Tensilica ConnX BBE32EP Baseband Engine

Learning Objectives

After completing this course, you will be able to:

• Understand the ConnX BBE32EP architecture, instruction set, and programming model
• Write and optimize C/C++ programs for VLIW/SIMD machines like the ConnX BBE32EP
• Use the advanced capabilities of the Xtensa C/C++ compiler to generate efficient compiled code
• Use the library routines provided with the ConnX BBE32EP to accelerate your software development cycle

Software Used in This Course

• Tensilica Xtensa Xplorer
• Tensilica Xtensa Software Tools

Software Release(s)

RG-2016.4

Modules in this Course

• About This Course
• BBE32EP Processor Overview
  • Application Performance
  • Architecture Overview
  • Instruction Set Highlights
  • Data Handling
• Programming Styles
  • The N-programming Model
  • Auto-vectorization of Scalar C Code
  • C Operators with Vector Types
  • Intrinsics Use
  • DSP Libraries
  • Lab 3-1 – Vector Programming
• Programming Guidelines
  • Lab 4-1 – Auto-vectorization
• BBE32EP Instruction Overview
  • Vector Element Operations
  • Load And Store Operations
  • Multiply Operations
  • Lab 5-1 – Intrinsic Optimization
• Advanced Topics
  • Matrix Multiply
  • Divide, Reciprocal, RSQRT
  • LFSR-Convolutional Encoding
  • 1D-Despread, Linear Block Decoder
  • FIR
  • FFT
  • Soft-demap, Inverse-LLR
  • Advanced precision
  • Dual/Single Peak Search
  • Vector Floating-Point
  • Lab 6-1 – Packed Matrix Multiplication
• Deliverables
  • Q/A

Audience

• Software developers and firmware engineers writing and optimizing code for the ConnX BBE32EP Baseband DSP

Prerequisites

You must have experience with or knowledge of the following:

• Programming in C for embedded processors or DSPs

You must have completed the following courses:

• Tensilica Processor Fundamentals

Related Courses

• Tensilica ConnX BBE16EP Baseband Engine
• Tensilica ConnX BBE64EP Baseband Engine

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