This is great news !
I just got a Tesla C870 at 500GIGAflops
I would love to use PDL's matrix manipulations
with it, I would love to see PDL merge with OpenCL
I think would Put PDL in the lime light ...
as well in my research I found a simple equation
that I have used effectively with PDL to
simulate Observable evidence of the electron
http://youtu.be/ofp-OHIq6Wo
then the electron Simulation
http://youtu.be/TKhokqmgFzI
energy = mass*speedoflight**2
a electron made from photons and anti-photons
energy*speedoflight**-2 = mass
I think all the hard work put in to PDL my pay off in a big way here
and could turn CERN on it's Head...
________________________________
From: David Mertens <[email protected]>
To: pdl-porters <[email protected]>; perldl <[email protected]>
Sent: Wednesday, May 9, 2012 11:28 AM
Subject: [Perldl] Fwd: NVIDIA Contributes CUDA Compiler to Open Source Community
FYI, this is a big deal. If anybody is in the San Jose area, you might consider
attending this.
I am not sure if or how we PDL developers should respond to this. Any ideas
would be great.
David
---------- Forwarded message ----------
From: CUDA Developer Relations <[email protected]>
Date: Wed, May 9, 2012 at 12:25 PM
Subject: NVIDIA Contributes CUDA Compiler to Open Source Community
To: [email protected]
The NVIDIA Compiler team have worked with the LLVM developers to provide key
CUDA compiler source code changes to the LLVM core and parallel thread
execution backend. The latest LLVM compiler with NVIDIA GPU support is now
available for download from the LLVM site.
At GPU Technology Conference (GTC), next week, we will be presenting more
details about the new compiler and releasing a preview of the LLVM-based CUDA
Compiler SDK that includes specifications, libraries, and code samples showing
how to interface with LLVM to produce GPU accelerated binaries from
domain-specific languages (DSLs).
It’s not too late to register for GTC, where you can engage with the NVIDIA
Compiler team directly. Of the 300+ technical sessions at the conference over
40 are focused on just parallel programming languages and compiler technology,
including:
• Compiling CUDA and Other Languages for GPUs (Session 235)
Vinod Grover & Yuan Lin, managers of the NVIDIA compiler team
• Delite: A Framework for Implementing Heterogeneous Parallel DSLs
(Session 365)
HyoukJoon Lee & Kevin J. Brown, PhD students at Stanford University
• Jet: A Domain-Specific Approach to Parallelism for Film Fluid Simulation
(Session 300)
Dan Baily, Research & Development at Double Negative
There is less than one week left, so register for GTC 2012 today!
See you there,
Nadeem Mohammad,
CUDA Developer Relations
Please note that this message was sent to the following email address:
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Copyright © 2012 NVIDIA Corporation. All rights reserved.
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Therefore, if you write the code as cleverly as possible, you are,
by definition, not smart enough to debug it." -- Brian Kernighan
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