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The Courts

RIAA Defendant Moves For Summary Judgment 117

Posted by timothy from the element-of-surprise dept.
NewYorkCountryLawyer writes "One thing you don't see too much of in RIAA litigation is a defendant moving for summary judgment, but that is what just occurred in federal court in Westchester, in Lava Records v. Amurao II. The RIAA had brought suit against Rolando Amurao, a middle aged man who knew nothing about file sharing. After haranguing him for 2 years, they dropped the case and sued his daughter, Audrey, who had used LimeWire years ago. When the RIAA moved for summary judgment against Audrey, however, she surprised them with a summary judgment motion of her own, calling for dismissal of the complaint on the grounds that the statute of limitations had run out on the RIAA's claims. The brief filed by her attorney (PDF) also points out some of the other infirmities in the RIAA's case, such as the inadmissibility of its evidence, the legal nonexistence of a claim for 'making available,' and the unconstitutionality of its damages theory. According to sources, the RIAA is unhappy about Audrey's motion, and is preparing a letter to send the Judge asking the Judge not to allow her to make it. Meanwhile, Audrey's father's case, Lava Records v. Rolando Amurao, is on appeal in the US Court of Appeals for the 2d Circuit over the issue of whether the RIAA should have to reimburse Mr. Amurao for his attorneys fees. Although the appeal was fully briefed and scheduled for argument May 19th, the RIAA has been asking for postponements of the argument."

Comment Single precision (Score 1) 134

by Gerb (#28009859) Attached to: Five Nvidia CUDA-Enabled Apps Tested

You get the big speedup only if you're doing single precision floating point computations.

On the NVIDIA GTX 280 & 260, a multiprocessor has eight single-precision floating point ALUs (one per core) but only one double-precision ALU (shared by the eight cores). Thus, for applications whose execution time is dominated by floating point computations, switching from single-precision to double-precision will increase runtime by a factor of approximately eight.

A lot of my HPC customers do CFD with (1) double precision in (2) Fortran. 1 and 2 are not easy or fast with CUDA.

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