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| {{intel|Cascade Lake|l=arch}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} || {{tchk|no}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} | | {{intel|Cascade Lake|l=arch}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} || {{tchk|no}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} | ||
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− | | {{intel|Cannon Lake|l=arch}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || | + | | {{intel|Cannon Lake|l=arch}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || || {{tchk|no}} || {{tchk|no}} |
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| {{intel|Ice Lake (server)|l=arch}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} | | {{intel|Ice Lake (server)|l=arch}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|yes}} || {{tchk|no}} || {{tchk|no}} |
Revision as of 03:29, 21 May 2018
x86
Instruction Set Architecture
Instruction Set Architecture
General
Variants
Topics
- Instructions
- Addressing Modes
- Registers
- Model-Specific Register
- Assembly
- Interrupts
- Micro-Ops
- Timer
- Calling Convention
- Microarchitectures
- CPUID
CPUIDs
Modes
Extensions(all)
AVX-512 is collective name for a number of 512-bit SIMD x86 instruction set extensions. The extensions were formally introduced by Intel in July 2013 with first general-purpose microprocessors implementing the extensions introduced in July 2017.
Contents
Overview
AVX-512 is a set of 512-bit SIMD extensions that allow programs to pack sixteen single-precision eight double-precision floating-point numbers, or eight 64-bit or sixteen 32-bit integers within 512-bit vectors. The extension provides double the computation capabilities of that of AVX/AV2.
- AVX512F - AVX-512 Foundation is base of the 512-bit SIMD instruction extensions which is a comprehensive list of features for most HPC and enterprise applications. AVX-512 Foundation is the natural extensions to AVX/AVX2 which is extended using the EVEX prefix which builds on the existing VEX prefix. Any processor that implements any portion of the AVX-512 extensions MUST implement AVX512F.
- AVX512CD - AVX-512 Conflict Detection Instructions offer additional vectorization of loops with possible address conflict.
- AVX512DQ - AVX-512 Doubleword and Quadword Instructions add new 32-bit and 64-bit AVX-512 instructions (conversion, transcendental support, etc..).
- AVX512PF - AVX-512 Prefetch Instructions add new prefetch instructions for gather/scatter and PREFETCHWT1 .
- AVX512ER - AVX-512 Exponential and Reciprocal Instructions (ERI) offer 28-bit precision RCP, RSQRT and EXP transcendentals for various scientific applications.
- AVX512VL - AVX-512 Vector Length Instructions add vector length orthogonality, allowing most AVX-512 operations to also operate on XMM (128-bit SSE) registers and YMM (256-bit AVX) registers
- AVX512BW - AVX-512 Byte and Word Instructions add support for for 8-bit and 16-bit integer operations.
- AVX512IFMA - AVX-512 Integer Fused Multiply-Add Instructions add support for fused multiply add of integers using 52-bit precision.
- AVX512VBMI - AVX-512 Vector Bit Manipulation, Version 1 add additional vector byte permutation instructions.
- AVX512VBMI2 - AVX-512 Vector Bit Manipulation, Version 2 add additional vector byte permutation instructions.
- AVX512VAES - AVX-512 Vector AES Instructions add vector AES operations
- AVX512BITALG - AVX-512 Bit Algorithms add bit algorithms operations
- AVX5124FMAPS - AVX-512 Fused Multiply Accumulation Packed Single precision Instructions add vector instructions for deep learning on floating-point single precision
- AVX512VPCLMULQDQ - AVX-512 Vector Carry-less Multiply add vector carry-less multiply operations
- AVX512GFNI - AVX-512 Galois Field New Instructions add Galois Field transformations instructions
- AVX512VNNI - AVX-512 Vector Neural Network Instructions add vector instructions for deep learning
- AVX5124VNNIW - AVX-512 Vector Neural Network Instructions Word Variable Precision Instructions add vector instructions for deep learning on enhanced word variable precision
- AVX512VPOPCNTDQ - AVX-512 Vector Population Count Doubleword and Quadword Instructions add double and quad word population count instructions.
Note that,
- Formerly, the term AVX3.1 referred to
F + CD + ER + PF
. - Formerly, the term AVX3.2 referred to
F + CD + BW + DQ + VL
.
Detection
CPUID | Instruction Set | |
---|---|---|
Input | Output | |
EAX=07H, ECX=0 | EBX[bit 16] | AVX512F |
ECX[bit 12] | AVX512BITALG | |
EBX[bit 17] | AVX512DQ | |
EBX[bit 21] | AVX512IFMA | |
EBX[bit 26] | AVX512PF | |
EBX[bit 27] | AVX512ER | |
EBX[bit 28] | AVX512CD | |
EBX[bit 30] | AVX512BW | |
EBX[bit 31] | AVX512VL | |
ECX[bit 01] | AVX512VBMI | |
ECX[bit 11] | AVX512VNNI | |
ECX[bit 14] | AVX512VPOPCNTDQ | |
EDX[bit 02] | AVX5124VNNIW | |
EDX[bit 03] | AVX5124FMAPS |
Implementation
Designer | Microarchitecture | Support Level | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
F | CD | ER | PF | BW | DQ | VL | IFMA | VBMI | 4FMAPS | VNNI | 4VNNIW | VPOPCNTDQ | ||
Intel | Knights Landing | ✔ | ✔ | ✔ | ✔ | ✘ | ✘ | ✘ | ✘ | ✘ | ✘ | ✘ | ✘ | ✘ |
Knights Mill | ✔ | ✔ | ✔ | ✔ | ✘ | ✘ | ✘ | ✘ | ✘ | ✔ | ✔ | ✔ | ✔ | |
Skylake (server) | ✔ | ✔ | ✘ | ✘ | ✔ | ✔ | ✔ | ✘ | ✘ | ✘ | ✘ | ✘ | ✘ | |
Cascade Lake | ✔ | ✔ | ✘ | ✘ | ✔ | ✔ | ✔ | ✘ | ✘ | ✘ | ✔ | ✘ | ✘ | |
Cannon Lake | ✔ | ✔ | ✘ | ✘ | ✔ | ✔ | ✔ | ✔ | ✔ | ✘ | ✘ | ✘ | ||
Ice Lake (server) | ✔ | ✔ | ✘ | ✘ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✘ | ✘ |
Documents
- Intel® Advanced Vector Extensions 2015/2016; GNU Tools Cauldron 2014; Presented by Kirill Yukhin of Intel, July 2014