Folding@home is biological
research based upon the science of
Molecular Dynamics
where molecular chemistry and mathematics are combined in
computer-based
models
to predict how protein molecules might fold in three spatial dimensions over time.
When I first heard about this, I recalled Isaac Asimov's sci-fi
masterpiece colloquially known as
The Foundation Trilogy
which introduces the fictional branch of science called
psychohistory
where statistics, history
and sociology are combined in computer-based models to predict humanity's
future. How did Asimov conceive of such things?
Years ago I became infected with an
Isaac
Asimov inspired optimism about humanity's future and have since felt
the need to contribute to it. While Folding@home will not cure my
"infection of optimism", I am convincedDr. Asimov (who received a Ph.D. in Biochemistry
from Columbia in 1948 then was employed as a Professor of Biochemistry at the Boston School of Medicine staying
there until 1958 when his sci-fi story-writing workload became too large) would have been fascinated by something like this.
Dr. Asimov, I'm computing these protein folding
sequences in memory of you and your work.
I was considering a financial
charitable donation to Folding@home when it occurred to me that
my money would be better spent by:
Making a knowledgeable charitable donation to all of humanity
by increasing my Folding@home
computations (which will advance medical discoveries along with
associated pharmaceutical treatments thus lengthening human
life). I was already folding on
a half-dozen computers anyway so all I needed to do was purchase
used video cards on eBay.
Convincing others (like you) to follow my example.
My solitary folding efforts will have little effect on humanity's
future. Together we can make a real difference.
Update: you may find the
folding-at-home article at Wikipedia
more informative than my personal effort here.
Science Problem:
Misfolded proteins have been associated with numerous diseases as well
as age-related illnesses. However, proteins are so much more larger and
complicated than smaller molecules that it is not possible to begin a
chemical experiment without first providing hints to researchers about
where to look and what to look
for. Since the behavior of "atoms-in-molecules" (Computational
Chemistry) as well as "atoms-between-molecules" (Molecular
Dynamics) can be modeled, it makes more sense to begin with a
computer analysis. Then permitted configurations can then be passed on to
experimental researchers.
Real-world observation:
Cooking an egg causes the clear protein (albumen) to
unfold into long strings, with the result that they now can intertwine into
a tangled network which will stiffen and scatter light (appear white). No chemical
change has occurred but taste, volume and color
have been altered.
Click
here to read a short "protein article" published by Isaac
Asimov in 1993 (shortly after his death).
Computer Solution:
Single CPU Systems
Using the most powerful single core processor (CPU) available today, simulating
the folding possibilities of one large protein molecule for
one
millisecond of chemical time might require one million
days (2737 years) of computational time. However (and this is
where you come in), if the problem is sliced up then assigned to 100,000
personal computers via the internet, the computational requirement would drop to
ten days. Convincing friends, relatives, and
employers to also do the same could drop the computational requirement further.
chemical time in nature
simulation time
one computer
one computer
100,000 computers
1 million computers
1 uS (0.000001 seconds)
1,000 days
2.73 years
14.4 mins
1.44 mins
1 mS (0.001 seconds)
1,000,000 days
2,737 years
10 days
1 day
1 S (1.0 seconds)
1,000,000,000 days
2,737,850 years
27 years
2.7 years
Additional information for techies, hackers and science buffs:
Special-purpose research computers like IBM's
BlueGene and
Roadrunner
employ 10,000 to 20,000 processors (CPUs) joined by many kilometers of
optical fiber to do
something similar.
As of December 2012, the Folding@home
project consists of
214,000 active processors
(some CPUs, some GPUs) which is equivalent to 4.2 PetaFLOPS. This means that
the million-day protein simulation problem could theoretically be completed
in (1,000,000/214,000) 4.7
days. But since there are many more protein molecules
than DNA molecules, humanity could be at this for quite some time to
come.
Adding your computers to Folding@home will permanently advance mankind's
progress in protein research.
Personal Comments:
214,000 is almost half
the number recorded one year ago.
I wonder how much of this drop was due to Sony discontinuing
support for folding-at-home on PS3
I wonder how much of this drop was due to AMD/ATI dropping
support for OpenCL on Windows-XP
I wonder how much of this drop was due to Stanford dropping
support for GPU2 cards (everything before HD-5000) from AMD/ATI
I wonder how much of this drop is due to people moving from PCs
(personal computers) to tablets and pads
I am also shocked at the low turnout (439) by MAC OS X users.
