Tensilica MathX DSPs Offer Exceptional PPA for Floating-Point Processing

Whether you are looking for a DSP solution to run your software generated by a DSP modeling tool, to offload your existing floating-point processing, or to meet your application requirement of computation in floating-point format, Cadence Tensilica MathX DSPs offer a DSP IP solution that is among the most scalable and most power, performance, and area cost efficient. Tensilica MathX DSPs scale from ultra-low energy and to super-high performance and address a broad range of application.

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MathX DSPs diagram

Key Benefits

Performance, Power, and Area

DSPs with exceptional PPA specifically designed for floating-point-centric processing

Scalability

A family of DSPs scaling from small and low power to very high performance

Software Portability

Common floating-point ISA promotes easy software migration between DSPs

Extensible and Configurable

Customizable instruction set promotes differentiation and performance enhancement

Features

  • VLIW parallelism issuing multiple concurrent operations per cycle
  • IEEE 754 vector floating-point (HP, SP, DP)
  • Performance optimized fused multiply-add (FMA)
  • 8b/16b/32b/64b integer ALU operations
  • Optimized for FFT operations
  • Enhanced complex data processing
  • Superior auto vectorization support
  • TIE for easy extension and further performance enhancement
  • Optimized Eigen, NatureDSP, Math, and SLAM libraries for easy software development

Target Markets

  • AI/ML
  • Automotive
  • Sensor fusion
  • Radar, lidar, and vision sensing
  • Motor control
  • AR/VR
  • Drones
  • Robotics
  • HPC/data center

 

Partners

Cadence, through its Tensilica processor IP, brings together best-in-class products and services from industry leaders to help you accelerate the development of your SoC designs while meeting your demanding power and performance requirements. Browse the list of Tensilica processor IP service partners below.

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TIE

Customize your DSPs/processors for optimized performance, energy efficiency, and differentiation

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