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Make a deal with Sam Westrick
🔒 Paid proposals held safely in escrow — released only when the work's approved.
Followers
410
Account age
3 yrs
💰 Suggested sponsorship rate
$40 – $65 / sponsored post
Estimated from audience size & typical reach — every deal is negotiable and held in SocialDB escrow.
🧰 Free analysis for Sam Westrick
Known for
6 views
my student Seong-Heon talking about one of our new projects at NYU!
(We’re at NJPLS today, come say hi)
4 views
Now we can easily peek inside a computation, even deeply across library boundaries. This is great for finding performance issues buried in places you did not expect.
For example, using just a few lines of code we can identify a granularity control issue inside of a library we did not author ourselves. We describe a case study in detail in the paper.
2 views
This paper is all about making it easy to dynamically observe the computation graph of a parallel execution (for profiling purposes, dynamic analyses, etc)
Customization is easy: just define a notion of vertex-local data and functions to update this data across forks and joins.
These custom vertices are handed off to an “augmented” scheduler, which incrementally maintains the computation graph und
1 views
Video post
📊 Post engagement
5
Avg engagement / post
1.2%
Engagement vs followers
Nov 2022
On Mastodon since
🔥 Top post: delighted to announce that our SPAA paper received an outstandin · 17 likes + reposts
📊 Activity & format
Posting cadence
0.39 / week
A lower-frequency account — each post lands with more weight.
Content mix
Mostly text
Recent: 7 text · 4 image · 1 video.
Follower / following
1.8×
Follows 227 back. A more reciprocal / networked account.
Recent posts
View on Mastodon ↗
(panopto preview is no good; recommend open in a separate window and then fast-forward to 1 hour mark)
incredibly honored that our paper on Scheduler Augmentation won this year's _Best Paper Award_ at SPAA!
This is joint work with my students Darshan Dinesh Kumar and Seong-Heon Jung. They did really fantastic work on this project!
Check out…
▶
Video post
RE: https://discuss.systems/@shwestrick/116872683907627841
getting some cool visuals going…
https://github.com/nyu-parcour/scheduler-augmentation/tree/graph-viz
Critically, none of these analyses incur major overhead: just a few percent in typical applications and use-cases, and fully parallelized, with almost no impact on scalability.
Scheduler augmentation is easily deactivated when not in use, …
In another case study, we measure the impact of a subtle space optimization.
With just a few lines of code, we can empirically confirm that the optimization works as intended, by measuring peak memory consumption as an abstract property on…
Now we can easily peek inside a computation, even deeply across library boundaries. This is great for finding performance issues buried in places you did not expect.
For example, using just a few lines of code we can identify a granularity…
This paper is all about making it easy to dynamically observe the computation graph of a parallel execution (for profiling purposes, dynamic analyses, etc)
Customization is easy: just define a notion of vertex-local data and functions to u…
We've extended the deadline for the ML Family Workshop 2026! The new deadline is
** July 1, AoE **
The submission requirements are fairly minimal: only 2 pages. Please consider submitting, and encourage your friends to do so too!
https:…
the ML Family Workshop (@ ICFP'26) submission deadline is approaching -- **Wednesday June 24**
Please consider submitting! We especially welcome works-in-progress. Submission requirements are minimal -- just 2 pages.
https://icfp26.sigplan…
my student Seong-Heon talking about one of our new projects at NYU!
(We’re at NJPLS today, come say hi)
▶
Video post
RE: https://discuss.systems/@shwestrick/116872683907627841
getting some cool visuals going…
https://github.com/nyu-parcour/scheduler-augmentation/tree/graph-viz
Critically, none of these analyses incur major overhead: just a few percent in typical applications and use-cases, and fully parallelized, with almost no impact on scalability.
Scheduler augmentation is easily deactivated when not in use, …
In another case study, we measure the impact of a subtle space optimization.
With just a few lines of code, we can empirically confirm that the optimization works as intended, by measuring peak memory consumption as an abstract property on…
Now we can easily peek inside a computation, even deeply across library boundaries. This is great for finding performance issues buried in places you did not expect.
For example, using just a few lines of code we can identify a granularity…
This paper is all about making it easy to dynamically observe the computation graph of a parallel execution (for profiling purposes, dynamic analyses, etc)
Customization is easy: just define a notion of vertex-local data and functions to u…
We've extended the deadline for the ML Family Workshop 2026! The new deadline is
** July 1, AoE **
The submission requirements are fairly minimal: only 2 pages. Please consider submitting, and encourage your friends to do so too!
https:…
the ML Family Workshop (@ ICFP'26) submission deadline is approaching -- **Wednesday June 24**
Please consider submitting! We especially welcome works-in-progress. Submission requirements are minimal -- just 2 pages.
https://icfp26.sigplan…
my student Seong-Heon talking about one of our new projects at NYU!
(We’re at NJPLS today, come say hi)
🐘 Community & instance
Home server
discuss.systems
Their home server on the fediverse — the instance a creator picks signals the community they belong to.
✅ Link-verified
Verified link
Proved ownership of a website linked on their profile — Mastodon's green-check verification, a real identity signal rather than a paid badge.
On Mastodon since
Nov 2022
Joined in the Twitter-exodus wave of late 2022 — part of the migration that made Mastodon a real destination.
💡 Facts
🗓️Joined Mastodon in 2022 — 3 years ago.
👁️Averages 5 views per post.
📤Posts about 0.4× per week.
🛡️ Audience credibility
89/100
Excellent
Credibility score
99%
Real
Real audience
Low
Fake-follower risk
High
Data confidence
- Est. 99% real, active audience · Low fake-follower risk.
- Strong engagement (~1.2% of followers engage each post) — an active, real audience.
- Verified account.
- Established account (3+ years old).
Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.
About
assistant professor of CS at NYU Courant :: programming languages :: parallel computing :: music :: lead dev of the MaPLe compiler (https://github.com/mpllang/mpl)
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