inference optimization
4 published articles
Deep Tech
One routing pass to rule them all: 7x faster LLM decoding without the quality trade-off
CLSA uses one routing pass per sequence instead of one per layer, cutting KV-cache overhead while keeping token-level selectivity. Benchmarks show 17.1x throughput improvement at 128K context.
2026-07-26
Artificial intelligence
Aleph alpha's new megakernel library cuts moe inference latency by 200%
Alpha-MoE fuses multiple operations into a single persistent kernel to achieve up to 200% inference speed gains over Triton-based kernels in vLLM and SGLang, targeting FP8-precision MoE models.
2026-07-09
Deep Dive
Aleph Alpha builds theoretical inference model for DeepSeek: Deriving performance from hardware primitives
Aleph Alpha created a theoretical inference model for DeepSeek v3 to estimate throughput from hardware parameters, analyzing trade-offs across GPU setups to help practitioners optimize performance and cost for large MoE models.
2026-07-05
LLM Inference Optimization
Aleph Alpha builds a theoretical inference model to decode DeepSeek V3 performance from hardware primitives
Aleph Alpha's theoretical model predicts DeepSeek V3 inference performance from hardware parameters alone, revealing how GPU count and interconnect bandwidth shift the bottleneck between compute, memory, and communication.
2026-07-04