A Computing Revolution? Flow’s PPU Powers CPUs up to 100 Times | Hardware and Software of Computer | Gpu vs cpu Performance Comparison | Cpu Hardware Software | Turtles AI

Flow’s new Parallel Processing Unit promises to revolutionize computing by boosting CPU performance by a hundredfold. Flow’s PPU offers extreme scalability and customization, making CPUs more efficient and enhancing the entire computing ecosystem.

Flow has introduced an innovative solution for one of the most fundamental dilemmas in computing: parallel processing. Flow’s Parallel Processing Unit (PPU) can boost CPU performance by a hundredfold, ushering in a new era for SuperCPUs. This technology is designed to be fully backward-compatible, enhancing existing software and applications after a simple recompilation. The performance boost is particularly evident in more parallel functions.

Flow’s technology is not limited to directly boosting CPUs; ancillary components such as matrix units, vector units, NPUs, and GPUs also benefit from the enhanced CPU capabilities thanks to the PPU. This effect extends across the entire computing ecosystem, delivering benefits on multiple fronts.

One of the main advantages of the PPU is the improvement of legacy software. The PPU not only boosts the performance of existing code without modifying the original application but also offers significant enhancements when paired with recompiled operating systems or programming libraries. This results in substantially increased speeds for a wide range of applications, especially those exhibiting parallelism but constrained by traditional thread-based processes.

Flow’s PPU’s parametric design allows it to adapt to multiple uses. Everything can be tailored to meet specific requirements: the number of PPU cores (4, 16, 64, 256, etc.), the type and number of functional units (ALUs, FPUs, MUs, GUs, NUs), and the size of on-chip memory resources (caches, buffers, scratchpads). This performance scalability is directly linked to the number of PPU cores. A PPU with 4 cores is ideal for small devices like smartwatches, while a PPU with 256 cores is recommended for servers, enabling them to handle the most demanding computational tasks with ease.

Flow’s Parallel Processing Unit is an IP block that integrates tightly with the CPU on the same silicon, being highly configurable for specific requirements. Customization options include the number of cores, the type and number of functional units, and the size of on-chip memory resources, in addition to instruction set modifications to complement the CPU’s instruction set extension. CPU modifications are minimal, involving the integration of the PPU interface into the instruction set and updating the number of CPU cores to leverage new performance levels.

Flow’s PPU architecture solves various issues related to CPU latency, synchronization, and virtual-level parallelism. Memory access latency is hidden by executing other threads while accessing memory, with no coherence issues thanks to the lack of caches at the network front. Synchronization occurs only once per step, significantly reducing costs. Functional units are organized in a chain, eliminating pipeline hazard issues.

Performance boosts for existing software are guaranteed by compatibility with all legacy software, with the PPU’s compiler automatically recognizing parallel code parts and executing them in PPU cores. Furthermore, Flow is developing an AI tool to help application and software developers identify parallel code parts and propose methods to optimize them for maximum performance.

CPUs remain a critical component of numerous AI workloads, analytics, information retrieval, and machine learning training and serving. Those aiming to maximize performance, reduce infrastructure costs, and meet sustainability goals have encountered a slowing rate of CPU improvement. Without proper CPU development, general-purpose computing could limit capacity and dominate AI infrastructure costs.

Autonomous vehicle systems, requiring immense parallel processing power, would greatly benefit from Flow’s PPU technology. This offers the robust performance needed for the high-speed, real-time data processing these systems demand. In edge computing contexts, where low latency is critical, Flow’s PPU ensures swift and reliable decision-making processes, enhancing safety and efficiency.

Emerging fields such as simulation and optimization, widely used in business computing for logistics planning and investment forecasting, will greatly benefit from Flow’s technology flexibility over GPU thread blocks. Classic numeric and non-numeric parallelizable workloads will also benefit from Flow’s PPU, improving performance even in code with small parallelizable parts.

Highlights

• Flow’s PPU could enhance CPU performance up to 100 times.
• Backward compatibility with legacy software.
• Parametric design for various uses.
• Reduced latency and improved synchronization.