Thread by @IanCutress

Here for @AMD DC event. Starts at 10am PT, follow this thread along with the stream!🧵

I expect to see @LisaSu, Mark Papermaster, Forrest Norrod, and Victor Peng on stage talking about #AI, #Bergamo, and #MI300

youtube.com/live/l3pe_qx95…

I'm with these goobers!
@dylan522p @PaulyAlcorn @Patrick1Kennedy

Lisa on stage

Optimizing for different workloads in the DC, Inc AI

Focused on building industry standard CPUs. Now the standard in the cloud. 640 epyc instances available in the cloud today

Genoa in November, 96 cores, pcie gen 5, CXL

Enterpiese leadership in industry standard workloads

Power efficiency is #1 on industry standard efficiency tests

Best CPU for AI in the market in TPCx-AI vs comp

Details on these tests likely to be in the backend of the slide deck

AWS to the stage

Happy Lisa

AWS Nitro + 4th Gen epyc. I think this is a #Bergamo comment

New M7a instances. Best price/perf x86 EC2 instance. Video transcoding, simulation, BF16

AMD uses these instances internally for data analytics workloads

Expanding to EDA too

New #Oracle instances in July for #Genoa

But future workloads need optimised infra

Now for cloud native computing - scale out with containers. Benefit from density and energy efficiency. Enter #Bergamo

128 cores per socket, 82 B transistors

Uses same io die, but new 16 core core dies.

Optimised for density, not perf, but completely same isa for software compatibility. 35% smaller core physically optimized, same socket and same IO support. Same platform support as Genoa

Up to 2.6x vs comp in cloud native workloads

Double density, double efficency, vs comp

Shipping now in volume to hyperscale customers. Meta to the stage

Enablement through an open source platform via OCP. Meta is using AMD in AI

Meta can rely on AMD to deliver, time and time again

Deploying #Bergamo internally, 2.5x over Milan, substantial TCO. Easy decision. Partnered with AMD to provide design optimisations at a silicon level too

Time for #Genoa-X. Dan mcnamara to the stage

This is all technical computing.

2nd gen vcache for over 1GB L3 per socket

Four new skus, 16-96 cores, available today

Xeon 8490H vs Genoa-X

These slides went fast. Azure in stage to talk about HPC

Ansys fluent 3.6x over first gen epyc using Milan-X

Memory optimized HX instances with Genoa-X.

Customer adoption, Petronas (tie in with Mercedes F1?). Looks like oil and gas getting back in the limelight as an important vertical

GA on azure for #Genoa-X

Now for #siena. Coming later this year

Citadel talking about workloads requiring 100k cores and 100PB databases. Moved to latest gen AMD for 35% speedup.

1 million cores *. Forrest says very few workloads require that much. So efficiency and performance matters.

Density required to be as close to the financial market as possible. Latency is key, so also xilinx in the pipeline.

Here we go. Using alveo.

Solarflare NICs for millions of trades a day. Architecture needs to be optimized together.

Same thinking drove the acquisition of #Pensando. Network complexity has exploded. Managing these resources is more complicated, especially with security.

Removing the CPU tax due to the infrastructure, before you even get to load balancing

#Pensando P4 DPU. Forrest calls it the best networking architecture team in the industry

Freeing the CPU from it's overhead

I'm in the wrong seat. Can't see any of the hardware images. Can see all the text though

SmartNICs already in the cloud. Available as VMware vSphere solutions.

New P4 DPU offload in a switch. #Pensando silicon alongside the switching silicon.

HPE Aruba switch

Enables end to end security solutions

Just says this was the first half of the presentation. So now ai

Aiaiaiaiaiaiai

Lisa back to the stage. AI is the next big megatrand

AMD wants to accelerate AI solutions at scale. AMD has #AI hardware

AMD already has lots of AI partners

$150B TAM by 2027

That includes CPU and GPU

Better photo. AMD going down the HPCxAI route.

Victor Peng to the stage!

The journey of AMD's AI stack. Proven at HPC scale

AI software platforms. Edge requires Vitis

Reminder : it's "Rock-'em". Not 'Rock-emm'.

Lots of ROCm is open source

Running 100k+ validation tests nightly on latest AI configs

Pytorch founder to the stage

I'm excited about #MI300 - pytorch founder

Day 0 support for #ROCm on PyTorch 2.0

Not every model is an LLM

@huggingface CEO on the stage.

New @AMD and @huggingface partnership being announced today. Instinct, radeon, ryzen, versal. AMD hardware in HF regression testing. Native optimization for AMD platforms.

Were talking training and inference. AMD hardware has advantages.

Still waiting for #MI300!

Lisa back to the stage.

At the center is GPU

New compute engine on CDNA3

Now sampling #MI300A

13 chiplets

Can replace CPU chiplets for GPU only version

So you replace 3 CPU chiplets with 2 GPU chiplets, add in more HBM for a total of 192GB of HBM3. That's 5.2 TB/sec of mem bandwidth.

153 BILLION TRANSISTORS.
That's #MI300X from @AMD

H100 only has 80GB. Means AMD has better scaling, better TCO, reduces overhead.

8x #MI300X in OCP infrastructure for open standards. Accelerates TTM and decreases dev costs. Easy to implement. $AMD

#MI300X for LLMs

#MI300A available today.
#MI300X available Q3
Ramping in Q4

That's a wrap for today. More sessions later, not sure about embargoes, but will say what I can when I can!