The Radeon Instinct MI300X is a professional graphics card by AMD, launched on December 6th, 2023. Built on the 5 nm process, and based on the Aqua Vanjaram graphics processor, the card does not support DirectX. Since Radeon Instinct MI300X does not support DirectX 11 or DirectX 12, it...
5.https://www.tomshardware.com/tech-industry/artificial-intelligence/amd-reveals-core-specs-for-instinct-mi355x-cdna4-ai-accelerator-slated-for-shipping-in-the-second-half-of-2025 排版:刘雅坤
5.https://www.tomshardware.com/tech-industry/artificial-intelligence/amd-reveals-core-specs-for-instinct-mi355x-cdna4-ai-accelerator-slated-for-shipping-in-the-second-half-of-2025 排版:刘雅坤
AMD Instinct Solutions Specs Comparisons AI Performance HPC Performance Memory AI Performance (Peak TFLOPs) Up to 1.3X the AI performance vs. competitive accelerators1 TF32 (Sparsity) 989.6 1307.4 0 1000 2000 3000 4000 5000 6000 7000 H100 SXM5 ...
def make_shard_and_gather_fns (partition_specs): def make_shard_fn (partition_spec): out_sharding = NamedSharding (mesh, partition_spec) def shard_fn (tensor): return jax.device_put (tensor, out_sharding).block_until_ready () return shard_fn ...
def make_shard_and_gather_fns (partition_specs): def make_shard_fn (partition_spec): out_sharding = NamedSharding (mesh, partition_spec) def shard_fn (tensor): return jax.device_put (tensor, out_sharding).block_until_ready () return shard_fn ...
shard_fns = jax.tree_util.tree_map (make_shard_fn, partition_specs) return shard_fns # Create shard functions based on partitioning rules shard_fns = make_shard_and_gather_fns (partitioning_rules) 这使得我们能够将每个参数放置在指定的设备上,并按照设定的分片进行处理。
PartQuantity Count UnitsSpecs SKU ID, Performance Units, etc. Processor 96 vCores Intel® Xeon® Scalable (Sapphire Rapids) Memory 1850 GiB Local Storage 1 Disk 1000 GiB Remote Disks 32 Disks 40800 IOPS 612 MBps Network 8 NICs 80000 Mbps Accelerators 8 GPUs AMD MI300X 192 GiB 1535...
(mesh, partition_spec)def shard_fn (tensor):return jax.device_put (tensor, out_sharding).block_until_ready ()return shard_fnshard_fns = jax.tree_util.tree_map (make_shard_fn, partition_specs)return shard_fns# Create shard functions based on partitioning rulesshard_fns = make_shard_and_...
defmake_shard_and_gather_fns(partition_specs):defmake_shard_fn(partition_spec):out_sharding=NamedSharding(mesh,partition_spec)defshard_fn(tensor):returnjax.device_put(tensor,out_sharding).block_until_ready()returnshard_fn shard_fns=jax.tree_util.tree_map(make_shard_fn,partition_specs)returnshar...