Cryptocurrency Mining Is Fueling a GPU Shortage
Looking for a new graphics card online? Good luck. Continue reading Cryptocurrency Mining Is Fueling a GPU Shortage
Category Archives: gpu
Does aircrack-ng use GPU/CUDA capabilities?
As stated, does aircrack-ng when brute forcing a WPA2 handshake capture use GPU/CUDA resources such as a program like Hashcat does?
Continue reading Does aircrack-ng use GPU/CUDA capabilities?
Microchip’s PIC32MZ DA — The Microcontroller With A GPU
When it comes to displays, there is a gap between a traditional microcontroller and a Linux system-on-a-chip (SoC). The SoC that lives in a smartphone will always have enough RAM for a framebuffer and usually has a few pins dedicated to an LCD interface. Today, Microchip has announced a microcontroller that blurs the lines between what can be done with an SoC and what can be done with a microcontroller. The PIC32MZ ‘DA’ family of microcontrollers is designed for graphics applications and comes with a boatload of RAM and a dedicated GPU.
The key feature for this chip is a …read more
Continue reading Microchip’s PIC32MZ DA — The Microcontroller With A GPU
Nvidia is surging after its income more than doubled year-over-year
Nvidia’s ballooning GPU business and big bets on divisions like autonomous driving continue to look better and better, with the company’s shares jumping more than 10% after it reported its first-quarter earnings. In the first quarter this year, the company said it brought in $507 million in net income — up from $208 million in the first quarter a year ago. That doubled… Read More Continue reading Nvidia is surging after its income more than doubled year-over-year
Neural Networks: You’ve Got It So Easy
Neural networks are all the rage right now with increasing numbers of hackers, students, researchers, and businesses getting involved. The last resurgence was in the 80s and 90s, when there was little or no World Wide Web and few neural network tools. The current resurgence started around 2006. From a hacker’s perspective, what tools and other resources were available back then, what’s available now, and what should we expect for the future? For myself, a GPU on the Raspberry Pi would be nice.
The 80s and 90s
For the young’uns reading this who wonder how us old geezers managed to …read more
Apple’s Making Its Own GPU to Control Its Own Destiny
Graphics are the future. And Apple’s not leaving the future up to someone else. The post Apple’s Making Its Own GPU to Control Its Own Destiny appeared first on WIRED. Continue reading Apple’s Making Its Own GPU to Control Its Own Destiny
Password cracking speeds according to Hashcat
from the site: http://www.netmux.com/blog/how-to-build-a-password-cracking-rig – they used 4 GPUs:
Hashtype: Keepass 1 (AES/Twofish) and Keepass 2 (AES)
Speed.Dev.#*…..: 416.5 kH/sHashtype: sha512crypt, SHA512(Unix) Speed.Dev.#*…..: 452.4 kH/s
Hashtype: bcrypt, Blowfish(OpenBSD) Speed.Dev.#*…..: 43551 H/s
Hashtype: WPA/WPA2 Speed.Dev.#*…..: 1190.5 kH/s
Hashtype: MD5 Speed.Dev.#*…..: 76526.9 MH/s
Q: Does this means that example with 1 GPU we can brute-force (at least try to brute) 452.4×1000÷4= ~113100 passwords (stored in sha512crypt) per second?
UPDATE: the / 4 is ok, the real q wanted to be: is “H/s” the same as “P/s”? or we need further calculations for geting the passwords/sec? (asking because there are rounds/iterations in sha512crypt)
Continue reading Password cracking speeds according to Hashcat
Password cracking speeds according to Hashcat
from the site: http://www.netmux.com/blog/how-to-build-a-password-cracking-rig – they used 4 GPUs:
Hashtype: Keepass 1 (AES/Twofish) and Keepass 2 (AES) Speed.Dev.#*…..: 416.5 kH/s
Hashtype: sha512crypt, SHA512(Unix) Speed.Dev.#*…..: … Continue reading Password cracking speeds according to Hashcat
Hallucinating Machines Generate Tiny Video Clips
Hallucination is the erroneous perception of something that’s actually absent – or in other words: A possible interpretation of training data. Researchers from the MIT and the UMBC have developed and trained a generative-machine learning model that learns to generate tiny videos at random. The hallucination-like, 64×64 pixels small clips are somewhat plausible, but also a bit spooky.
The machine-learning model behind these artificial clips is capable of learning from unlabeled “in-the-wild” training videos and relies mostly on the temporal coherence of subsequent frames as well as the presence of a static background. It learns to disentangle foreground objects from …read more
Continue reading Hallucinating Machines Generate Tiny Video Clips
Hallucinating Machines Generate Tiny Video Clips
Hallucination is the erroneous perception of something that’s actually absent – or in other words: A possible interpretation of training data. Researchers from the MIT and the UMBC have developed and trained a generative-machine learning model that learns to generate tiny videos at random. The hallucination-like, 64×64 pixels small clips are somewhat plausible, but also a bit spooky.
The machine-learning model behind these artificial clips is capable of learning from unlabeled “in-the-wild” training videos and relies mostly on the temporal coherence of subsequent frames as well as the presence of a static background. It learns to disentangle foreground objects from …read more
Continue reading Hallucinating Machines Generate Tiny Video Clips