This has got to reflect a mistake in stats collection.
There are almost 1 billion accounts registered on Facebook. Even
if some of these entries represent organizations, I am shocked that
there are less than one million "active processors" at
folding-at-home. We all know there are other distributed
computing projects on the internet but "less than one
million protein-folders" seems a crime against
humanity.
When the
Human
Genome Project (to study human DNA) was being planned it was
thought that the task may require 100 years. However, technological change
in the area of computers, robotic sequencers, and use of the
internet to coordinate the activities of a large number of
universities (each assigned a small piece of the problem),
allowed the human genome project to publish results after only 15
years.
Distributed computing projects like Folding@home and
BOINC have only been possible since 1995 when the
world-wide-web (which
was first proposed in 1989 to solve a document sharing problem at CERN) began to
make the internet popular and ubiquitous.
Traditionally, processor technology was defined like this:
SSE
replaces
MMX
(both are SIMD but SSE uses its own floating point registers)
2001: SSE2 was
implemented on Pentium 4 from Intel
2004: SSE3 was
implemented on Pentium 4 Prescott on from Intel
2006: SSE4 was
implemented on Intel Core and AMD K10
2008:
AVX (Advanced Vector Instructions) proposed by Intel + AMD but
not seen until 2011
this technology employs 256-bit
instructions
But GPU (graphics programming units) take
vector processing to a whole new level. Why? A $200.00
graphics card now equip your
system with 1500-2000 streaming processors and 2-4 GB of additional
high speed memory.
I've been in the computer hardware-software business for along
time
but can tell you that things have only started to get real
interesting this side of Y2K (perhaps Y2K10).
Distributed computing projects like Folding@home and
BOINC have only been practical since 2005 when the CPUs
in personal computers began to out-perform mini-computers and enterprise servers. This
was partly because...
AMD added 64-bit support to their x86 processor technology calling
it x86-64.
Intel followed suit calling their 64-bit extension technology
EM64T
Intel added DDR2 support to their
Pentium 4 processor
line
AMD added DDR2 support to their
Athlon 64
processor line
Since then, the following list of technological improvements has only made computers both
faster and cheaper:
multi-core
(each core is a fully functional CPU)
chips from all manufacturers
shifting analysis from each CPU core into multiple (hundreds to
thousands) streaming processors found in high-end graphics cards
ATI (now AMD) Radeon graphics cards
NVidia GeForce graphics cards
development of high performance "graphics" memory technology (e.g.
GDDR3 ,
GDDR4 ,
GDDR5) to bypass
processing stalls caused when processors are too fast. Note that GDDR5
will represent main memory in the not-yet-release
PlayStation 4
(PS4)
Intel's abandonment of
NetBurst which meant
a return to shorter instruction pipelines starting with
Core2 Comment: AMD never went to longer pipelines; a long
pipeline is only efficient when running a static CPU benchmark for marketing
purposes - not running code in real-world where i/o events interrupt the
primary foreground task (science in our case)
this technology was
invented by DEC for their Alpha CPUs and named CSI (Common System Interconnect).
Compaq bought DEC
in 1998.
The Alpha Engineering team and Alpha Technology was sold to Intel in 2001 during merger discussions between HP and Compaq.
The merger was completed in 2002.
The AMD equivalent of QPI is called
HyperTransport
which has been described as a multipath Ethernet targeted for use within a
computer system.
As is true in any "demand vs. supply"
scenario, most consumers didn't need the additional computing power which
meant that chip manufacturers had to drop their prices just to keep the
computing marketplace moving. This
was good news for people setting up "folding
farms". Something similar is happening today with computer
systems since John-q-public is shifting from "towers and desktops" to "laptops
and pads". This is causing the price of towers and graphics cards to plummet
ever lower. You just can't beat the price-performance ratio of an
Core-i7 motherboard hosting an NVidia graphics card. (prediction:
laptops and pads will never ever be able to fold as well as a tower; towers will
always be around in some form; low form-factor desktops might become extinct)
Shifting from brute-force "Chemical Equilibrium" algorithms to
techniques involving
Bayesian statistics and
Markov Models will
enable some
exponential speedups.
Liquid Water This diagram
depicts an H2O molecule loosely connected to four others
Computational Chemistry
Question: After perusing the
periodic table for a moment you will soon realize that the
molecular mass of
water (H2O) is ~18 while the molecular mass of oxygen (O2) is ~32,
carbon dioxide (CO2) is ~44 and ozone (O3) is
~48. So why is H20 in a liquid state at room temperature while other slightly heavier molecules take the form of a gas?
