At GTC Japan, NVIDIA announced the Tesla T4 GPU, the company’s first datacenter product that incorporates the capabilities of the Turing architecture. To go along with the new hardware, the GPU-maker is also releasing enhanced TensorRT software.
According to the latest analysis from Hyperion Research, the various global efforts to reach exascale supercomputing are making good headway. But in some cases, the decision to develop domestically-produced processors for these systems and the inclusion of new application use cases appears to be stretching out the timelines.
With a share price riding high and dominance in the datacentre market, it may seem perverse to state that Intel is a company facing a range of significant problems. So what caused the technology behemoth on the occasion of its 50th birthday to find itself so spectacularly on its back foot?
In the second installment of our two-part report on the Student Cluster Competition (SCC), we trace the history of the top three teams at the recent ISC High Performance conference (ISC18) and look at the factors that drove their success.
Every contest has winners and losers. If you have spent much time following student cluster competitions at HPC conferences, you may wonder, as I have, why some win time and again, while others have a difficult time placing. You may also wonder why some never make it on the field.
In a bid to reinvent computer graphics and visualization, NVIDIA has developed a new architecture that merges AI, ray tracing, rasterization, and computation.The new architecture, known as Turing, was unveiled this week by NVIDIA CEO Jensen Huang in his keynote address at SIGGRAPH 2018.