Hardware systems, such as the FPGA-based platforms, are very efficient in doing such studies given their intrinsic parallelism, reconfigurability and real-time processing capability. We have successfully used the Xilinx Virtex-6 FPGA devices to prototype the generalized Laguerre鈥揤olterra model (...
Microsoft is using Intel FPGAs to run complex deep learning models at what Microsoft describes in a blog post as delivering ‘unprecedented levels of performance and flexibility.’ This FPGA-based accelerated deep learning platform provides “real-time AI” capabilities, which will allow cloud infrast...
These bandwidth capabilities make Intel Stratix 10 MX FPGAs the essential multi-function accelerators for high-performance computing (HPC), data centers, network functions virtualization (NFV), and broadcast applications that require hardware accelerators to speed-up mass data movements and stream data ...
FPGA 与 Open Compute Server 之间的连接与固定,来源:[1] FPGA 采用 Stratix V D5,有 172K 个 ALM,2014 个 M20K 片上内存,1590 个 DSP。板上有一个 8GB DDR3-1333 内存,一个 PCIe Gen3 x8 接口,两个 10 Gbps 网络接口。一个机柜之间的 FPGA 采用专用网络连接,一组 10G 网口 8 个一组连成环,另...
在过去的几年中,FPGA试图在高性能计算(high-performance computing ,HPC)和数据中心市场中发力。2017年,微软宣布在数据中心使用Altera FPGA,英特尔收购了Altera。2018年,Xilinx宣布了“数据中心优先”的战略,其CEO在分析师面前宣布,Xilinx不再是一家FPGA公司。这可能是一种轻微的戏剧化,但在历史上是有关联的。
“Using Altera’s Stratix III FPGA, the XD2000i delivers up to five times the logic capacity of previous generations of ISAs. Additionally, it offers unparalleled double-precision floating performance per watt, the key benchmark requested by our customers in high-performance computing and financial...
for market leading and innovate applications like 5G, Machine Learning (ML), Data Center or High-Performance Computing. "Designing a modular FPGA system reaching an interface performance of 32.75 Gbps was a big challenge and I wasn't sure, whether this was doable, because you are reaching the...
FPGA 正是一种硬件可重构的体系结构。它的英文全称是Field Programmable Gate Array,中文名是现场可编程门阵列。 FPGA常年来被用作专用芯片(ASIC)的小批量替代品,然而近年来在微软、百度等公司的数据中心大规模部署,以同时提供强大的计算能力和足够的灵活性。
“The flexibility, power efficiency, massively parallel architecture, and huge input/output (I/O) bandwidth make FPGAs attractive for accelerating a wide range of tasks from high-performance computing (HPC) to storage and networking. Many of these applications put enormous demands on memory, ...
参阅《用于基于 FGPA 的高性能计算的浮点数值数据流的带宽压缩(Bandwidth Compression of Floating-Point Numerical Data Streams for FPGA-Based High-Performance Computing)》:http://dl.acm.org/citation.cfm?id=3053688。 这种动态的架构敏捷性(architectural agility)很困难,几乎无法用其它任何方法实现。