Embedded - DSP (Digital Signal Processors)

Image Part Number Description / PDF Quantity Rfq
TMS320DM365ZCE27

TMS320DM365ZCE27

Texas Instruments

IC DIGITAL MEDIA SOC 338NFBGA

160

TMS320C6202GJL200

TMS320C6202GJL200

Texas Instruments

DSP, 32-BIT SIZE, 32-EXT BIT, 20

145

TMS320VC5510AGGW1

TMS320VC5510AGGW1

Texas Instruments

IC FIXED POINT DSP 240-BGA

102

TNETV2685FIBZUT5

TNETV2685FIBZUT5

Texas Instruments

DIGITAL MEDIA PROCESSOR

0

TMS320VC5506ZHHR

TMS320VC5506ZHHR

Texas Instruments

DSP, 32-BIT SIZE, 16-EXT BIT, 20

2375

TMS320C6457CGMHA

TMS320C6457CGMHA

Texas Instruments

DIGITAL SIGNAL PROCESSOR, 32-BIT

22986

TMS320C28342ZFET

TMS320C28342ZFET

Texas Instruments

TMS320- DELFINO, 32-BIT MCU WITH

715

66AK2H12BAAWA2

66AK2H12BAAWA2

Texas Instruments

RISC MICROPROCESSOR

19

TMS320VC5502PGF300

TMS320VC5502PGF300

Texas Instruments

IC FXD-PNT DSP 600 MIPS 176-LQFP

456

TMS320C31PQA50

TMS320C31PQA50

Texas Instruments

DSP, 32-BIT SIZE, 32-EXT BIT, 50

0

TMS320DM8127BCYE0

TMS320DM8127BCYE0

Texas Instruments

32-BIT, 600MHZ, CMOS, PBGA684

60

TMS320C5514AZCH12

TMS320C5514AZCH12

Texas Instruments

IC DSP FIXED-POINT 196NFBGA

0

TMS320C28343ZFET

TMS320C28343ZFET

Texas Instruments

32-BIT, MROM, TMS320 CPU

332

TMS320C6205DZHK200

TMS320C6205DZHK200

Texas Instruments

DSP, 32-BIT SIZE, 32-EXT BIT, 20

35

TMS320C28343ZFEQ

TMS320C28343ZFEQ

Texas Instruments

IC DSP FLOATING POINT 256BGA

0

TMS320C6472ECTZ7

TMS320C6472ECTZ7

Texas Instruments

IC DSP FIXED-POINT 737FCBGA

0

TMS320DM368ZCEF

TMS320DM368ZCEF

Texas Instruments

IC DGTL MEDIA SOC 338NFBGA

160

TMS320C5534AZHH05

TMS320C5534AZHH05

Texas Instruments

DSP, 16-BIT SIZE, 0-EXT BIT, 12M

960

TMS320C6454BZTZ7

TMS320C6454BZTZ7

Texas Instruments

IC FIXED-POINT DSP 697-FCBGA

38

TMS320VC5503ZAY

TMS320VC5503ZAY

Texas Instruments

IC DSP FIXED POINT 179-BGA

0

Embedded - DSP (Digital Signal Processors)

1. Overview

Digital Signal Processors (DSPs) are specialized microprocessors optimized for high-speed numerical calculations required in signal processing. Embedded DSPs integrate these capabilities into compact systems, enabling real-time processing of analog and digital signals. They play a critical role in modern technologies by enabling tasks like audio/video compression, noise reduction, radar imaging, and AI inference. Their ability to perform complex mathematical operations (e.g., FFTs, convolutions) at low power makes them indispensable in applications ranging from consumer electronics to industrial automation.

2. Main Types and Functional Classification

Type Functional Features Application Examples
General-Purpose DSP Balanced performance for common signal processing tasks Audio codecs, motor control systems
High-Performance DSP Multi-core architectures with teraflop-level processing Radar systems, 5G base stations
Low-Power DSP Optimized for energy efficiency (sub-1W operation) IoT sensors, wearable devices
Fixed-Point DSP Integer arithmetic for cost-sensitive applications Entry-level automotive systems
Floating-Point DSP High precision for complex algorithms Medical imaging, scientific instruments

3. Structure and Composition

A typical embedded DSP system includes:

  • Core Architecture: Modified Harvard architecture with separate instruction/data buses
  • Memory Hierarchy: L1/L2 cache, on-chip SRAM, external DDR interfaces
  • Accelerators: SIMD units, VLIW engines, FFT hardware
  • Interfaces: SPI, I2C, PCIe, JTAG for debugging
  • Power Management: DVFS (Dynamic Voltage/Frequency Scaling)

Advanced packages like BGA and QFN enable high pin density while maintaining thermal efficiency.

4. Key Technical Specifications

Parameter Description and Importance
Processing Speed (MIPS/GFLOPS) Determines real-time processing capability
Word Length (16/32/64-bit) Affects dynamic range and precision
Power Consumption (mW/MHz) Crucial for battery-powered devices
Memory Bandwidth (GB/s) Limits throughput in data-intensive tasks
Thermal Design Power (TDP) Dictates cooling requirements

5. Application Fields

  • Telecommunications: 5G NR modems, optical network transceivers
  • Consumer Electronics: Smart speakers (Amazon Echo), AR headsets
  • Industrial: Predictive maintenance sensors, robotic vision systems
  • Medical: Ultrasound machines, ECG analyzers
  • Automotive: LiDAR processing for ADAS, engine control units

6. Leading Manufacturers and Products

Manufacturer Representative Product Key Specifications
Texas Instruments TMS320C6678 8-core DSP, 16 GMACS, 10-band spectral analysis
Analog Devices ADSP-BF707 256-bit LPDDR memory bus, hardware accelerators
NXP Semiconductors S32K144H Arm Cortex-M4F core, ASIL-D functional safety
Intel Turbo DSP C6XX Dynamic core scaling, PCIe Gen4 interface

7. Selection Guidelines

Key considerations include:

  • Algorithm Complexity: Floating-point for radar beamforming vs. fixed-point for voice codecs
  • Real-Time Constraints: Deterministic latency requirements
  • Power Budget: 150mW for hearables vs. 25W for base stations
  • Development Ecosystem: Availability of optimized libraries (e.g., TI's DSP/BIOS)
  • Scalability: Pin-to-pin compatible families for future upgrades

8. Industry Trends

Future developments include:

  • Integration of AI accelerators (e.g., Google Edge TPU)
  • 7nm process nodes enabling 10TOPS/Watt efficiency
  • Adoption of RISC-V architecture for customizable DSPs
  • Increased use in edge computing for Industry 4.0 systems
  • Advanced packaging (2.5D/3D) for heterogeneous integration

Market projections indicate a CAGR of 6.2% through 2027, driven by automotive radar and AIoT applications.

9. Practical Application Case

Case: Smart Speaker Audio Processing
A leading smart speaker uses ADI's SHARC DSP for beamforming and noise suppression. The DSP processes 8-channel microphone inputs in real-time, achieving 40dB noise reduction while maintaining 15ms latency. Its low-power mode consumes 85mW during voice activity detection, extending Wi-Fi-enabled device battery life by 30% compared to GPU-based solutions.

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