01 // ARCHITECTURE BREAKTHROUGH
MLA 低秩键值压缩与 DeepSeek企业级私有化部署突破
通过消减 78% 推理 KV Cache 显存开销与无辅助损失专家负载均衡,使千亿参数大模型在企业内网集群中的私有化吞吐率提升 3.4 倍。
- kv_state = full_precision_kv_cache(q, k, v) # 显存占用高,阻碍企业私有化
- loss = task_loss + 0.01 * aux_balance_loss
+ kv_latent = mla_low_rank_compress(hidden, rank=512) # 赋能DeepSeek企业级私有化部署
+ routed = bias_updated_moe_gate(kv_latent, top_k=8) # 无辅助损失动态路由均衡
+ return fp8_tensor_core_gemm(routed)