# GPUs, DSPs, ISPs, NPUs and what TOPS means

Accelerators do one kind of work far more efficiently than a CPU. TOPS is the headline number, and it is hard to compare between chips.

Page: https://dharanova.com/learn/accelerators-and-tops · Track: Think · Level: Core · Facts last checked 6 October 2026

Read first: [Microcontroller or microprocessor?](https://dharanova.com/learn/mcu-vs-mpu.md)

Diagram: Four cards: a GPU accelerates graphics and parallel arithmetic, a DSP signal-processing loops such as audio filters, an ISP turns raw camera-sensor data into images, and an NPU runs neural-network operations, usually at reduced precision. TOPS means tera (10^12) operations per second; it is usually quoted for INT8 and some figures assume sparse weights, so it is not directly comparable between vendors. A timeline of one model shows layers 1, 2, 4 and 5 on the NPU and layer 3, an unsupported operator, falling back to the CPU and taking far longer (not to scale).

## Key points

1. A GPU accelerates graphics and parallel arithmetic; a DSP accelerates signal-processing loops such as audio filters; an ISP turns raw camera-sensor data into usable images; an NPU accelerates neural-network operations, usually at reduced precision. [1][2][3]
2. TOPS means tera (10^12) operations per second. Vendors usually quote it for INT8 arithmetic, and some quote figures that assume sparse (partly zero) weights, so TOPS from different vendors are not directly comparable. [4][5]
3. A model only runs at NPU speed if every layer is supported by the NPU's toolchain; unsupported operators fall back to the CPU, which can dominate the total inference time. [3][6][7]

## Where to go next

- [Choosing a microcontroller or processor](https://dharanova.com/learn/choosing-a-processor.md): Answer six questions to find the kind of chip that fits your project, from small microcontrollers to Linux-class processors. You get a class, not a brand.
- [Machine learning on a microcontroller](https://dharanova.com/learn/tinyml.md): Small machine-learning models can run on microcontrollers, with no operating system and very little memory.

## Sources

1. [i.MX 8M Plus](https://www.nxp.com/products/i.MX8MPLUS), NXP
2. [Ethos-U55 microNPU](https://www.arm.com/products/silicon-ip-cpu/ethos/ethos-u55), Arm
3. [Vela: compiler for Arm Ethos-U NPUs (README and supported operators)](https://gitlab.arm.com/artificial-intelligence/ethos-u/ethos-u-vela), Arm
4. [Jetson Orin Nano Super Developer Kit](https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/nano-super-developer-kit/), NVIDIA
5. [NVIDIA Jetson Orin Nano Developer Kit Gets a 'Super' Boost](https://developer.nvidia.com/blog/nvidia-jetson-orin-nano-developer-kit-gets-a-super-boost/), NVIDIA
6. [GPU delegates for LiteRT](https://developers.google.com/edge/litert/performance/gpu), Google
7. [LiteRT Delegates](https://developers.google.com/edge/litert/performance/delegates), Google