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In spring 2005 Azul introduced a 24 core machine tuned for Java. A couple years later they were at 48 and then jumped to an obscene 768 cores which seemed like

by hinkley 10mo ago

In spring 2005 Azul introduced a 24 core machine tuned for Java. A couple years later they were at 48 and then jumped to an obscene 768 cores which seemed like such an imaginary number at the time that small companies didn’t really poke them to see what the prices were like. Like it was a typo.

fweimer 10mo ago
Before clusters with fast interconnects were a thing, there were quite a few systems that had more than a thousand hardware threads: https://linuxdevices.org/worlds-largest-single-kernel-linux-system/ https://linuxdevices.org/worlds-largest-single-kernel-linux-... We're slowly getting back to similarly-sized systems. IBM now has POWER systems with more than 1,500 threads (although I assume those are SMT8 configurations). This is a bit annoying because too many programs assume that the CPU mask fits into 128 bytes, which limits the CPU (hardware thread) count to 1,024. We fixed a few of these bugs twenty years ago, but as these systems fell out of use, similar problems are back.
- alexjplant 10mo ago
  > Driven by 1,024 Dual-Core Intel Itanium 2 processors, the new system will generate 13.1 TFLOPs (Teraflops, or trillions of calculations per second) of compute power. This is equal to the combined single precision GPU and CPU horsepower of a modern MacBook [1]. Really makes you think about how resource-intensive even the simplest of modern software is... [1] https://www.cpu-monkey.com/en/igpu-apple_m4_10_core https://www.cpu-monkey.com/en/igpu-apple_m4_10_core
  - fweimer 10mo ago
    Note that those 13.1 TFLOPs are FP64, which isn't supported natively on the MacBook GPU. On the other hand, local/per-node memory bandwidth is significantly higher on the MacBook. (Apparently, SGI Altix only had 8.5 to 12.8 GB/s.) Total memory bandwidth on larger Altix systems was of course much higher due to the ridiculous node count. Access to remote memory on other nodes could be quite slow because it had to go through multiple router hops.
  - hinkley 10mo ago
    My Apple Watch can blow the doors off a Cray 1. It’s crazy.

by hinkley 10mo ago

fweimer 10mo ago

Before clusters with fast interconnects were a thing, there were quite a few systems that had more than a thousand hardware threads: https://linuxdevices.org/worlds-largest-single-kernel-linux-system/ https://linuxdevices.org/worlds-largest-single-kernel-linux-... We're slowly getting back to similarly-sized systems. IBM now has POWER systems with more than 1,500 threads (although I assume those are SMT8 configurations). This is a bit annoying because too many programs assume that the CPU mask fits into 128 bytes, which limits the CPU (hardware thread) count to 1,024. We fixed a few of these bugs twenty years ago, but as these systems fell out of use, similar problems are back.

alexjplant 10mo ago
> Driven by 1,024 Dual-Core Intel Itanium 2 processors, the new system will generate 13.1 TFLOPs (Teraflops, or trillions of calculations per second) of compute power. This is equal to the combined single precision GPU and CPU horsepower of a modern MacBook [1]. Really makes you think about how resource-intensive even the simplest of modern software is... [1] https://www.cpu-monkey.com/en/igpu-apple_m4_10_core https://www.cpu-monkey.com/en/igpu-apple_m4_10_core
- fweimer 10mo ago
  Note that those 13.1 TFLOPs are FP64, which isn't supported natively on the MacBook GPU. On the other hand, local/per-node memory bandwidth is significantly higher on the MacBook. (Apparently, SGI Altix only had 8.5 to 12.8 GB/s.) Total memory bandwidth on larger Altix systems was of course much higher due to the ridiculous node count. Access to remote memory on other nodes could be quite slow because it had to go through multiple router hops.
- hinkley 10mo ago
  My Apple Watch can blow the doors off a Cray 1. It’s crazy.