Tag Archives: talk

Talk: Extragalactic B-fields from Gamma Rays

Speaker: Tom Weisgarber (Chicago)

  • Voids: <1nG; filaments: ~0.3 µG; galaxies: ~1 µG; clusters: 10 µG.  No detections of B-fields in voids.
  • Gamma rays interact with the extragalactic background light (EBL) and create electron-positron pairs, which then cascade down to create more gamma rays. This cascade is then observed with some opening angle.  Pair production and inverse Compton scattering are the important processes in creating the cascades.
  • Semi-analytic model for the cascade: Huan+ (2011, ApJL 735, 28). Using the blazar RGB J0710+591, they constrain the B-field to be <3e-16 G (<3e-18 G for a 3 year livetime).

GPU Meeting (04 Oct 2011)

Lionel London (CRA) – GPU Computing in Matlab

  • Matlab Parallel Computing Toolbox (PCT) vs. Jacket
  • PCT allows for multi-cpu and GPU computing. Limited to 12 cores on the local machine. Very high level.
  • GPU computing with PCT requires an nVidia card with v1.3 compute capabilities. GPGPU with Jacket has relaxed requirements but is very expensive ($4k for 5 licenses!)
  • PCT GPU can run external .cu files.
  • Jacket has 10x more CUDA-enabled functions than Matlab.  It’s cluster capable.

Talk: Magnetar Dynamics & Grav. Waves

Kostas Kokkotas (Tübingen)

  • Magnetars exhibit regular gamma-ray flares that are preceded by star quakes or glitches in the pulsations.  The largest flares have L ~ 10^47 erg/s (3 since 1979).
  • No natural explanation for (1) sudden stop of activity P ~ 12 sec and (2) AXP-SNR association but no SGR-SNR association
  • Thompson & Duncan (1990’s) – developed a fireball model that erupts from the NS surface to explain these largest bursts.
  • Can QPOs be explained by global Alfvèn waves?  (see KK publications)
  • NS models, using perturbation theory, with crust and B-fields to predict QPO frequencies.  No crust oscillations at B > 4 x 10^14 G.
  • Gravitational wave amplitudes are unknown and must be calculated with simulations (3D GRMHD).
  • Simulation of B-field instability (Lasky et al. 2011, ApJL) and prediction for GW (Zink et al. 2011)

GPU Meeting (20 Sept 2011)

Matt Kinsey: Porting the 2D Wave Equation to the GPU
  • Optimal number of threads per block is 32*n-1, where n is an integer.  The best performance in the example shown was 63 threads per block.
  • Minimum number of blocks per grid is 32, according to the user’s guide.
  • Every time a kernel is called, the memory needs to be pushed from the CPU to the GPU.  Thus it is optimal to minimize the kernel calls.
  • In the 2D wave equation problem, Matt utilized texture memory to reduce the number of kernels to one.  The memory is indexed in a space-filling curve.  This results in better cache locality.
  • With texture memory, one can take advantage of built-in linear interpolation and boundary conditions.  Texture memory can be addressed in 1D, 2D, and 3D.