Substance
Molecule
Atomic Masses
Molecular Mass
State at Room Temperature
Water
H2O
(1x2)+16
18
liquid
Molecular Oxygen
O2
(16x2)
32
gas
Carbon Dioxide
CO2
12+(16x2)
44
gas
Ozone
O3
(16x3)
48
gas
Methane
CH4
12+(1x4)
16
gas
Ethane
C2H6
(12x2)+(1x6)
30
gas
Propane
C3H8
(12x3)+(1x8)
44
gas
Butane
C4H10
(12x4)+(1x10)
58
gas
Pentane
C5H12
(12x5)+(1x12)
72
gas
Hexane
C6H14
(12x6)+(1x14)
86
liquid
Heptane
C7H16
(12x7)+(1x16)
100
liquid
Octane
C8H18
(12x8)+(1x18)
114
liquid
Short answer: In the case of
an H20 molecule,
even though two hydrogen atoms are electrically bound to one oxygen atom,
the same hydrogen atoms are also attracted to each other and this causes the
water molecule to bend into a Y shape. At the mid-point of the bend, an
electrical charge from the oxygen atom is exposed to the world which allows a weak
connection to the hydrogen atom of a neighboring H20 molecule (water
molecules weakly sticking to each other form a liquid). These weak
connections are called
Van der Waals
forces
Van der Waals did all his computations with pencil and
paper long before the computer was invented but it was only possible because
the molecules involved were small.
Chemistry
Caveat: The compound table above was only meant to get you thinking
because Molecular Mass is not all there is to the picture. Getting back to the
periodic table
for a moment will show:
all elements in column 1 (except hydrogen) are solid at room
temperature
all elements in column 8 (helium to radon) are gaseous at room temperature
Half the elements in row 2 starting with Lithium (atomic number 3)
and ending with Carbon (atomic number 6), as well as two thirds of
row 3 starting with Sodium (atomic number 11) and ending with Sulphur (atomic number 16), are
solid at room
temperature.
I will leave it to you to determine why.
hint: the answer also involves
the repulsive force between
electrons as well as the attractive force between electrons and protons.
Molecular
Dynamics
Proteins come in many shapes and sizes. Here is a
very short list:
This "folding knowledge" will be used to develop new drugs for treating
diseases such as:
ALS ("Amyotrophic Lateral Sclerosis" a.k.a. "Lou Gehrig's Disease")
Alzheimer's
Disease
Plaques, which contain misfolded peptides called amyloid beta,
are formed in the brain many years before the signs
of this disease are observed. Together, these plaques and neurofibrillary
tangles form the pathological hallmarks of the disease
Cancer
& p53
P53 is the suicide gene
involved in apoptosis (programmed cell death - something
necessary in order your immune system to kill cancer cells)
CJD (Creutzfeldt-Jakob Disease)
the human variation of mad cow disease
Huntington's
Disease
Huntington's disease is caused by a trinucleotide repeat expansion
in the Huntingtin (Htt) gene and is one of several polyglutamine
(or PolyQ) diseases. This expansion produces an altered form of
the Htt protein, mutant Huntingtin (mHtt), which results
in neuronal cell death in select areas of the brain. Huntington's
disease is a terminal illness.
Osteogenesis
Imperfecta
Normal bone growth is a yin-yang
balance between osteoclasts and oseteoblasts. Osteogenesis Imperfecta
occurs when bone grows without sufficient or healthy collagen
(protein)
Parkinson's
Disease
The mechanism by which the brain cells in Parkinson's are lost
may consist of an abnormal accumulation of the protein alpha-synuclein
bound to ubiquitin in the damaged cells.
Ribosome
& antibiotics
A ribosome is a protein producing
organelle found inside each cell
Folding@home: the most powerful and energy
efficient supercomputer in the world -
Vijay Pande (Stanford University) gave this one hour lecture
at PARC (Palo Alto Research Center) on 2009-01-08
All my SETI credits were
accumulated in the early 2000s on a few DEC Alpha servers. I stopped contributing to SETI
(sorry SETI) when I
came to the realization that biological and climate science would bring immediate
benefits to humanity.
Rosetta, POEM, and
Docking are protein related.
CPDN (Climate Prediction Data Network) is a group
running "what if" scenarios on climate models.
WCG
(World Community Grid) is a unified science group.
