Embedded processors always have had the focus on low-energy. Now a combination of Moore’s law, the frequency-wall and multi-processor developments have made it possible for these processors to compete in completely new market segments. Most notable due to impressive advancements in graphics IP.We are now looking at four groups who are interested in learning from
LEAP-conference call for papers Read More »
In OpenCL large memory objects, residing in the main memory of the host or the global memory at the accelerator/GPU, need special treatment. First reason is that these memories are relatively slow. Second reason is that the most times serial copy of objects between these two memories take time. In this post I’d like to
OpenCL Basics: Flags for the creating memory objects Read More »
For more information on the program, contact us. For information on sponsoring, contact Tim Lewis of CroftEdge. Website with more info and ticket-sales will open 1 February.
Low-Energy Application Parallelism (LEAP) conference in London Read More »
HiPEAC is the conference on “High-performance and Embedded Architectures and Compilers” to be held on 20 to 22 January in Berlin – tickets are still available, if you can spare three days. I (Vincent Hindriksen) would like to share the program I’m doing. Edit: I met great people here and hope to see you next
StreamHPC is at HiPEAC, Berlin Read More »
Important: this article was written before Intel “Haswell” and AMD “Richland” architectures came out. So you want to start developing for OpenCL? When you focus on developing OpenCL for X86, you have these three options: CPUs, GPUs and CPUs with and embedded GPU. This article is for you and represents the current state of hardware – if you
X86-workstation buying guide for OpenCL developers, Q1 2013 Read More »
Every now and then I read stories on Bitcoins (Wikipedia-article), as GPUs are used a lot to “mine” Bitcoins. They have some extensive benchmarks, and also their discussions giving me insights in specific parts of accelerators like GPUs. Also is this group very upwards if it comes to accepting new techniques. Today something changed: they
The entanglement of Bitcoins and compute-capabilities Read More »
Say you have some data that needs to be used as input for a larger kernel, but needs a little preparation to get it aligned in memory (small kernel and random reads). Unluckily the efficiency of such kernel is very low and there is no speed-up or even a slowdown. When programming a GPU it
The OpenCL power: offloading to the CPU (AVX+SSE) Read More »
During the “little” HPC-show, SC12, several vendors have launched some very impressive products. Question is who steals the show from whom? Intel got their Phi-processor finally launched, NVIDIA came with the TESLA K20 plus K20X, and AMD introduced the FirePro S10000. This card is the fastest card out there with 5.91 TFLOPS of processing power
AMD positions FirePro S10000 against both TESLA K10 (and K20) Read More »
NOTE: there are many contradicting sources out there, so there are mistakes in this article. Please give me feedback via twitter, mail or comments, so all the info can be completed. Yes, another post in the answer-to series. At SC12 Intel tries to steal away the show from the Tesla K20 and FirePro S10000. After
Intel’s answer to AMD and NVIDIA: the XEON Phi 5110P Read More »
Two months ago I wrote about the FirePro S9000 – AMD’s answer to the K10 – and was already looking forward to this K20. Where in the gaming world, it hardly matters what card you buy to get good gaming performance, in the compute-world it does. AMD presented 3.230 TFLOPS with 6GB of memory, and now
NVIDIA’s answer to FirePro S9000: the TESLA K20 Read More »