Xilinx Expands Alveo Portfolio with Industry's First Adaptable Compute, Network and Storage Accelerator Card Built for Any Server, Any Cloud
The Alveo U50 provides customers with a programmable low profile and low-power accelerator platform built for scale-out architectures and domain-specific acceleration of any server deployment, on-premise, in the cloud and at the edge. To meet the challenges of emerging dynamic workloads such as cloud microservices, Alveo U50 delivers between 10-20x improvements in throughput, latency and power efficiency. For accelerated networking and storage workloads, the U50 card helps developers identify and eliminate latency and data movement bottlenecks by moving compute closer to the data.
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From machine learning inference, video transcoding and data analytics to computational storage, electronic trading and financial risk modeling, the Alveo U50 brings programmability, flexibility, and high throughput and low latency performance advantages to any server deployment. Unlike fixed architecture alternatives, the software and hardware programmability of the Alveo U50 allows customers to meet ever-changing demands and optimize application performance as workloads and algorithms continue to evolve.
Alveo U50 accelerated solutions deliver significant customer value across a range of applications, including:
- Deep learning inference acceleration (speech translation): delivers up to 25x lower latency, 10x higher throughput and significantly improved power efficiency per node compared to GPU-only for speech translation performance1;
- Data analytics acceleration (database query): running the TPC-H Query benchmark, Alveo U50 delivers 4x higher throughput per hour and reduced operational costs by 3x compared to in-memory CPU2;
- Computational storage acceleration (compression): delivers 20x more compression/decompression throughput, faster Hadoop and big data analytics, and over 30 percent lower cost per node compared to CPU-only nodes3;
- Network acceleration (electronic trading): delivers 20x lower latency and sub-500ns trading time compared to CPU-only latency of 10us4;
- Financial modeling (grid computing): running the Monte Carlo simulation, Alveo U50 delivers 7x greater power efficiency compared to GPU-only performance5 for a faster time to insight, deterministic latency and reduced operational costs.
"Ever-growing demands on the data center are pushing existing infrastructure to its limit, driving the need for adaptable solutions that can optimize performance across a broad range of workloads and extend the lifecycle of existing infrastructure, ultimately reducing TCO," said
"The forthcoming 2nd Gen
"With the smaller design and advanced features of the Alveo U50,
"We are excited to be collaborating with
The Alveo U50 is sampling now with OEM system qualifications in process. General availability is slated for fall 2019.
Flash Memory Summit:
- Performance of Alveo U50, with both Alveo U50 and Nvidia Tesla T4 running (B=2, L=8), Tesla T4 (B=8, L=8) (estimated data)
- Alveo U50=24ms, 150k query/hr / CPU Query time = 210ms, 34k query/hr. based on Intel Xeon Platinum 8260 Processor (35.75M Cache, 2.40 GHz) 24 core
- Intel Skylake-SP 6152 @2.10GHz CPU (Ubuntu 16.04) CPU Query time = 210ms, 34k query/hr. Alveo U50=24ms, 150k query/hr Xilinx Alveo U50 SDAccel 2018.3 (estimate) GB/s compression per CPU core = .0229. Alveo U50 = 10GB/s (estimate)
- Alveo U50 latency is <0.5us, CPU latency is 10us. Measured from start of packet in on Tick (Market Data) to start of packet out on the order to Start Packet Out on the Order (estimate)
- Intel Xeon E5-2697 v4 GCC 5.4.0 Nvidia Tesla V100 16GB PCIe CUDA 10.1 / GCC 5.4.0 Intel Skylake-SP 6152 @2.10GHz CPU (Ubuntu 16.04) CPU Query time = 210ms, 34k query/hr. Alveo U50=24ms, 150k query/hr Xilinx Alveo U50 SDAccel 2018.3 (estimated data).
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