Current Folding-at-Home Stats (updated every 3 hours)
faster because I bought a bunch of ATI graphics cards on eBay
3
100
2009-01-14
4
083
2009-04-07
faster because I upgraded my ATI graphics cards to GPU2
5
084
2009-06-30
6
088
2009-09-26
7
115
2010-01-19
slower because non-GPU resources were diverted to BOINC (its
all about the science)
8
103
2010-05-02
9
149
2010-09-28
slower because one PC motherboard has burned out (will not
repair or replace)
10
178
2011-03-25
slower because one graphics card burned out
11
172
2011-09-13
a little faster - upgraded one graphics card from HD-3800 to
HD-5570
12
156
2012-02-16
faster because of experiments with an SMP client on a quad-core
machine
13
101
2012-05-27
Faster because: 1. upgraded all version 6 clients to version 7.1.52 2. upgraded two graphics cards from HD-3870 to HD-6570 3.
moved my single SMP client from my Intel Core2 Quad Q6600 system to a
Core-i7
system 4. added an SMP client to a second Core-i7 system
14
37
2012-07-03
Faster because two Windows-XP machines where changed from
AMD/ATI HD-3870 to NVidia GTX-560 (they hadn't folded for a couple of months
because AMD deleted my OpenCL driver; Why?AMD no longer supports OpenCL on
Windows-XP)
15
27
2012-07-30
The NVidia cards are speedsters (AMD should have never driven me
to their competition)
16
21
2012-08-20
The majority of these impressive times come from two NVidia GTX-560 cards (and two Intel Core-i7
CPUs; each running an SMP client configured for 6 processors rather
than 8).
17
18
2012-09-07
18
17
2012-09-24
19
18
2012-10-12
20
17
2012-10-29
21
23
2012-11-21
A little slower because: 1. I experienced a 24-hour internet outage
2. Sony discontinued support for folding-at-home (my PS3 had been
folding since 2007)
22
20
2012-12-11
A little slower because of problems at the Stanford website over
Christmas
23
15
2012-12-26
24
14
2013-01-09
25
15
2013-01-24
26
15
2013-02-08
27
17
2013-02-25
A little longer; power supply problems with one PC
28
14
2013-03-11
A little faster (clicked over at 23:00)
29
17
2013-03-28
Probably should have been 16 days (see previous line)
30
17
2013-04-14
31
19
2013-05-03
32
19
2013-05-22
Using your NVidia graphics card to do
protein-folding science
Executive Summary: while a single core Pentium-class CPU
provides also provides one streaming (vector) processor under marketing names like MMX and SSE, one
graphics card can
provide hundreds to thousands of streaming (vector) processors.
Modern computers can do 3d graphics two different ways:
in software using a general purpose CPU (central processing unit)
like Intel's Pentium or AMD's Athlon
in specialized hardware using a special purpose GPU (graphics
processing unit) like those found in:
NVidia graphics cards
ATI graphics cards
Sony's PS3 (PlayStation 3) system which can achieve speeds of
100 GigaFLOPS per console
Microsoft's XBOX-360 game console
Scalar vs. Vector
CPUs (central processing units) are scalar processors which
execute instructions sequentially
RISC processors can exploit certain kinds of
instruction-level parallelism. In some cases they can execute
instructions out-of-order.
Modern processors (CISC and RISC) also support SIMD (single instruction - multiple
data) technology for certain applications involving DSP (digital
signal processing) or
multi-media.
In the Intel world, SIMD technology goes by the name
MMX/SSE/SSE2, etc.
GPUs (graphics programming units) are vector
processors which easily execute parallel operations
AMD/ATI cards typically support anywhere between 800 and 200
streaming processors
(typically labeled "unified shaders")
NVidia cards typically support fewer streaming processors but
seem to be able to utilize them more efficiently
Since graphics cards have their own large memory systems, they
should be thought of as a private computer system within your
computer. Remember that this private computer is not going to be
continually trounced by real-world interrupts, etc.
Charlie Rose interviews
NVidia president and CEO, Jen-Hsun Huang (pronounced:
gen-son wang).
This 38 minute interview from February 2009 features many
GPU-related topics including CUDA (Compute Unified Device Architecture).
Quote: "The CPU is
irrelevant; now it's all about the GPU"
When preparing to run the Folding@home GPU client for the first
time, do not waste your time attempting to use the UPDATE DRIVER tool from
within the DEVICE MANAGER. Instead, go to the NVidia web site and download a
stand-alone driver application.
