#parallelcomputing résultats de recherche

Clustering NVIDIA DGX Spark + M3 Ultra Mac Studio for 4x faster LLM inference. DGX Spark: 128GB @ 273GB/s, 100 TFLOPS (fp16), $3,999 M3 Ultra: 256GB @ 819GB/s, 26 TFLOPS (fp16), $5,599 The DGX Spark has 3x less memory bandwidth than the M3 Ultra but 4x more FLOPS. By running…

BOOM! MAJOR AI SPEEDUP! Hot Rod AI 100 times faster inference 100,000 times less power! — Reviving Analog Circuits: A Leap Toward Ultra-Efficient AI with In-Memory Attention I got my start in analog electronics when I was a kid and always thought analog computers would make a…

Sliding window attention (SWA) is powering frontier hybrid models for efficiency. Is there something better? Introducing Phalanx, a faster and better quality drop-in replacement for sliding window attention (SWA). Phalanx is a new family of hardware and numerics-aware windowed…

🚀 Why Parallelization Matters in Web3? From DeFi to GameFi, NFTs to AI-powered dApps — the demand for high-performance execution is exploding. Bitroot’s multi-engine parallel architecture was built to break these limits: ⚡ Parallel transaction processing ⚡ Independent…

𝗖𝗼𝗻𝗰𝘂𝗿𝗿𝗲𝗻𝘁 𝗶𝘀 𝗻𝗼𝘁 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗮𝘀 𝗽𝗮𝗿𝗮𝗹𝗹𝗲𝗹 Most developers use these terms interchangeably. That's a mistake. 𝗖𝗼𝗻𝗰𝘂𝗿𝗿𝗲𝗻𝗰𝘆 is about structure. You design your program so that multiple tasks can progress simultaneously without waiting for…

.@Oracle Acceleron, powered by AMD Pensando DPUs, brings breakthrough performance and security to all workloads. 🔗 Get the details: oracle.com/news/announcem…

Theta EdgeCloud progress in the last year. The first hybrid cloud-edge computing platform for AI, video, rendering, gaming and more. thetaedgecloud.com Empowering AI teams with unrivaled GPU price-to-performance.

.@Oracle and AMD are expanding AI performance and scalability with the general availability of OCI Compute featuring AMD Instinct MI355X GPUs. Built on the AMD CDNA 4 architecture, the MI355X provides nearly 3x the compute power and 50% more high-bandwidth memory, giving…

Prime earnings in @ParallelTCG looking juicy with a Gravity Key 300% hit and the new variant boosts. Down in Platinum too, Diamond and Master earning even more.

Understanding Pharos’ Parallel Execution Framework 🧵

Intelligence has been locked in walled gardens. Today, we’re opening the gates. Parallax now runs in Hybrid mode, with Macs and GPUs serving large models together in a truly distributed framework.

Exploiting the power of the multi-core and many-core processors requires writing parallel algorithms and data structures. Moreover, the implementation also needs to be cache friendly. But these aspects are typically not covered in the introductory courses. I came across this…

Se acabaron los problemas de instalación y las pesadillas de administración. Parallels RAS lo simplifica todo. Contáctame por mensaje privado si quieres saber cómo.

Still training AI on infra built for websites? It’s not your model, it’s your data center. AI needs purpose built infrastructure: ⚙️ GPU clusters for parallel compute 💧 Cooling that can handle megawatts 💾 Storage & bandwidth made for scale Stop forcing 2020s AI on 2000s…

In computer science, there are two general ways to achieve parallel execution: shared memory and message passing. While most blockchains opt for shared memory, ao takes an innovative approach by passing messages. How does it work? 👇

Not All Bits Are Equal: What We Learned From 1700 Experiments on Memory-Optimal Reasoning Given a fixed memory budget, how should you allocate across model weights, KV cache, and test-time compute to maximize accuracy in reasoning models? For example: would you choose a 32B,…

I just read this paper from Google and it's blowing my mind. Usually when you want to do parallel programming you need to have semaphores and mutexes and message passing. But instead, you write two functions: map (from KV to intermediate KV) and reduce (merge intermediate KVs)

Imagine: Parallel Neural Networks with Shaders 🤔 (GLSL instead of CUDA) Parallelization by encoding the weights and activations as Buffer Objects or Textures, using fs to perform matmul and activation functions in parallel. Each fragm shader instance parproc 1..n neuron.