Compute
Intel To Set Its FPGA Unit Free To Pursue Its Own Path
Maybe Intel chief executive officer Pat Gelsinger has spent too much time at EMC and VMware. …
Altera
Compute
Intel To Broaden FPGA Lineup And Make Them At Home
Back in 2015, when Intel was flush with cash thanks to a near-monopoly from X86 datacenter compute, it shelled out an incredible $16.7 billion to acquire FPGA maker Altera because a few hyperscalers and cloud builders were monkeying around with offloading whole chunks of CPU compute to FPGAs to create SmartNICs. …
Compute
How Far Can You Push Integration With FPGAs?
If you squint your eyes, a modern FPGA looks like a programmable logic device was crossbred with the mutt of a switch ASIC and an SoC. …
Connect
The Killer Apps For FPGAs Could Be SmartNICs And Storage
If FPGAs are going to take off in the datacenter in their own right, they are going to need their own killer apps. …
Compute
Covering All The Compute Bases In A Heterogeneous Datacenter
Intel has spent more than three decades evolving from the dominant provider of CPUs for personal computers to the dominant supplier of processors for servers in the datacenter. …
Compute
Stratix 10 SX At The Heart Of Intel’s Most Powerful FPGA Accelerator
Intel has started shipping a new FPGA accelerator card based on the high-end Stratix 10 SX FPGA. …
Compute
With Agilex, Intel Gets A Coherent FPGA Strategy
When Intel purchased Altera in 2015 for $16.7 billion, company officials predicted that up to a third of servers would be equipped with FPGAs by 2020. …
Compute
Intel Kicks FPGA Performance Up a Notch With Stratix 10 PAC
Intel is gearing up the FPGA user base it inherited from Altera for the release of Stratix 10 hardware and companion application acceleration stack. …
HPC
OpenCL Optimizations Make Case for FPGAs in HPC
The use of FPGAs in HPC is limited less by the capabilities of current hardware and more by the challenges in programming them without sacrificing performance. …
AI
Intel FPGA Architecture Focuses on Deep Learning Inference
There has been much written about the potential for FPGAs to take a leadership role in accelerating deep learning but in practice, the hurdles of getting from concept to high performance hardware design are still taller than many AI shops are willing to scale, particularly when GPUs dominate in training and in a pinch, standard CPUs will do just fine for datacenter inference since they involve little developer overhead. …