In some rare instances (like using a non-Windows operating system) you may need to download the CUDA driver
separately from this location:
www.nvidia.com/object/cuda_get.html
My Personal Experience Doing GPU-based Science:
I run a mixture of systems employing graphics cards from both AMD/ATI
and NVidia.
Most of my systems employ the HD-6670 from AMD/ATI.
Two of my
systems employ the GTX-560 from NVidia (I was forced to buy these
cards when AMD/ATI removed OpenCL support from their Windows-XP device
driver in the Spring of 2012)
When purchased new, the price of GTX-560 is
approximately twice that of the HD-6670 but seems to be doing 9-10 times more science even
though my NVidia cards are installed on older hardware platforms running
older operating systems.
Information from 2008 (stills seems technically relevant today)
Now to be fair, when you compare mid-range priced cards between
these two companies it would seem that NVidia cards are
only doing twice as much science.
If you are are setting up protein folding systems for charitable
humanitarian purposes then considering spending the extra money to buy an NVidia GTX-560
In 2013 the GTX-560 product has been replaced with
GTX-660
Make sure you buy something with a GTX prefix rather than a GE
prefix
Make sure the last two digits are 60, 70, 80 or 90.
Table: GTX-6xx Technical Comparisons
Using your ATI graphics card to do protein-folding science
Stream Computing at ATI (acquired by AMD in 2006)
ATI (2005) claims that science software will run 20 to 40 times faster
on a GPU (graphics processing unit) than a traditional general purpose CPU. ATI didn't tell us if they were
comparing to Pentium-3 (which only supported MMX/SSE) or Pentium-4
(where early models also included SSE2 support while later models
also included SSE3 support)
an October 2006 trial by Stanford indicated a science speedup of over 70 times when tuned for the ATI-x1950 graphics card.
The GPU2 client running on an HD-3870 is rumored to increase analysis
throughput (relative to a CPU client) by over 105 times.
Modern computers can do 3d graphics two different ways:
in software using a general purpose CPU (central processing unit)
like Intel's Pentium or AMD's Athlon
in specialized hardware using a special purpose GPU (graphics
processing unit) like those found in:
ATI graphics cards
NVidia graphics cards
Sony's PS3 (PlayStation 3) system which can achieve speeds of
100 GigaFLOPS per console
Microsoft's XBOX-360 game console
Scalar vs. Vector
CPUs (central processing units) are scalar processors which
execute instructions sequentially
RISC processors can exploit certain kinds of
instruction-level parallelism. In some cases they can execute
instructions out-of-order.
Modern processors (CISC and RISC) also support SIMD (single instruction - multiple
data) technology for certain applications involving DSP (digital
signal processing) or
multi-media.
GPUs (graphics programming units) are vector
processors which easily execute parallel operations
ATI's x1950 was released in 2006 with 36 streaming processors (pixel shaders)
ATI's HD-4870 was released in 2008 with 800 processors
(unified shaders)
This is an increase of 22 times in only 2 years. (Moore's Law
only expects one doubling every 18 months)
Since graphics cards have their own large memory systems, they
should be thought of as a private computer system within your
computer. Remember that this private computer is not going to be
continually trounced by real-world interrupts, etc.
synchronized with
delayed release of Windows 7 1600/800 = 2.0 fold increase in one year (growth is currently exceeding Moore's law)
Radeon HD6870
AMD/ATI
1536
unified (programmable)
GPU3
Cayman XT
2010
Radeon HD7970
AMD/ATI
2048
unified (programmable)
GPU3
Tahiti XT
2012
GeForce GTX 560
NVidia
288:48:24
Vertex:Geometry:Pixel
GPU3
GF114
2011
This graphics card is the most powerful folder in my
collection but look at the relatively (compared to AMD/ATI) low
number of shaders. The speed is due to
architectural differences.
all clients may stop working when a certain date is reached. This is
normal behavior and you usually only need to download a newer client or
new device driver.
See: 2012
AMD/ATI Caveat
below for recent bad news for people running Radeon cards on Windows-XP
AMD/ATI GPU2 Graphics Card Caveat
(2012)
Time and technology never stand still and the same is true for graphics
cards. You can imagine the difficulty science organizations experience
while trying to keep up with the constant introduction of new products from hardware
manufacturers.
