71–80 of 209 posts
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Also https://www.reddit.com/r/wallstreetbets/
And of course https://www.reddit.com/r/AyyMD/ Right now the hot topic is this gem: https://www.youtube.com/watch?v=PjCVaMYdjgo
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Some examples that can easily push you beyond 64 GB: - high resolution photo editing: when you start with a 80 mpix / 48 bit photo from a medium format camera pushing beyond 16 GB requires only a couple layers and a couple undo steps being available - high resolution video processing. 1 second of uncompressed 4k 60fps video is almost 1.4GB - very large application compilation: building Android requires 16GB of RAM/sw…
What camera is capturing 16GB photos? An IQ180 captures 80 megapixels but the images are something like 500 MB each. All of your hypothetical examples are also for very niche high-resource usage professionals. It's absurd that these cases need extremely high memory support from consumer processors. Intel is not obligated to subsidize anyone, especially not people who can afford to pay for high end systems.
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Just because someone can afford to rent a $30,000 camera doesn't necessarily mean they have unlimited cash to burn on other things.
It's about $2000/week to rent an IQ180. If you can afford the rental price, you can afford a computer to process the images.
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64gb workstation ought to be enough for anybody. Jokes aside, what do you do if you are interested in >64gb workstations?
Quantum chemistry. There are a number of high accuracy wavefunction based methods that are compute-tractable on desktop machines but very demanding of storage. Even when there's a disk based alternative to RAM storage it's a lot slower when you can't just allocate huge arrays in memory. I could easily use 256 GB, maybe 512, on a machine with 8 physical cores. You can get commercial software that is a bit better tuned…
I just hope this lives up to the hype. I built my last machine using Phenom II X6 1090T but I always regretted it after; as the 6 core advantage that I thought future games will use, never materialized and per core performance of that was not as good as the Intel CPUs of the same generation. Most of the benchmark leaks have focussed on top of the line Ryzens, I would be interested in seeing how the mid level Ryzens a…
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Exactly. Ridiculous Intel pricing and artificial limitations were a consequence of de facto monopoly. I absolutely hate how they cap maximum RAM on consumer machines, so that you need to pony up for a Xeon workstation if you need more than 64 GB.
The recent generations can address 128GB as long as your motherboard supports it (my X99 board does).
This article doesn't actually list any benchmarks and the link/URL is totally broken for the "Ryzen offers even better single-threaded performance per clock than Intel’s Kaby Lake." - http://single-threaded/
in the video, they say they cant release any benchmark until march 2nd. not sure why.
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The other day, I was struggling to emulate a Hadoop cluster in a series of VMs on a 16G laptop with zero work being performed - just keeping all the services and Cloudera's management scripts and tools made everything swap everywhere. VMs are my biggest memory hog, particularly when they are running lots and lots of separate Java processes.
And the problem with your 16GB system was that it didn't support >64GB?
It's usually foolish to say that we don't have need for more X in computing because nothing today warrants more than X; the thing is, if we have more of X, we find uses for it. Most of what we do can trade space for time, or incorporate things in cache hierarchies; and sometimes quantitative change adds up to a qualitative change because new architectural approaches become possible.
If I could have 1TB in my laptop, it would change the way we at my company develop software. In fact we'd rewrite our product to take advantage of that much memory, the case would be overwhelming; we'd introduce a new tier in our architecture for keeping a copy of the customer's working set (typically several GB) in memory. As it is, we rely on the database and its caching; it's OK, but it can't support all the operators we'd like to support.
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I use a sound sampler (Hauptwerk) that loads tens of thousand of wavefiles and needs a polyphony (simultaneous samples being played) of thousands of voices to simulate a pipe organ. The minimum configuration for the smallest instrument (one voice) with natural acoustics (ie. original ambient reveberation recorded) is 4gb. The normal requirements for some good instruments are 64-128gb for 24-bit 6-channel uncompressed…
> 24-bit (...) uncompressed audio Do you really need this much headroom, e.g. for producing music professionally? (If so, why are you arguing over the $50-100 extra for a Xeon?) Because for listening, it's proven fact that even professional musicians and mixing engineers using equipment costing >$100k can't tell 24 bit from 16 bit in a proper double-blind A/B test. Presumably you use a high sample rate as well (maybe…
While people here like to quote that infamous looks-like-science-but-isn't Xiph video, the reality is that a lot of professional engineers absolutely can hear the difference.
If you have good studio monitors and you know what to listen for the difference between a 24-bit master and a downsampled and dithered 16-bit CD master is very obvious indeed, and there are peer reviewed papers that explain why.
Dither was developed precisely because naively interpolated or truncated 16-bit audio is audibly inferior to a 24-bit source.
Many people certainly can hear the effect of dither on half-decent hardware, even though it's usually only applied to the LSB of 16-bit data. From a naive understanding of audio a single bit difference should be completely inaudible, because it's really, really quiet.
From a more informed view it isn't hard to hear at all - and there are good technical reasons for that.
For synthesis, you don't want dither. You want as much bit depth as possible so you can choose between dynamic range and low-level detail. So 24-bit data is the industry standard for orchestral samples.
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Quantum chemistry. There are a number of high accuracy wavefunction based methods that are compute-tractable on desktop machines but very demanding of storage. Even when there's a disk based alternative to RAM storage it's a lot slower when you can't just allocate huge arrays in memory. I could easily use 256 GB, maybe 512, on a machine with 8 physical cores. You can get commercial software that is a bit better tuned…
Honestly that application sounds like you should be able to just get that 512G machine. Buffered ECC DDR4 RAM has gotten cheaper over the last year too.
(Tangentially: I wouldn't bother with ECC RAM for this application unless that were required by the rest of the hardware. Memory errors may slightly affect time to a converged solution, but it's rare that a flipped bit would actually cause a job to converge to a different solution.)