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| Started by | Mild Shock <janburse@fastmail.fm> |
|---|---|
| First post | 2026-08-12 02:18 +0200 |
| Last post | 2026-08-14 22:03 +0200 |
| Articles | 2 — 1 participant |
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ANN: Dogelog Player 2.2.5 (π-WAM Channels) Mild Shock <janburse@fastmail.fm> - 2026-08-12 02:18 +0200
Blum’s Speed-Up Theorem and Sudoku (Was: ANN: Dogelog Player 2.2.5 (π-WAM Channels)) Mild Shock <janburse@fastmail.fm> - 2026-08-14 22:03 +0200
| From | Mild Shock <janburse@fastmail.fm> |
|---|---|
| Date | 2026-08-12 02:18 +0200 |
| Subject | ANN: Dogelog Player 2.2.5 (π-WAM Channels) |
| Message-ID | <115ge43$aml4$1@solani.org> |
Dear All, We are happy to announce a new edition of the Dogelog Player: - GPU Backend: The two pilars of π-calculus are processes and channels. While processes in the CPU Backend mapped straight forward to some platform threads and a new predicate execute/[1,2]. The predicate introduced here is expedite/[1,2] and it does the same for your GPU via compute shaders. We observed good results with iGPUs from budget AI laptops. - CPU Channels: We mentioned already that the two pilars of π-calculus are processes and channels. In search of easy channel objects, we arrived at a kind of ADA RendezVous without ACK or NACK. This is basically a 1-element mpmc queue, now available via the predicate chan/1 for the CPU backend. - GPU Channels: Channel objects are now also available for the GPU backend via the predicate flit/1. The approach is again some busy-wait, so dont use CPU or GPU channels for isolated long waits. Because of a batch oriented GPU command API, we could not yet provide online communication between CPU and GPU . Have Fun! Jan Burse, August 12, 2026, https://www.herbrand.ai/
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| From | Mild Shock <janburse@fastmail.fm> |
|---|---|
| Date | 2026-08-14 22:03 +0200 |
| Subject | Blum’s Speed-Up Theorem and Sudoku (Was: ANN: Dogelog Player 2.2.5 (π-WAM Channels)) |
| Message-ID | <115nsb6$flmq$1@solani.org> |
| In reply to | #15854 |
Hi, Years ago Sam Altman said to have no idea how to generate revenue, but when the generally intelligent system is in place, he might ask it. We take Sudoku as the drosophila how different schools deal with “generality”, in this particular instance attacking NP problems with constraint solvers. Every turing machine T has a turing machine T’ that can do multiple steps at once. In propagation methods repeated goal reconstructions happens, while static methods construct goals once. The later is applied in Dogelog Player and looking at AI Escargot it can beat EyeProlog in the browser. Bye See also: Blum’s Speed-Up Theorem and Sudoku https://medium.com/2989/bb8acd0c3284 Mild Shock schrieb: > Dear All, > > We are happy to announce a new edition of > the Dogelog Player: > > - GPU Backend: > The two pilars of π-calculus are processes and > channels. While processes in the CPU Backend > mapped straight forward to some platform threads > and a new predicate execute/[1,2]. The predicate > introduced here is expedite/[1,2] and it does > the same for your GPU via compute shaders. We > observed good results with iGPUs from > budget AI laptops. > > - CPU Channels: > We mentioned already that the two pilars of > π-calculus are processes and channels. In > search of easy channel objects, we arrived at > a kind of ADA RendezVous without ACK or NACK. > This is basically a 1-element mpmc queue, now > available via the predicate chan/1 for > the CPU backend. > > - GPU Channels: > Channel objects are now also available for the > GPU backend via the predicate flit/1. The approach > is again some busy-wait, so dont use CPU or GPU > channels for isolated long waits. Because of a > batch oriented GPU command API, we could not > yet provide online communication > between CPU and GPU . > > Have Fun! > > Jan Burse, August 12, 2026, https://www.herbrand.ai/
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