For the past half-decade the computer industry as been working on heterogeneous technologies
(OpenCL,
CUDA,
PhysX,
DirectCompute,
etc.) for doing science on graphics cards. Stanford
Folding Software requires OpenCL (Open Computing Language)
which must not be confused with OpenGL (Open Graphics Library).
Announcement: Stanford to drop GPU2 cards
made by AMD/ATI
In March-2012, Stanford University announced their intention to
drop AMD/ATI GPU2 cards in September, 2012.
Reason: OpenCL on GPU2 cards from AMD/ATI (everything before
HD-5000) was implemented in software (Brook language for GPU
programming) which is being discontinued.
GPU3 cards from all vendors implement OpenCL are implemented in
hardware.
GPU folding on Windows-XP is no longer
supported by AMD/ATI
In April-2012, all my graphic-card-based folding platforms
stopped folding (could not get a work unit)
I noticed new client software was available from Stanford so I updated all my machines from the
version 6 GPU
client to the version 7 unified client but
still no luck (could not get a work unit)
Next, I updated all my AMD/ATI drivers from version 10 to 12 then one
machine with an HD-5570 immediately began to fold
Next, I replaced one of my HD-3870 cards with a new
HD-6570 and that system began to fold as well
At first I didn't suspect an OpenCL problem because one of my
systems was running an HD-4650 which did support OpenCL
when I bought it
AMD is no longer supporting
OpenCL on
Windows platforms below Windows-Vista SP2
so my
OpenCL driver was deleted during the driver upgrade.
Rolling back the driver will only buy you a small amount
of time since Stanford is shifting from GP2
(fahcore_11) hardware to the newer GP3 (fahcore_16) hardware.
All the cards
above HD-4xxx support GPU3 (but not on Windows-XP or lower)
It looks like AMD still supports OpenCL on Linux (OpenSUSE,
Ubuntu, RedHat/Fedora)
My advice to those using AMD/ATI
graphics card owners:
run the
GPU-Z diagnostic to make sure your hardware and
drivers are still capable of supporting OpenCL
as of 2012-05-xx the minimum AMD/ATI requirements are:
host OS: Windows-Vista (SP2), Windows-7
or Windows-8
alternatives for those with the wrong OS (or
obsolete graphics hardware)
Give up on GPU-based folding and only do CPU-based
folding
Replace Windows with Linux (will be okay as long as AMD/ATI produces
an OpenCL driver for Linux)
Consider switching to
NVidia cards
which continue to support OpenCL on older operating
systems
This might be the best
science-wise decision. Why?
Many BOINC clients will only work with NVidia cards
supporting CUDA or PhysX (more science-friendly)
AMD/ATI cards only support: OpenCL
(depending on your OS) and sometimes DirectCompute
Most GTX NVidea cards support: OpenCL,
CUDA, PhysX,
DirectCompute
My actions:
I tried to go the cheap route by purchasing used
NVidia cards on eBay but didn't have any luck (they
hardly seem to go up for resale).
So I was forced to buy new units from a retail
store.
For folding purposes you should not buy anything
less than a
GeForce GTX 560 (I bought two of these)
I was able to trial a GeForce GT 520
before purchasing from a friend but found it
unacceptable for my needs (too slow)
As of this writing (2012-06-xx) you want a
part number with GTX (not GT) because "X"
versions do more science in hardware. But double-check
the specs because info at many retail web sites seem woefully inaccurate.
While older cards can no longer be used for science they
still can be used as video cards. I sold all my AMD/ATI cards on
kijiji.ca (a
subsidiary of eBay)
NSR Comments:
We live in a Dilbert world which means there is no way to predict the
actions of "corporate suits". I wonder how much money AMD saved (if any)
by dropping OpenCL from their device drivers on Windows-XP. Did AMD
actually think about Risk-vs-Reward before making this decision? It was
ATI who originally partnered with Stanford and it seems to me that
the suits at AMD (who acquired ATI in 2006) have less passion for
the graphics card business. Perhaps AMD should have stuck with
competing head-to-head with Intel on processors.
Update: I just (2013-02-xx) learned that AMD will be producing
APU chips for the recently announced
PlayStation 4
(PS4) and it is rumored that the yet unannounced
XBOX-720 (code
name "Durango") will
use the same chips in order to reduce costs for cross-platform game
publishers. If true, AMD stands to make a huge sum of money in this
business so maybe they are (slowly) deferring the PC-based graphics
business to NVidia and Intel.
