Unlocking new possibilities
for CPU-powered systems
Flow PPU + CPU
Next-gen CPUs unlock new system-level capabilities
Modern systems' competencies are increasingly limited by CPU performance. As workloads become more parallel and data-intensive, general-purpose CPUs struggle to scale efficiently. Adding more cores increases software complexity and synchronization overhead, limiting practical performance gains. Cache coherence and shared-memory contention further constrain scalability, while external accelerators introduce latency, memory copies, and programming complexity.
As a result, systems hit performance ceilings, costs rise, and optimization opportunities are missed.
Flow Computing®'s Parallel Processing Unit® (Flow PPU) brings scalable parallelism to environments where traditional CPUs fall short: from hyperscale infrastructure to embedded systems. Flow PPU delivers low-latency, high-throughput parallel performance with linear scalability. Flow-powered CPU systems enable higher parallel throughput by integrating Flow PPU alongside the CPU, allowing more demanding workloads to run efficiently on the CPU.
This extends to general-purpose computing capabilities across cloud and data-center systems, deterministic industrial and embedded platforms, and power-constrained consumer and edge devices.
Solutions across CPU markets
Scalable CPU performance for cloud, data center, and HPC workloads
Scalable throughput for cloud infrastructure, data centers, supercomputers, and high-performance computing environments running general-purpose and AI-adjacent workloads.
Server CPUs increasingly struggle with synchronization overhead, memory access patterns, and poor scalability as core counts grow. Flow PPU improves parallel throughput for CPU workloads, reducing execution time and improving efficiency while keeping software development manageable.
This makes Flow PPU well suited to preprocessing, inference support, scientific computing, data processing, and other parallel workloads that are difficult to scale efficiently on traditional CPUs.
Flow PPU-powered server CPUs enable better utilization in cloud and data-center environments.
Deterministic parallel performance for industrial and embedded systems
Deterministic, low-latency performance for decentralized AI, robotics, signal and sensor data processing, autonomous systems, defense, and real-time industrial compute.
Industrial and embedded systems operate under strict timing, reliability, and efficiency constraints. Parallel workloads in these environments are often limited by synchronization overhead and unpredictable execution behavior on traditional multicore CPUs.
Flow PPU supports scalable parallel execution, suitable for real-time and control-heavy systems. By accelerating parallel workloads on the CPU, Flow PPU helps improve performance and efficiency.
Efficient parallel performance for consumer and edge devices
High-performance, energy-efficient acceleration for mobile AI, edge inference, and next-generation consumer devices such as smartphones, laptops, and wearables.
Consumer and edge devices operate under tight power and thermal limits, which restrict how much parallel workload can be handled locally. Flow PPU extends what consumer CPUs can process efficiently, enabling more capable on-device workloads.
This allows more demanding general-purpose and AI-related tasks to run more efficiently
Why Flow PPU works
Traditional multicore CPUs struggle to scale efficiently due to memory access inefficiencies, high synchronization overhead, and cache coherence costs.
Flow PPU addresses these architectural bottlenecks by hiding memory latency, reducing synchronization overhead, and enabling high-throughput shared-memory execution across processing elements.
This enables efficient parallel execution and near-linear scalability for general-purpose workloads, without extensive manual tuning or complex software workarounds.
Technology
Flow PPU is a licensable, on-die parallel acceleration architecture that works alongside the CPU as a general-purpose parallel co-processor.
The CPU handles sequential parts of execution, while Flow PPU executes the parallel parts of the workload. This division allows each part of the system to do what it does best: low-latency execution on the CPU and high-throughput parallel execution on the PPU.
Flow PPU is instruction-set independent and can be integrated with Arm, x86, RISC-V, and Power CPU architectures, while maintaining backward compatibility with existing software and a step-by-step migration path.
Built on decades of research
Flow PPU is based on more than 30 years of research in parallel computing, memory systems, and processor design.
The architecture builds on established models of parallel computation and introduces key innovations such as Emulated Shared Memory and Thick Control Flow, enabling scalable general-purpose parallel execution while simplifying parallel software development.
This research foundation underpins Flow PPU’s ability to deliver scalable performance and predictable execution across a wide range of systems.
Performance results
Flow PPU has been benchmarked against leading consumer and server CPUs across compute-intensive, memory-intensive, and synchronization-heavy workloads.
These results demonstrate significant improvements in throughput, scalability, and efficiency for general-purpose parallel workloads, particularly in cases where traditional multicore CPUs fail to scale efficiently.
Let's start a conversation
Flow PPU is designed to integrate into existing and future CPU designs across server, industrial, and consumer markets.
If you’d like to discuss system integration, performance characteristics, or suitability for your workloads, get in touch.