Invokes a Relay closure. InvokePacked Invokes a TVM compiled kernel. AllocStorage Allocates a storage block. AllocTensor Allocates a tensor value of a certain shape. AllocTensorReg Allocates a tensor ty=int32 */ } } sum_up: alloc_storage 1 1 64 bool alloc_tensor $2 $1 [] uint1 invoke_packed PackedFunc[0] (in: $0, out: $2) load_consti $3 1 if $2 $3 1 2 goto 9 alloc_storage 4 4 64 int32 alloc_tensor $5 $5 $4 [] int32 invoke_packed PackedFunc[1] (in: $0, out: $5) invoke $6 VMFunc[0]($5) alloc_storage 7 4 64 int32 alloc_tensor $8 $7 [] int32 invoke_packed PackedFunc[2] (in: $6, $0, out: $8) move $0 $8

past two decades, tech CapEx has flexed upward at points through data’s long arc – first toward storage / access, then toward distribution / scale, and now toward computation / intelligence. The earliest Growth = Unprecedented96 CapEx Spend – Big Technology Companies = On Rise for Years as Data Use + Storage Exploded97 CapEx Spend @ Big Six* Tech Companies (USA) = +21% Annual Growth Over Ten Years *Note: Year Data: +28% / Year CapEx Spend – Big Technology Companies = On Rise for Years as Data Use + Storage Exploded Big Six* USA Public Technology Company CapEx Spend ($B) vs. Global Data Generation (Zettabytes)

graphs) Direct access from other languages QQ octoML HTVM Overview *。 Plug directly into TVYM as a backend *，Target C to emit code for microcontrollers that is device- agnostic AuroTYM QQ octoML AutoTVM Tet tl 引 -。 Let t2 3 memory planning,， storage Let s = alLLoc_storage(40，64，f32) ; Tet outl = attoc_tensor(s，(19,)，f32); coalescing

MLA, respectively. The amount of KV cache is measured by the number of elements, regardless of the storage precision. For DeepSeek-V2, ?? is set to 4?ℎ and ?? ℎ is set to ?ℎ 2 . So, its KV cache is equal utilization. (2) Secondly, we leverage vLLM (Kwon et al., 2023) with large batch sizes as our inference backend to accelerate the inference speed. (3) Thirdly, we carefully design a scheduling strategy for offloading parameter models. In SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, pages 1–16. IEEE, 2020. C. Riquelme, J. Puigcerver, B. Mustafa, M. Neumann, R. Jenatton

NN/ACL/CMSIS-NN and TVM ○ Integrate optimized ACL/CMSIS-NN kernels into TVM? ○ Implement Arm NN generic backend in TVM for more flexibility with the runtime plugins? ○ Integrate TVM codegen into Arm NN? ● CI

accept subgraphs and build binary/library/engine for runtime dispatching ● Codegen path: src/relay/backend/contrib//codegen.cc ● Flow overview data weight1 weight3 weight2 output Build()

Over the past several decades, with the explosive growth of renewable energy, large-scale energy storage technologies allow intermittent renewable energy to replace traditional energy. High-performance promising candidates for large-scale energy storage intermittent technologies. Since commercialization, lithium-ion batteries (LIBs)have become mainstream energy storage devices with their high output voltage electronic conduction network within the electrode,ultimately resulting in a sharp decline in Li+ storage capacity and attenuation of cycle life. ln order to overcome these problems, previous research

Vectorized load/store for higher bandwidth utilization 。Double buffer to hide memory load latency 。 storage align to reduce bank conflicts of shared memory 。 Virtual threads for data reuse (on going) Performance

ensuring internal governance and compliance. Flexible retention Adjust settings for logging and storage to match your organization’s policies. For more on OpenAI and security, visit our Security page