Using your Playstation3 (PS3) to do protein-folding science
Five
reasons to buy a
Playstation 3 now
(June 2008):
The 2008 consoles (PS3-40 and PS3-80) only require 110 watts compared
to previous models (PS3-10 and PS3-60) which required 220 watts.
The Canadian price has dropped from $699 to $399
Blu-ray player can play either hi-def Blu-ray
movies or standard-def DVD movies
When not playing games or watching movies, you can contribute to
folding@home
Five
reasons to buy a
Playstation 3
now (August 2009). Sony has just released a new PS3 model called
PS3-Slim which:
is one third smaller in size
requires one third less power
25% price decrease from from $399 to $299
features: 120 GB hard drive
dropped: Third-party OS install (no Linux install capability which
very few people used anyway)
Multicore: It's No Game (June 9, 2007) http://www.ddj.com/architect/199902753 Quote: In total, approximately 250,000 PlayStation3 consoles are
contributing about 400 TFLOPs of compute power, making it the number one
compute-resource contributor to Folding@home - more than doubling that from
Windows-based PCs.
Sony Studies Commercial PlayStation 3 Supercomputing Grid (April
11, 2007) http://www.ddj.com/architect/199000499 Quote: On Wednesday, for example, 20,000 of the 200,000 PS3 users
who have signed up for the Folding@home project were online, delivering
a combined processing speed of 267 teraflops, Dave Karraker, spokesman for
Sony Computer Entertainment America, told InformationWeek. By comparison,
the 200,000 PCs online were producing a combined speed of 240 teraflops.
A teraflop is a trillion mathematically computations, called floating-point
operations, per second.
(2012-October) Sony to discontinue folding-at-home
(in November-2012)
Earlier this year, Radeon graphics-card manufacturer AMD made a huge mistake
(IMHO) by
dropping support for OpenCL on older platforms like Windows-XP. This only
chased protein folders to NVidia (AMD's main competitor in the graphics
market).
Next month, Sony announced they will drop support for folding-at-home.
If you think this is a mistake, then tell Sony your thoughts by posting
here:
A few years ago I convinced family (mostly cousins,
nieces and nephews) and friends at work to purchase a PS3 console rather
than an XBOX-360 because the Sony product could support folding-at-home
while the Microsoft product could not. Now Sony is making the same
mistake as AMD. How short sighted.
Sony pulled the plug on 2012-11-06
Okay so Sony had a few self-inflicted security problems with
their network last year (possibly loosing in the neighborhood of $1
billion) but does that mean they need to get nasty then pinch
pennies with a valuable charitable offering like this? I think not.
GPU Programming (this knowlege is not required to use
folding-at-home)
Scalar vs. Vector
CPUs (central processing units) are scalar processors
which execute instructions sequentially
Some RISC processors can exploit certain kinds of
instruction-level parallelism. In some cases they can
execute instructions out-of-order.
Some CISC processors support SIMD (single instruction -
multiple data) instructions for certain applications
involving DSP or multi-media.
GPUs (graphics programming units) are PC-based vector
processors which easily execute parallel operations
The ATI x1950 was released in 2006 with 36 processors
(pixel shaders)
The ATI HD-3870 was released in 2007 with 320 processors
(unified shaders)
The ATI HD-4870 was released in 2008 with 800 processors
(unified shaders)
This is an increase of 22 times in only 2 years.
(Moore's Law expects transistors to double every 18 months)
Since graphics cards have their own large memory
systems, they should be thought of as private computer
systems within your computer. Also, this private memory is
not going to be trounced by interrupting devices etc.
In most cases vector processors are easily two orders of
magnitude (100 times) more powerful than scalar processors. Some are
three orders of magnitude
https://simtk.org/home/openmm (molecular
mechanics/molecular dynamics) is the next big thing in computers. While
modern CPUs tend to support one-to-four cores and solve problems
sequentially, modern GPUs support 300-800
cores and compute in parallel. Modern GPUs do not (yet) seem to be
limited in the same way that Moore's Law affects today's CPUs.
http://go.microsoft.com/fwlink/?LinkId=4544
- Windows Server 2003 Resource Kit Tools (Also works with XP) includes cool stuff like: imagecfg , sleep (used to pause a script), timezone
, etc.
