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USENIX LISA2021 Computing Performance: On the Horizon

Brendan Gregg

It's an exciting time for developments in computer performance, not just for the BPF technology (which I often [write about]) but also for processors with 3D stacking and cloud vendor CPUs (e.g., This was a chance to talk about other things I've been working on, such as the present and future of hardware performance.

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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

At USENIX SREcon22 APAC I gave the opening keynote on the future of computer performance, rounding up the latest developments and making predictions of where I see things heading. This talk originated from my updates to [Systems Performance 2nd Edition], and this was the first time I've given this talk in person! Or even on a plane.

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The Return of the Frame Pointers

Brendan Gregg

I'm sure this delivered large performance improvements and I wouldn't try arguing against it. While that Java change led to discovering countless performance wins in application code, libc was still breaking some portion of the samples (as pictured in the example at the top of this post) and preventing off-CPU flame graphs.

Java 145
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The Performance Inequality Gap, 2024

Alex Russell

The usual caveats also apply: Performance is a deep and nuanced domain, and much can go wrong beyond content size and composition. How sites manage resources after-load can have a big impact on perceived performance. Until and unless teams have better data about their performance, the global baseline budget should be enforced.

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USENIX LISA2021 Computing Performance: On the Horizon

Brendan Gregg

It's an exciting time for developments in computer performance, not just for the BPF technology (which I often [write about]) but also for processors with 3D stacking and cloud vendor CPUs (e.g., This was a chance to talk about other things I've been working on, such as the present and future of hardware performance.

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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

At USENIX SREcon22 APAC I gave the opening keynote on the future of computer performance, rounding up the latest developments and making predictions of where I see things heading. This talk originated from my updates to Systems Performance 2nd Edition , and this was the first time I've given this talk in person!

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A Brief Guide of xPU for AI Accelerators

ACM Sigarch

TFLOPS deep learning performance, and is equipped with 32GB of high-bandwidth memory (HBM) capacity. The new DGX-2, which achieves 2 petaFLOPS in the system, combines 16 fully interconnected GPUS with 10x the deep learning performance. HPU: Holographic Processing Unit (HPU) is the specific hardware of Microsoft’s Hololens.