Speed is the superpower of computing

Say goodbye to CPU bottlenecks.

Hello, Performance 2.0. Hello, Parallel Processing Unit.

For decades, CPU progress has been incremental while workload demands have exploded across AI, edge, and cloud.

Flow’s Parallel Processing Unit (PPU) introduces a new architectural layer that brings true parallelism inside the CPU,delivering measurable, scalable performance gains.

Learn how it works ↓

Parallel Processing Unit

PPU

What is the PPU?

The PPU is a general-purpose parallel co-processor that integrates on-die with standard CPU architectures (Arm, x86, RISC-V, Power).

It works in tandem with the CPU to accelerate parallel execution directly within the chip, enabling a new level of throughput and efficiency for modern computing workloads.

The result: scalable parallel performance without external accelerators or added latency.

A new era for CPU performance

Significant performance gains, validated across real workloads.

Flow unites the CPU’s sequential strength with the PPU’s scalable parallelism, ushering in a new generation of general-purpose computing.

Key advantages

Significant performance boost

2× baseline improvements after recompilation; much higher when optimized.

Ideal for AI, simulation, and data-intensive workloads.

Integrated architecture

Licensable IP block that fits seamlessly within existing CPUs, supporting future generations of compute.

Scalable and future-proof

Parametric architecture configurable from edge to HPC, enabling linear scalability and energy-efficient throughput across industries.

How it fits

Flow’s PPU works with the CPU.
They share memory and operate as one coherent system:

  • CPU executes sequential and control logic.
  • PPU handles fine-grained parallel tasks with high throughput.

The PPU shows a promising path without being as exotic as a traditional accelerator.

- Prof. Dr. Jörg Keller (FernUniversität in Hagen)

Ready to explore the future of CPU performance?

Request access to Flow’s technical material and benchmark data.

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