: 1.50mm x 1.70mm x 1.83mm independent lives. Detecting signals triggered by symptoms • Various measuring ranges possible (1 - 12g) • Proven capacitive 3D-MEMS Technology helps optimize medication and prevent serious attacks of illness. Murata’s unique MEMS design, which combines single SCB10H crystal silicon and glass, ensures exceptional reliability, Pressure Sensor Elements (Dies) unprecedented accuracy and excellent stability over time. The • Size 1.4mm x 1.4mm x 0.85mm • High pressure shock survival (> 200 bar) power requirements of these medical sensors are extremely • Various pressure ranges possible (1.2 - 25 bar) low, which gives them a significant advantage in small • Proven capacitive 3D-MEMS technology battery-operated devices. -
Amd Epyc 7351
SPEC CPU2017 Floating Point Rate Result spec Copyright 2017-2019 Standard Performance Evaluation Corporation Sugon SPECrate2017_fp_base = 176 Sugon A620-G30 (AMD EPYC 7351) SPECrate2017_fp_peak = 177 CPU2017 License: 9046 Test Date: Dec-2017 Test Sponsor: Sugon Hardware Availability: Dec-2017 Tested by: Sugon Software Availability: Aug-2017 Copies 0 30.0 60.0 90.0 120 150 180 210 240 270 300 330 360 390 420 450 480 510 560 64 550 503.bwaves_r 32 552 165 507.cactuBSSN_r 64 163 130 508.namd_r 64 142 64 141 510.parest_r 32 146 168 511.povray_r 64 175 64 121 519.lbm_r 32 124 64 192 521.wrf_r 32 161 190 526.blender_r 64 188 164 527.cam4_r 64 162 248 538.imagick_r 64 250 205 544.nab_r 64 205 64 160 549.fotonik3d_r 32 163 64 96.7 554.roms_r 32 103 SPECrate2017_fp_base (176) SPECrate2017_fp_peak (177) Hardware Software CPU Name: AMD EPYC 7351 OS: Red Hat Enterprise Linux Server 7.4 Max MHz.: 2900 kernel 3.10.0-693.2.2 Nominal: 2400 Enabled: 32 cores, 2 chips, 2 threads/core Compiler: C/C++: Version 1.0.0 of AOCC Orderable: 1,2 chips Fortran: Version 4.8.2 of GCC Cache L1: 64 KB I + 32 KB D on chip per core Parallel: No L2: 512 KB I+D on chip per core Firmware: American Megatrends Inc. BIOS Version 0WYSZ018 released Aug-2017 L3: 64 MB I+D on chip per chip, 8 MB shared / 2 cores File System: ext4 Other: None System State: Run level 3 (Multi User) Memory: 512 GB (16 x 32 GB 2Rx4 PC4-2667V-R, running at Base Pointers: 64-bit 2400) Peak Pointers: 32/64-bit Storage: 1 x 3000 GB SATA, 7200 RPM Other: None Other: None Page 1 Standard Performance Evaluation -
CS 110 Discussion 15 Programming with SIMD Intrinsics
CS 110 Discussion 15 Programming with SIMD Intrinsics Yanjie Song School of Information Science and Technology May 7, 2020 Yanjie Song (S.I.S.T.) CS 110 Discussion 15 2020.05.07 1 / 21 Table of Contents 1 Introduction on Intrinsics 2 Compiler and SIMD Intrinsics 3 Intel(R) SDE 4 Application: Horizontal sum in vector Yanjie Song (S.I.S.T.) CS 110 Discussion 15 2020.05.07 2 / 21 Table of Contents 1 Introduction on Intrinsics 2 Compiler and SIMD Intrinsics 3 Intel(R) SDE 4 Application: Horizontal sum in vector Yanjie Song (S.I.S.T.) CS 110 Discussion 15 2020.05.07 3 / 21 Introduction on Intrinsics Definition In computer software, in compiler theory, an intrinsic function (or builtin function) is a function (subroutine) available for use in a given programming language whose implementation is handled specially by the compiler. Yanjie Song (S.I.S.T.) CS 110 Discussion 15 2020.05.07 4 / 21 Intrinsics in C/C++ Compilers for C and C++, of Microsoft, Intel, and the GNU Compiler Collection (GCC) implement intrinsics that map directly to the x86 single instruction, multiple data (SIMD) instructions (MMX, Streaming SIMD Extensions (SSE), SSE2, SSE3, SSSE3, SSE4). Yanjie Song (S.I.S.T.) CS 110 Discussion 15 2020.05.07 5 / 21 x86 SIMD instruction set extensions MMX (1996, 64 bits) 3DNow! (1998) Streaming SIMD Extensions (SSE, 1999, 128 bits) SSE2 (2001) SSE3 (2004) SSSE3 (2006) SSE4 (2006) Advanced Vector eXtensions (AVX, 2008, 256 bits) AVX2 (2013) F16C (2009) XOP (2009) FMA FMA4 (2011) FMA3 (2012) AVX-512 (2015, 512 bits) Yanjie Song (S.I.S.T.) CS 110 Discussion 15 2020.05.07 6 / 21 SIMD extensions in other ISAs There are SIMD instructions for other ISAs as well, e.g. -
Intel® Core™ Microarchitecture • Wrap Up
EW N IntelIntel®® CoreCore™™ MicroarchitectureMicroarchitecture MarchMarch 8,8, 20062006 Stephen L. Smith Bob Valentine Vice President Architect Digital Enterprise Group Intel Architecture Group Agenda • Multi-core Update and New Microarchitecture Level Set • New Intel® Core™ Microarchitecture • Wrap Up 2 Intel Multi-core Roadmap – Updates since Fall IDF 3 Ramping Multi-core Everywhere 4 All products and dates are preliminary and subject to change without notice. Refresher: What is Multi-Core? Two or more independent execution cores in the same processor Specific implementations will vary over time - driven by product implementation and manufacturing efficiencies • Best mix of product architecture and volume mfg capabilities – Architecture: Shared Caches vs. Independent Caches – Mfg capabilities: volume packaging technology • Designed to deliver performance, OEM and end user experience Single die (Monolithic) based processor Multi-Chip Processor Example: 90nm Pentium® D Example: Intel Core™ Duo Example: 65nm Pentium D Processor (Smithfield) Processor (Yonah) Processor (Presler) Core0 Core1 Core0 Core1 Core0 Core1 Front Side Bus Front Side Bus Front Side Bus *Not representative of actual die photos or relative size 5 Intel® Core™ Micro-architecture *Not representative of actual die photo or relative size 6 Intel Multi-core Roadmap 7 Intel Multi-core Roadmap 8 Intel® Core™ Microarchitecture Based Platforms Platform 2006 20072007 Caneland Platform (2007) MP Servers Tigerton (QC) (2007) Bensley Platform (Q2’06)/ Glidewell Platform (Q2’06) ) DP Servers/ Woodcrest (Q3’06) DP Workstation Clovertown (QC) (Q1’07) Kaylo Platform (Q3’06)/ Wyloway Platform (Q3 ’06) UP Servers/ Conroe (Q3’06) UP Workstation Kentsfield (QC) (Q1’07) Bridge Creek Platform (Mid’06) Desktop -Home Conroe (Q3’06) Kentsfield (QC) (Q1’07) Desktop -Office Averill Platform (Mid’06) Conroe (Q3’06) Mobile Client Napa Platform (Q1’06) Merom (2H’06) All products and dates are preliminary 9 Note: only Intel® Core™ microarchitecture QC refers to Quad-Core and subject to change without notice.