stefanpie

11 ms·

91.
by stefanpie 3y ago
I would take a look at pymoo library which has a good enough API for using in for applied problems I’ve run into in my research. It’s also surprisingly flexible to extend / subclass for any needs you need as well.
92.
by stefanpie 3y ago
Not sure, my best advice would be to just email the authors if you are interested. Seems like they presented to ASPLOS so maybe the students disappeared over the summer for internships or vacation.
93.
by stefanpie 3y ago
One group at Georgia Tech in our building has also been working on open source GPU designs that can also target FPGAs and interoperate with RISCV. They have several publications on the work they have built up. Thought I might share since it
94.
Mastermind Solver(stefanabikaram.com)
1 points by stefanpie 3y ago|0 comments
95.
by stefanpie 3y ago
To point 1, many classes I’ve been in (undergrad and grad) have study groups form at the beginning of the semester where I decide I’m just gonna go though the class solo. In that case, it’s fully conceivable for a subset (or almost all of t
96.
OpenAssistant Chat LLM Released(open-assistant.io)
1 points by stefanpie 3y ago|0 comments
97.
by stefanpie 4y ago
Yes, the FPGAs! Atlas and other experiments at CERN require such complex and hard-read time requirements, making them great applications of FPGAs. Right now, I am working on a project to try and deploy graph neural networks for track recons
98.
“The RISC Journey from One to a Million Processors” (2022) [pdf](microarch.org)
1 points by stefanpie 4y ago|0 comments
99.
by stefanpie 4y ago
During a recent conference I attended, a keynote speaker discussed their idea of having CPUs with at least 10,000 RISC-V cores and servers with one million RISC-V cores [1]. The idea is appealing, but how feasible is it and how does RISC ma
100.
XLS: Google's Open-Source HLS Tool(google.github.io)
1 points by stefanpie 4y ago|0 comments
101.
by stefanpie 4y ago
Timeseries data can sometimes be deceptive, depending on what you are trying to model. I have been hacking on a peroneal research project to predict hurricane tracks furcating using deep learning. Only given track and intensity data at diff
102.
“XLS: Accelerated HW Synthesis” – Google's Open-Source HLS Tool(google.github.io)
1 points by stefanpie 4y ago|0 comments
103.
by stefanpie 4y ago
My academic page list some of my initial publications in this area (mostly graph neural network accelerators for FPGAs): < https://stefanabikaram.com/ >. My lab's webpage has way more publications on the topic as w
104.
by stefanpie 4y ago
I work in this field of research, and right now, there are many people trying to reach the ultimate goal of "anyone can take their existing code, and my tool will run it on an FPGA and will be 100x faster / 100x more efficient&quo
105.
FPGA Design Elements(fpgacpu.ca)
1 points by stefanpie 4y ago|0 comments
106.
Genetic Football(web.archive.org)
1 points by stefanpie 4y ago|0 comments
107.
So You Want to Abolish Time Zones(qntm.org)
1 points by stefanpie 4y ago|0 comments
108.
by stefanpie 4y ago
Antihypoxiant by Andy Weir: http://www.galactanet.com/oneoff/antihypoxiant.html
109.
by stefanpie 4y ago
Fixed point is a super fun rabbit hole into quantization and numerical representations. I work with them all the time for FPGA hardware design and HLS to build deep learning models and HLS is our bread and butter.
110.
by stefanpie 4y ago
When joining my current research lab, this book was a god send. For context this book is directed at users who are interested in high level synthesis which at the simplest level let's you write C++ code to convert to hardware construc
111.
by stefanpie 4y ago
Amaranth (previously nmigen) is super awesome declarative ways to build circuits. I like to think of it as a superior verilog alternative that lets you do RTL design in Python. Being able to use python constructs to dynamically build logic
112.
by stefanpie 4y ago
I remember the original twitter thread on the topic but haven't heard much about it since then. It would be interesting to see a nice arxiv submissions with some initial experiments across common tasks and architectures. Would also be
113.
Mastermind Solver(stefanabikaram.com)
1 points by stefanpie 4y ago|0 comments
114.
Common pitfalls for Covid-19 detection using deep learning on medical images(nature.com)
1 points by stefanpie 4y ago|0 comments
115.
by stefanpie 4y ago
Link to the relevant journal article: https://ieeexplore.ieee.org/document/9714188
116.
NIST Digital Library of Mathematical Functions(dlmf.nist.gov)
1 points by stefanpie 5y ago|0 comments
117.
Matrix Market(math.nist.gov)
1 points by stefanpie 5y ago|0 comments
118.
Matrix Market(math.nist.gov)
1 points by stefanpie 5y ago|0 comments
119.
Parallel Programming for FPGAs(arxiv.org)
1 points by stefanpie 5y ago|0 comments
120.
by stefanpie 5y ago
As a novice Linux (Ubuntu) user, I am curious as to how these new changes for rand will speed up a Linux distro overall or if there is even a way to measure this. It seems that, in addition to an overdue replacement SHA-1, the new code is a

More ›