Fungible announced Fungible Data Processing Unit at Hot Chips 2020. The company announced that Fungible DPU is a transformational technology that will power next-generation, high-performance, efficient, and cost-optimized scale-out data centers. Fungible’s new DPU is optimized for data interchange and data-centric computations, and also complements the CPU and GPU.
Availability:
The Fungible DPU is available immediately at two performance points:
- Fungible F1 DPU – an 800Gbps processor designed specifically for high-performance storage, analytics, and security platforms.
- Fungible S1 DPU – a 200Gbps processor optimized for host-side use cases including bare-metal virtualization, storage initiator, NFVi/VNF applications, and distributed node security.
Fungible DPU comprises two core innovations:
- A programmable data-path engine that executes data-centric computations at extremely high speeds, while providing flexibility comparable to general-purpose CPUs. The engine is programmed in C using industry-standard toolchains and is designed to execute many data-path computations concurrently.
- A new network engine that implements the endpoint of a high-performance TrueFabricTM that provides deterministic low latency, full cross-section bandwidth, congestion and error control, and high security at any scale (from 100s to 100,000s of nodes).
Pradeep Sindhu, CEO and Co-Founder of Fungible said,
“The Fungible DPU is purpose-built to address two of the biggest challenges in scale-out data centers, inefficient data interchange between nodes, and inefficient execution of data-centric computations. Data-centric computations are increasingly prevalent in data centers, with important examples being the computations performed in the network, storage, security and virtualization data-paths. Today, these computations are performed inefficiently by existing processor architectures. These inefficiencies cause overprovisioning and underutilization of resources, resulting in data centers that are significantly more expensive to build and operate. Eliminating these inefficiencies will also accelerate the proliferation of modern applications, such as AI and analytics.”