Stopped services may only be deleted from DOS like so:
sc query neil369
sc delete neil369
Console Client Startup
Script for GPU1
caveat: no longer required with the newer GPU2 clients associated starting
with HD-2000 series ATI cards
@echo off
echo "================================="
echo "GPU console client control script"
echo "================================="
echo "sleeping 2 minutes while Windows is starting"
echo "you may wish to start TASK-MANAGER to set CPU Affinity"
@echo on
sleep 120
cd /d c:\folding-0
:myloop
echo "starting the GPU console client"
fah6-win-gpu-console.exe -local
echo ">>> the console has just exited <<<"
echo "did someone do a 3-finger salute?"
echo "sleeping 1 minute while the system stabilizes"
sleep 60
goto myloop
rem ==============================
Notes:
"sleep" is an application found in the "Windows Server 2003 toolkit"
which can be downloaded from here: http://go.microsoft.com/fwlink/?LinkId=4544 Make sure you place a copy of "sleep.exe" in your working directory (or
invoke it by its full path name)
if this is a new-client installation then you must first run the client
manually to configure the settings file
as of 2007-12-31 you should make sure that your screen saver is set
to "none" in order to avoid a reset of the graphics card
an alias to this script should be placed in the following location:
Start >> Programs >> Startup
If you set the affinity of the CMD process while it is still waiting
to start, you then won't need to set the affinity of any daughter tasks.
BOINC (Berkeley Open Infrastructure for Network Computing)
BOINC
(Berkeley Open Infrastructure for Network Computing) is a science framework in which
you can support one, or more, projects of choice.
If you are unable to pick a single cause then pick several because
the BOINC manager will switch between science clients every hour (this interval is adjustable). In my
case I actively support POEM, Rosetta, and Docking.
The current BOINC client can be programmed to use one, some, or all
cores of a multi-core machine. The BOINC client can also utilize (or
not) the streaming processors on your Graphics Card.
Caveat: If you care about advancing science then
you should run multiple science projects (I do) and perhaps multiple clients
(I run Folding@home as well as BOINC). These computer rooms are mostly
maintained by university students and I have found that they usually run out
of data, or experience server problems (like full disks) on holiday long
weekends. So when one of your science projects goes off line due to some
technical problem beyond your control, then your computer can stay busy with
the alternate projects. Because just like that advert 30-years ago stating
"A mind is a terrible thing to waste", I believe "a
computer is a terrible thing to waste"
Other Protein Analysis
Projects
POEM@home (via BOINC)
http://boinc.fzk.de/poem/ is the
home of POEM@Home (Protein
Optimization with Energy Methods)
which operates through the BOINC framework
http://boinc.bakerlab.org/rosetta/
is the home of Rosetta@home
which operates through the BOINC framework. Their graphics screen-saver is one
very effective way to help visualize "what molecular dynamics is all about". Science teachers
must show this to their students.
I'm sure everyone already knows that a computer "rendering
beautiful graphical displays" is doing less science. That said,
humans are visual creatures and graphical displays have their place
in our society. Except for some public locations, all clients
should be running in
non-graphical mode so that more system resources are diverted to
protein analysis.
Five questions for Rosetta@home: How Rosetta@home helps cure cancer,
AIDS, Alzheimer's, and more
http://en.wikipedia.org/wiki/World_community_grid
(WCG) is an effort to create the world's largest public computing grid
to tackle scientific research projects that benefit humanity. Launched
2004-11-16, it is funded and operated by IBM with client software currently
available for Windows, Linux, Mac-OS-X and FreeBSD operating systems.
They encourage their employees and customers to do the same.
Personal Comment: I wonder why Hewlett-Packard (a.k.a. HP) has not followed IBM's lead.
Up until now I always thought IBM was the template of uber-capitalism but it
seems that the title of "king of profit by the elimination of seemingly
superfluous expenses" goes to HP. Don't they realize that IBM's effort
in this area is done under IBM's advertising budgets? Just like IBM's 1990s
foray into chess playing systems (e.g. Deep Blue) led to increased sales as
well as share prices, one day IBM will be able to say "IBM
contributed to a treatments for human diseases including cancer". IBM
actions in this area reinforce the public's association with IBM and
information processing.
http://www.technologyreview.com/view/510571/the-million-core-problem/
The Million-Core Problem - Stanford researchers break a supercomputing
barrier. quote: A team of Stanford researchers have broken a record in
supercomputing, using a million cores to model a complex fluid dynamics
problem. The computer is a newly installed Sequioa IBM Bluegene/Q system at
the Lawrence Livermore National Laboratories. Sequoia has 1,572,864
processors, reports Andrew Myers of Stanford Engineering, and 1.6
petabytes of memory.