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SiFive Intelligence
X200 Series

SiFive Intelligence
X280

The SiFive Intelligence™ X280 is a multi-core capable RISC-V processor with vector extensions and SiFive Intelligence Extensions and is optimized for AI/ML compute at the edge.

In addition to ML inferencing, it is ideal for applications requiring high-throughput, single-thread performance while under power constraints (e.g., AR, VR, sensor hubs, IVI systems, IP cameras, digital cameras, gaming devices).

Contact SalesDownload X280 and X280-MC Data Sheet

SiFive Intelligence
X280 Key Features

  • SiFive Intelligence Extensions for ML workloads
    - Custom instructions to greatly accelerate Neural Network computation
    - Optimized TensorFlow Lite implementation
    - Hundreds of Neural Network models ported
    - 4.6 TOPS performance
  • 512-bit vector register length processor
    - Variable length operations, up to 512-bits of data per cycle
    - Ideal balance of control logic and data parallel compute
    - Decoupled Vector pipeline
    - INT8 to INT64 integer data type
    - BF16/FP16/FP32/FP64 floating point data type
  • Performance benchmarks
    - 5.75 CoreMarks/MHz
    - 3.25 DMIPS/MHz
    - 4.6 SpecINT2k6/GHz
  • Built on silicon-proven U7-Series core
    - 64-bit RISC-V ISA
    - 8-stage dual-issue in-order pipeline
    - Coherent multi-core, Linux capable
  • High performance vector memory subsystem
    - Memory parallelism provides cache miss tolerance
    - Virtual memory support with precise exceptions
    - Up to 48-bit addressing
  • Multi-core, multi-cluster processor configuration, up to 8 cores

Application Spotlight

Case Study: Google Datacenter

SiFive Intelligence X280 as AI Compute Host

View the Case Study

SiFive Intelligence
X288

The SiFive Intelligence™ X288 is a multi-core capable RISC-V processor ideal for Aerospace applications with vector extensions and SiFive Intelligence Extensions and is optimized for AI/ML compute at the edge.

Ask about applications in aerospace, infrastructure and other applications.

Contact Sales

SiFive Intelligence
X288 Key Features

  • SiFive Intelligence Extensions for ML workloads
    - Custom instructions to greatly accelerate Neural Network computation
    - Optimized TensorFlow Lite implementation
    - Hundreds of Neural Network models ported
    - 4.6 TOPS performance
  • 512-bit VLEN
    - Single Vector ALU
    - Split-Lock with DCLS
    - CXL Host interface
  • Performance benchmarks
    - 5.75 CoreMarks/MHz
    - 3.25 DMIPS/MHz
    - 4.6 SpecINT2k6/GHz
  • Built on silicon-proven U7-Series core
    - 64-bit RISC-V ISA
    - 8-stage dual-issue in-order pipeline
    - Coherent multi-core, Linux capable
  • High performance vector memory subsystem
    - Memory parallelism provides cache miss tolerance
    - Virtual memory support with precise exceptions
    - Up to 48-bit addressing
  • Multi-core, multi-cluster processor configuration, up to 8 cores

SiFive Intelligence Family

X300 Series
Intelligence
  • 1024-bit Vector Length
  • Single/Dual Vector ALU
  • VCIX (2048-bit)
View X300 Series
XM Series
Intelligence
  • Scalable Matrix Engine
  • 4 X300 cores per cluster
  • 1 Cluster = 16 TOPS (INT8)
View XM Series

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Core IP Families

Automotive
SiFive Automotive™ solutions provide a range of high-end application and real-time processors, delivering industry-leading performance, minimal area, and low power consumption. ISO 21434, SO26262 ASIL B, ASIL D and split-lock certifications.
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Intelligence
Intelligence embraces a software-first approach to processor design, addressing the future needs of deploying ML and AI at the edge. It provides high-performance, scalable vector and matrix compute capabilities, adaptable to evolving workloads.
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Performance
The SiFive Performance™ family of RISC-V processors is designed for maximum throughput and performance efficiency for a range of application from datacenter workloads, ranging from Web servers and multimedia processing, Networking/Storage to consumer applications like TV, wearables and other smart devices requiring AI functionality.
View Performance