
Denser digital infrastructure and pervasive wireless have raised background radio-frequency levels. Here’s how EMI threatens data centers and what operators can do to contain it.
Electromagnetic interference (EMI) is an invisible disruption caused by electromagnetic waves from natural sources like lightning and human-made sources like cellular transmitters and power supplies that can damage data center equipment and cause outages. The risk is growing because digital infrastructure is becoming denser and more widespread, with ubiquitous wireless networks and high-power 5G infrastructure creating higher baseline electromagnetic energy, while data centers themselves generate EMI that can affect neighboring facilities. Data centers can protect against EMI through shielding with conductive materials like aluminum, installing EMI-resistant gaskets, using power supplies with built-in filtering, maintaining proper grounding and bonding, organizing cables carefully, and selecting sites away from strong emitters like cellular infrastructure and high-voltage transmission lines. Beyond environmental factors, intentional attacks using EMI to cause targeted interference represent an additional threat that many operators have historically underestimated in their risk assessments.

In this tutorial, we explore TileLang as a high-level Python domain-specific language for designing and compiling performance-oriented GPU kernels through TVM. We begin by validating the CUDA environment and establishing reusable benchmarking and numerical-verification utilities, then progressively implement vector addition, tiled tensor-core matrix multiplication, schedule exploration, fused GEMM epilogues, row-wise softmax, and FlashAttention. Throughout the tutorial, we work directly with Ti

A close call in Northern Virginia revealed just how poorly data centers respond to grid disruptions. Here's how to fix the problem.

As AI infrastructure grows more complex, companies are rethinking how they acquire, own, and finance assets that operate on dramatically different economic timelines.
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