DL Boost
E653484
DL Boost is Intel’s deep learning acceleration technology that enhances AI inference performance on its processors through specialized instruction set extensions.
Statements (40)
| Predicate | Object |
|---|---|
| instanceOf |
Intel technology
ⓘ
deep learning acceleration technology ⓘ |
| appliesTo |
AI inference
ⓘ
deep neural networks ⓘ |
| architectureLevel | x86 instruction set architecture extension ⓘ |
| basedOn | specialized instruction set extensions ⓘ |
| benefit |
higher performance per watt for AI inference
ⓘ
reduced need for discrete accelerators for some AI workloads ⓘ |
| category |
AI hardware acceleration feature
ⓘ
CPU instruction set extension ⓘ |
| compatibleWith |
Intel OpenVINO toolkit
NERFINISHED
ⓘ
Intel oneDNN NERFINISHED ⓘ |
| designedFor |
data center workloads
ⓘ
edge AI workloads ⓘ |
| developer | Intel NERFINISHED ⓘ |
| enables |
faster matrix multiply-accumulate operations
ⓘ
higher operations per cycle for AI kernels ⓘ |
| focus | inference rather than training ⓘ |
| fullName | Intel Deep Learning Boost NERFINISHED ⓘ |
| improves |
latency of AI inference
ⓘ
performance of image recognition models ⓘ performance of natural language processing inference ⓘ throughput of AI workloads ⓘ |
| introducedBy | Intel Xeon Scalable processors NERFINISHED ⓘ |
| introducedIn | Intel Xeon Scalable 2nd Generation NERFINISHED ⓘ |
| marketingNameFor | Intel VNNI features NERFINISHED ⓘ |
| optimizationFor |
INT8 inference
ⓘ
low-precision arithmetic ⓘ |
| purpose |
accelerate deep learning workloads
ⓘ
enhance AI inference performance ⓘ |
| supports |
convolutional neural networks
ⓘ
fully connected layers ⓘ quantized neural network operations ⓘ recurrent neural networks ⓘ |
| targetHardware |
Intel Core processors
NERFINISHED
ⓘ
Intel Xeon processors NERFINISHED ⓘ |
| uses |
AVX-512 extensions
ⓘ
VNNI NERFINISHED ⓘ vector neural network instructions ⓘ |
| vendor | Intel NERFINISHED ⓘ |
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
Tiger Lake