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Carl Peterson ✓

@carlpeterson

Founder @thundercompute (YC S24) | Making GPUs abundant

1 386Followers
110Following
1 345Posts total
1.3MViews on collected posts

Latest posts

Thank you everyone for the love, we have been working towards this moment and are so excited to show you what comes next 442 views · 3 likes · 0 reposts · 0 replies Open on X →
@carlpeterson how does GPU virtualization unlock idle capacity more effectively than static allocation? 746 views · 7 likes · 0 reposts · 1 replies Open on X →
We're hiring across the board Come join us! https://t.co/vCAnPfcCsJ 10.1K views · 45 likes · 0 reposts · 1 replies Open on X →
Our goal is to virtualize every GPU We’ve secured $13M in Series A funding from Matrix Partners to scale virtualization to cloud providers and enterprises https://t.co/dDZmNr1mTd 10.8K views · 49 likes · 1 reposts · 1 replies Open on X →
Thunder Compute has built that virtualization layer for GPUs During YC, we launched our self-serve cloud platform Two years and 10,000 users later we’ve proven that physical GPUs can be virtualized in production Now we’re scaling the VMware for GPUs 11.7K views · 51 likes · 0 reposts · 1 replies Open on X →
Today, we raised a $13M series A to solve the GPU shortage Trillions are being spent on GPU CapEx while 80% of it sits idle The capacity already exists Virtualizing GPUs unlocks it Backed by Matrix, YC, and CEAS https://t.co/88zFVc96LC
1:17
1.3M views · 1.2K likes · 148 reposts · 201 replies Open on X →
In contrast, CPUs and storage have been virtualized for decades For example: When a cloud workload needs 100GB of storage, a virtualization layer sits over hundreds of drives and exposes exactly 100GB Virtualization creates flexibility, which enables efficiency 12.1K views · 45 likes · 0 reposts · 1 replies Open on X →
We are witnessing the largest capital infrastructure buildout in modern history Meanwhile, average GPU utilization is between 5% and 20%, because GPUs are not virtualized They are assigned statically to a workload regardless of whether that workload uses them 17.7K views · 57 likes · 0 reposts · 1 replies Open on X →

Against accounts of the same size

8 posts from the last 90 days, next to the under 10K follower range. shown widely, but few of those viewers react.

Median views11 225this account4 175median for under 10K
Reach, %809.88%this account250.82%median for under 10K
Engagement, %0.45%this account1.41%median for under 10K
MetricThis accountMedian for under 10KRatio
Median views per post11 2254 1752.69×
Reach (views ÷ followers)8.1× audience2.5× audience3.23×
Engagement rate0.45%1.41%0.32×

Others in this range →   Compare with another account →   How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

17.7K19 Aug
12.1K
1.3M
11.7K
10.8K
10.1K
746
44220 Aug

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.33%19 Aug
0.38%
0.13%
0.44%
0.47%
0.46%
1.07%
0.68%20 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for under 10K accounts is 1.41%.

What the audience does

Likes58.8%1 426 in total
Reposts6.1%149 in total
Replies8.5%207 in total
Quotes6.0%146 in total
Bookmarks20.5%497 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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